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Cancer risk variation in BRCA1/2 mutation familiesVos, Jantje Rebecca

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Cancer risk variation in BRCA1/2 mutation families

Janet Vos

Vos, J.R.Cancer risk variation in BRCA1/2 mutation families

Thesis, University of Groningen, the Netherlands

ISBN: 978-90-367-8551-8 (printed version) 978-90-367-8550-1 (digital version)

© Copyright J.R. Vos, 2015All rights reserved. No part of this thesis may be reproduced, stored in a retrieval system, or transmitted in any other form or by any means, without the written permission from the author or, when appropriate, from the publishers of the publications.

Cover design & lay-out: Janet VosPrinting: Ridderprint BV, Ridderkerk

The printing of this thesis was financially supported by: ChipSoft BV, Tromp Medical BV, University of Groningen, and University Medical Center Groningen.

Cancer risk variation in BRCA1/2 mutation families

Proefschrift

ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen

op gezag van de rector magnificus prof. dr. E. Sterken

en volgens besluit van het College voor Promoties.

De openbare verdediging zal plaatsvinden op

maandag 14 maart 2016 om 16.15 uur

door

Jantje Rebecca Vos

geboren op 27 juli 1987te Noordoostpolder

PromotoresProf. dr. G.H. de BockProf. dr. M.J.E. Mourits

CopromotorDr. J.C. Oosterwijk

BeoordelingscommissieProf. dr. N. HoogerbruggeProf. dr. K.G.M. MoonsProf. dr. R.H. Sijmons

ParanimfenEsther MettingMarieke van der Linden-Hildering

Chapter 1. General introduction

Chapter 2. Proven non-carriers in BRCA1/2 families have an earlier age of onset of breast cancerEuropean Journal of Cancer 2013; 49:2101-6

Chapter 3. Variation in mutation spectrum partly explains regional differences in the breast cancer risk of female BRCA1/2 mutation carriers in the NetherlandsCancer Epidemiology Biomarkers and Prevention 2014; 23: 2482-91

Chapter 4. Bias correction methods explain much of the variation seen in breast cancer risks of BRCA1/2 mutation carriersJournal of Clinical Oncology 2015; 33: 2553-62

Chapter 5. Inverse birth cohort effects in ovarian cancer: increasing risk in BRCA1/2 mutation carriers and decreasing risk in the general populationGyneacological Oncology 2015, in press

Chapter 6. Bias explains most of the parent-of-origin effect on breast cancer risk in BRCA1/2 mutation carriersSubmitted for publication

Chapter 7. Relevance and efficacy of breast cancer screening in BRCA1 and BRCA2 mutation carriers above 60 years: a national cohort studyInternational Journal of Cancer 2014; 135: 2940-9

Chapter 8. General discussion

Appendices. Nederlandse samenvattingDankwoordCurriculum Vitae

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Table of contents

Chapter 1General introduction

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Chapter 1

Chapter outline

As an introduction to this thesis ‘Cancer risk variation in BRCA1/2 mutation families’ several aspects of the Hereditary Breast and Ovarian Cancer (HBOC) syndrome will be discussed briefly. This chapter starts off with a review of the epidemiology and characteristics of breast and ovarian cancer; followed by a description of several aspects of familial and hereditary cancer (e.g. family history and genetic mutations) and of non-genetic risk factors as well as the current clinical practice regarding referral of families to the Family Cancer Clinic, genetic counseling, and risk prevention. This chapter finishes with the aim and outline of this thesis.

Incidence of breast and ovarian cancer

Breast cancer is the most prevalent cancer among women worldwide.1, 2 In the Netherlands approximately 14,000 invasive breast cancer cases are detected each year, of which about 20-25% is detected before the age of 50.3 The cumulative lifetime risk (CLTR) to develop breast cancer is approximately 12% by age 85 for women in the general population. A positive family history is found in 15-20% of the women with breast cancer, and about 5-10% of all cases is associated with a hereditary mutation.4-7 The most common high risk mutations associated with the HBOC syndrome are those in the autosomal dominant breast cancer genes 1 and 2 (BRCA1/2), as they account for 1-3% of all the breast cancer cases.8, 9 BRCA1/2 mutation carriers have a CLTR up to 88% to develop breast cancer and also an strongly increased risk to develop ovarian cancer.10-13 The breast cancer risk of BRCA1/2 mutation carriers starts to increase at an much earlier age as compared to women in the general population. Approximately half of the patients with BRCA1/2 associated breast cancer is diagnosed before their mid- to end-forties. BRCA1/2 mutation carriers also have an increased risk to develop contralateral breast cancer; which risk is approximately 2-3% per year depending on the age of the primary diagnosis.10, 14-16

Ovarian cancer is less prevalent than breast cancer, but it associated with a worse survival and it is the most lethal gynecologic cancer.3, 17 In the Netherlands every year approximately 1,300 cases are detected, of which 12-16% is detected before the age of 50 years. The CLTR of ovarian cancer for women in the general population is approximately 1.2%.3 About 10-15% of the ovarian cancer cases are familial, and approximately 5-10% can be attributed to a mutation in the BRCA1/2 genes.18-21 BRCA1 mutation carriers have a CLTR of ovarian cancer of 30-60%, and BRCA2 mutation carriers of 5-20%.10-13 Approximately half of the patients with BRCA1/2 associated ovarian cancer is diagnosed before their mid- to end-fifties.

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General introduction

Tumor characteristics

Most invasive breast cancers are infiltrating ductal cancers (70-80%). BRCA1 associated breast cancers most often have a distinct basal-like phenotype, consisting of a higher mitotic index, a higher grade and a triple-negative status (i.e. estrogen receptor (ER), progesterone receptor (PR) and Human Epidermal growth factor Receptor 2 (HER2/neu) negative). 22-26 The BRCA2 associated breast cancers are phenotypically harder to distinguish from sporadic cases.24, 25, 27, 28 They are most often of the luminal type, and are more frequently steroid receptor positive than those associated with a BRCA1 mutation. BRCA2 associated breast cancers have a lower proportion of interval cancers, a higher proportion of DCIS, and a significant higher frequency of a favorable tumor size (≤ 2cm) at time of diagnosis compared with BRCA1 associated breast cancers.29 For BRCA1 associated breast cancers, the percentage of receptor positive cancers increases with increasing age at breast cancer diagnosis, while in BRCA2 associated breast cancers the percentage of receptor positive cancers decreases.30, 31

Ovarian cancer is in about 90% of the cases of epithelial origin, of which many subtypes exist. High-grade serous cancer is the most common (70-80%) and at the same time the most aggressive subtype. BRCA1/2 associated ovarian cancers are most often of this type.32, 33 No clinicopathological differences are known between BRCA1 and BRCA2 associated ovarian carcinoma.34, 35 The site of origin of high-grade serous ovarian cancer is under debate, because ovarian cancer is usually detected in a late stage and precursor lesions are unknown or undetectable. More recently, it has been hypothesized that the fallopian tubes are the site of origin of this ovarian cancer since serous tubal intraepithelial cancer -the first morphological manifestation- has been detected in the tubes.36-39

Family history

About 10-15% of all breast cancer patients has a first-degree relative with breast cancer, and about 15-25% a positive history of breast cancer in first- or second-degree relatives.4,

40-42 Having a first-degree relative with breast cancer increases the risk for breast cancer about 2 times. This risk increase depends on the age of cancer in the relative, and having more affected relatives increases the risk further.4, 40, 43, 44 It is estimated that approximately 30% of the high-risk breast cancer families and 15% of the familial relative risk can be attributed to a pathogenic mutation.7

About 15% of all ovarian cancer patients has a first-degree relative with ovarian cancer.45,46 Having a first-degree relative with ovarian cancer increases the risk for ovarian cancer about 3 times, and having multiple affected relatives increases this risk further.45 About 25% all familial clustering of ovarian cancers is due to a BRCA1/2 mutation.47-49 Whether a ovarian cancer patient carries a BRCA1/2 mutation is not very well predicted by her family history.41, 46, 50

In BRCA1/2 mutation families, the cancer risks cannot be contributed completely to the BRCA1/2 mutation itself.11, 51 Among BRCA1/2 mutation carriers the breast cancer

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Chapter 1

risk and ovarian cancer risk increases when the first-degree family history is positive for the same cancer (i.e. breast and ovarian cancer, respectively), however, a family history of the other cancer might decrease the risks.51, 52

Cancer genetics

The BRCA1 and BRCA2 genes are tumor suppressor genes that contribute to genomic stability through double-stranded DNA repair processes.53, 54 In the general population the carrier frequency of BRCA1 and BRCA2 mutations is estimated to range between 1 in 400 to 1 in 800.55, 56 Over 5,000 different BRCA1/2 mutations have been detected to date, and they occur throughout the entire coding region. Apart for these pathogenic mutations, a vast number of mutations has been detected of which the effect is as yet unclassified (variants of unclassified significance, VUS).57 The position of the mutation on the BRCA gene is statistically significantly correlated to the risk of breast and ovarian cancer, since both ‘breast cancer cluster regions’ and ‘ovarian cancer clusters regions’ on the BRCA genes have been identified.58-60 Some specific BRCA1/2 mutations are more common in populations of a defined geographical or ethnic background (i.e. founder mutations). The BRCA1/2 carrier frequency can be higher in some populations, such as the Ashkenazi Jewish population.61, 62 Besides the BRCA mutations, other moderate and high risk gene mutations are associated with an increased breast and/or ovarian cancer risk. For breast cancer these are mutations in the genes PTEN (Cowden /PTEN Hamartoma Tumor Syndrome), TP53 (Li- Fraumeni syndrome), NF1 (neurofibromatosis type 1), MEN1 (Multiple Endocine Neoplasia type 1), STK11 (Peutz-Jeghers syndrome), PALB2 and CHEK2 1100delC.63-65 For ovarian cancer most of the remaining hereditary ovarian cancer cases are associated with MSH2, MLH1, MSH6 and PMS2 (Lynch syndrome) and STK11 (Peutz-Jeghers syndrome).66

Also common low risk variants, single nucleotide polymorphisms (SNPs), are associated with breast and ovarian cancer. As research on these SNPs is ongoing, the number of SNPs identified is growing and interactions with genetic and non-genetic factors are being identified.67, 68 Some but not all SNPs validated in the general population are confirmed as risk modifiers in BRCA1/2 mutations carriers.69-75 Therefore, the future use of SNPs in risk prediction models is complicated, and its use might also depend on the population of interest.

Risk assessment

Since the discovery of the BRCA1 and BRCA2 genes in the early nineties, multiple studies have been conducted to assess the breast and ovarian cancer risks for mutation carriers, and the probability of carrying a BRCA1/2 mutation. As a result, multiple risk estimations -both absolute and relative cancer risks- and risk assessment tools are available. Over time, several study designs have been applied to estimate cancer risks, such as case-control studies, kin-cohort studies, retrospective cohort studies and more

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recently, prospective cohort studies. The ascertainment of the study population is one of the most important elements when it comes to the estimation of cancer risks. Study populations can roughly be divided in population-based or clinic-based, of which the latter comprise a more selected population based of referral criteria for genetic testing, i.e. one’s personal and family history of cancer. The family history of cancer is a representation of the shared physical environments, lifestyles and genes affecting one’s personal cancer risk. Therefore, all risk assessment tools assessing the cancer risk make use of the family history of cancer, though it depends on the type of tool whether besides breast cancer, also bilateral breast cancer, male breast cancer, ovarian cancer and their ages at diagnosis are considered.43, 76-79 Even when a BRCA1/2 mutation has been detected in a family, apart from the mutation type, the family history still remains relevant for a more tailored risk estimation.51, 52, 80 In addition to family history factors, personal characteristics, demographic, lifestyle, reproductive and hormonal factors can be used for a more tailored risk estimation.81-87

Genetic counseling

Women, who are suspected of carrying a HBOC associated high-risk mutation on the basis of their personal and/or family history of cancer, are referred to a Family Cancer Clinic for counselling and genetic testing.88-90 These referral criteria have changed over time and differ between countries. Currently, in the Netherlands a woman can be referred if her personal or family history meets one of the following criteria: 63, 91

Single casesA history of breast cancer diagnosed <35 yearsA history of epithelial ovarian/fallopian tube cancer any ageA history of bilateral/multiple primary breast cancer, first cancer <50 yearsA history of both breast and ovarian cancerA history of triple negative breast cancer <50 yearsA history of breast cancer diagnosed in a male at any age

Familial cases2 first-degree relatives with breast cancer, one <50 years≥3 breast cancer cases (one <50 years)Breast cancer <50 years and prostate cancer <60 years

Nb. For other genetic predispositions than can be associated with breast and/or ovarian cancer, other referral criteria apply.

The first person in the family who is tested positive for a BRCA1/2 mutation is called the index case. This index case is most often the person in the family who was diagnosed with cancer at the youngest age, with bilateral breast cancer or with (breast and) ovarian cancer, or being a male breast cancer patient. Genetic testing in family members of the index case is performed following a cascade approach.

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In approximately 90% of the referred families, no BRCA1/2 mutation can be detected as an explanation for the strong familiar history of cancer.63 The current criteria for referral are not very specific as they are associated with a limited positive predictive value.92, 93

After the discovery of the BRCA1 and BRCA2 genes, it was expected that over time a BRCA3 gene would be discovered that could explain the high risk in the families with an unexplained increased risk. However, it is clear by now that there might not be a BRCA3 gene responsible for this risk increase, but that multiple very rare high-risk genes, multiple common moderate-risk genes and multiple common SNPs in combination with environmental factors are driving this risk.94, 95

Primary and secondary prevention

Depending on a woman’s cancer risk, different preventive measures are available. For breast cancer screening women are classified as being at population risk or at a slightly increased risk (<20%), at moderate increased risk (20-30%), at high risk (30-40%) or at very high risk (>40%) of breast cancer. Women at population risk or slightly increased risk can opt for breast cancer screening according to the national breast cancer screening program. In the Netherlands this consists of biennial mammographic screening between age 50-75 years. Women with a moderate increased risk get additional screening with annual mammography between age 40-50, and can subsequently enroll in the national screening program, whereas women with a high risk get clinical breast examination between age 35-60 combined with annual mammography, after which they can enter into the national breast cancer screening program. Women at very high risk, i.e. including BRCA1/2 mutation carriers and their untested FDRs, are offered an intensive screening program with an annual clinical breast examination and an annual MRI between age 25-60 years, to which an annual mammogram is added between age 30-60 years. Hereafter they can either continue with annual mammography which will be performed in a hospital or enter into the national screening program till age 75.88, 89 As an alternative to intensive breast cancer screening, BRCA1/2 mutation carriers can opt for preventive surgery. Prophylactic mastectomy reduces the breast cancer risk with approximately 90%, and the residual risk for breast cancer is lower than 5%.96-

98 If a woman is already diagnosed with primary breast cancer, mastectomy of the unaffected breast will substantially reduce the risk of contralateral breast cancer.99, 100 Occult breast cancer, i.e. cancer in the absence of mammographic or physical findings of disease in the breast- at the time of mastectomy is rare.101, 102

Up to 2009, annual screening for ovarian cancer with transvaginal ultrasound and serum tumor marker CA-125 testing was offered to woman at high risk of ovarian cancer. However, after several studies this screening was has stopped due to its proven ineffectiveness: ovarian cancer was not detected in an earlier stage, multiple unnecessary surgeries were performed due to false-positive screening results, and mortality was most likely not reduced.103-106 To reduce the risk of ovarian cancer, women are now advised to undergo a timely risk-reducing salpingo-oophorectomy (RRSO)

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before the ovarian cancer risk rises. For BRCA1 mutation carriers RRSO is offered at the age of 35-40 years, and for BRCA2 mutation carriers at the age of 40-45 years.66, 90, 107 The residual risk of extraovarial ovarian cancer (peritoneal cancer) is about 1% depending on the age at RRSO. Occult invasive ovarian cancer at the time of RRSO is rare.39 RRSO was until recently considered to also significantly reduce the breast cancer risk (up to 50%) when performed before the menopause.108 However, the evidence contradicting this strong beneficial side-effect is becoming more substantial.16, 109-111

Thesis aims and outline

AimCurrently all female BRCA1/2 mutation carriers receive counseling on the basis of population-averaged CLTRs, while the decision making regarding screening and risk-reducing surgery is drastic. More accurate, age-specific and personalized risk estimation would be beneficial for the medical professionals and their patients.

The aim of this thesis is to improve the accuracy of the breast and ovarian cancer risk estimates in BRCA1/2 mutation families, by understanding the reasons for risk variation and assessing the effect of suggested risk modifying factors, especially familial factors, more closely. The implications of these CLTRs for breast cancer screening over age 60 in BRCA1/2 mutation carriers is evaluated.

OutlineWomen in BRCA1 and BRCA2 mutation families can be classified according to the type of mutation and their carrier status, which is either mutation positive (proven by genetic testing or obligate carrier), proven mutation negative or untested. For proven non-carriers it is under debate whether they are still at increased risk as compared to women in the general population. Chapter 2 discusses the breast and ovarian cancer risk of proven non-carriers in clinic-based BRCA1/2 mutation families.

For BRCA1/2 mutation carriers the risk estimates and the reason for the variation in the risk estimates is a topic of debate. For the Northern Netherlands relatively high risks were observed for mutation carriers at older age. Was this a true phenomenon or was it due to bias of differences in methodology? In chapter 3 the breast cancer risk of BRCA1/2 mutation carriers in the Northern-Netherlands is compared with the rest of the Netherlands using similarly ascertained populations and one method for risk estimation. As methodological differences seemed to impact the CLTRs, in chapter 4 the effect of different methods of risk assessment and bias correction is assessed by applying the different methods to one large clinic-based cohort of BRCA1/2 mutation carriers.

Many genetic and environmental factors influence the CLTR of breast and ovarian cancer. In population-averaged risk estimates these factors are usually not taken into account, but for the development of more personalized risk estimations the relative risks are of interest. For BRCA1/2 mutation carriers it is known that the breast cancer risk increases in more recent the birth cohorts, most probably as a consequence of

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changing lifestyles and reproductive factors. The existence of such a trend in the ovarian cancer risk in BRCA1/2 mutation carriers and their background population is discussed in chapter 5. Some risk factors are family-specific or have a high correlation within a family, such as the family history of cancer and type of BRCA1/2 mutation. The parental origin of a BRCA mutation is also such a factor that may affect CLTRs in offspring. In chapter 6 it is discussed whether the parental origin of the BRCA1/2 mutation has an effect on the breast cancer risk of the offspring, when corrected for ascertainment bias.

Breast cancer screening is tailored to a woman’s breast cancer risk classification, as mentioned above. BRCA1/2 mutation carriers are at very high risk of breast cancer and –when they do not choose for preventive mastectomy- receive intensive screening up to at least age 60. As the breast cancer risk continues to increase after this age, the relevance and necessity of additional screening beyond age 60 is investigated and discussed in chapter 7.

Finally, chapter 8 contains a summary and general discussion on the most important results of this thesis.

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28. Brekelmans CT, Tilanus-Linthorst MM, Seynaeve C, vd OA, Menke-Pluymers MB, Bartels CC, et al. Tumour characteristics, survival and prognostic factors of hereditary breast cancer from BRCA2-, B. Eur J Cancer 2007; 43: 867-876.

29. Rijnsburger AJ, Obdeijn IM, Kaas R, Tilanus-Linthorst MM, Boetes C, Loo CE, et al. BRCA1-associated breast cancers present differently from BRCA2-associated and familial cases: long-term follow-up of the Dutch MRISC Screening Study. J Clin Oncol 2010; 28: 5265-5273.

30. Graeser MK, Engel C, Rhiem K, Gadzicki D, Bick U, Kast K, et al. Contralateral breast cancer risk in BRCA1 and BRCA2 mutation carriers. J Clin Oncol 2009; 27: 5887-5892.

31. Van der Groep P, van der Wall E and van Diest PJ. Pathology of hereditary breast cancer. Cell Oncol (Dordr) 2011; 34: 71-88.

32. Rubin SC, Benjamin I, Behbakht K, Takahashi H, Morgan MA, LiVolsi VA, et al. Clinical and pathological features of ovarian cancer in women with germ-line mutations of BRCA1. N Engl J Med 1996; 335: 1413-1416.

33. Pharoah PD, Easton DF, Stockton DL, Gayther S and Ponder BA. Survival in familial, BRCA1-associated, and BRCA2-associated epithelial ovarian cancer. United Kingdom Coordinating Committee for Cancer Research (UKCCCR) Familial Ovarian Cancer Study Group. Cancer Res 1999; 59: 868-871.

34. Boyd J, Sonoda Y, Federici MG, Bogomolniy F, Rhei E, Maresco DL, et al. Clinicopathologic features of BRCA-linked and sporadic ovarian cancer. JAMA 2000; 283: 2260-2265.

35. Reitsma W, de Bock GH, Oosterwijk JC, ten Hoor KA, Hollema H and Mourits MJ. Clinicopathologic characteristics and survival in BRCA1- and BRCA2-related adnexal cancer: are they different?. Int J Gynecol Cancer 2012; 22: 579-585.

36. Dietl J. Revisiting the pathogenesis of ovarian cancer: the central role of the fallopian tube. Arch Gynecol Obstet 2014; 289: 241-246.

37. Gilks CB, Irving J, Kobel M, Lee C, Singh N, Wilkinson N, et al. Incidental nonuterine high-grade serous carcinomas arise in the fallopian tube in most cases: further evidence for the tubal origin of high-grade serous carcinomas. Am J Surg Pathol 2015; 39: 357-364.

38. Reitsma W, Mourits MJ, de Bock GH and Hollema H. Endometrium is not the primary site of origin of pelvic high-grade serous carcinoma in BRCA1 or BRCA2 mutation carriers. Mod Pathol 2013; 26: 572-578.

39. Reitsma W, de Bock GH, Oosterwijk JC, Bart J, Hollema H and Mourits MJ. Support of the ‘fallopian tube hypothesis’ in a prospective series of risk-reducing salpingo-oophorectomy specimens. Eur J Cancer 2013; 49: 132-141.

40. Collaborative Group on Hormonal Factors in Breast Cancer. Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet 2001; 358: 1389-1399.

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41. Hoberg-Vetti H, Bjorvatn C, Fiane BE, Aas T, Woie K, Espelid H, et al. BRCA1/2 testing in newly diagnosed breast and ovarian cancer patients without prior genetic counselling: the DNA-BONus study. Eur J Hum Genet 2015; doi: 10.1038/ejhg.2015.196.

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43. De Bock GH, Jacobi CE, Seynaeve C, Krol-Warmerdam EM, Blom J, van Asperen CJ, et al. A family history of breast cancer will not predict female early onset breast cancer in a population-based setting. BMC Cancer 2008; 8: 203.

44. Brandt A, Bermejo JL, Sundquist J and Hemminki K. Age of onset in familial breast cancer as background data for medical surveillance. Br J Cancer 2010; 102: 42-47.

45. Zhang S, Royer R, Li S, McLaughlin JR, Rosen B, Risch HA, et al. Frequencies of BRCA1 and BRCA2 mutations among 1,342 unselected patients with invasive ovarian cancer. Gynecol Oncol 2011; 121: 353-357.

46. Pal T, Permuth-Wey J, Betts JA, Krischer JP, Fiorica J, Arango H, et al. BRCA1 and BRCA2 mutations account for a large proportion of ovarian carcinoma cases. Cancer 2005; 104: 2807-2816.

47. Prat J, Ribe A and Gallardo A. Hereditary ovarian cancer. Hum Pathol 2005; 36: 861-870.

48. Reedy M, Gallion H, Fowler JM, Kryscio R and Smith SA. Contribution of BRCA1 and BRCA2 to familial ovarian cancer: a gynecologic oncology group study. Gynecol Oncol 2002; 85: 255-259.

49. Jervis S, Song H, Lee A, Dicks E, Harrington P, Baynes C, et al. A risk prediction algorithm for ovarian cancer incorporating BRCA1, BRCA2, common alleles and other familial effects. J Med Genet 2015; 52: 465-475.

50. Alsop K, Fereday S, Meldrum C, deFazio A, Emmanuel C, George J, et al. BRCA mutation frequency and patterns of treatment response in BRCA mutation-positive women with ovarian cancer: a report from the Australian Ovarian Cancer Study Group. J Clin Oncol 2012; 30: 2654-2663.

51. Metcalfe K, Lubinski J, Lynch HT, Ghadirian P, Foulkes WD, Kim-Sing C, et al. Family

history of cancer and cancer risks in women with BRCA1 or BRCA2 mutations. J Natl Cancer Inst 2010; 102: 1874-1878.

52. Teixeira N, Mourits MJ, Vos JR, Kolk DM, Jansen L, Oosterwijk JC, et al. Ovarian cancer in BRCA1/2 mutation carriers: The impact of mutation position and family history on the cancer risk. Maturitas 2015; 82:197-202.

53. O’Donovan PJ and Livingston DM. BRCA1 and BRCA2: breast/ovarian cancer susceptibility gene products and participants in DNA double-strand break repair. Carcinogenesis 2010; 31: 961-967.

54. Welcsh PL, Owens KN and King MC. Insights into the functions of BRCA1 and BRCA2. Trends Genet 2000; 16: 69-74.

55. McClain MR, Palomaki GE, Nathanson KL and Haddow JE. Adjusting the estimated proportion of breast cancer cases associated with BRCA1 and BRCA2 mutations: public health implications. Genet Med 2005; 7: 28-33.

56. Anglian Breast Cancer Study Group. Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Br J Cancer 2000; 83: 1301-1308.

57. Paradiso A and Formenti S. Hereditary breast cancer: clinical features and risk reduction strategies. Ann Oncol 2011; 22 Suppl 1: i31-i36.

58. Thompson D and Easton D. Variation in cancer risks, by mutation position, in BRCA2 mutation carriers. Am J Hum Genet 2001; 68: 410-419.

59. Thompson D, Easton D and Breast Cancer Linkage Consortium. Variation in BRCA1 cancer risks by mutation position. Cancer Epidemiol Biomarkers Prev 2002; 11: 329-336.

60. Rebbeck TR, Mitra N, Wan F, Sinilnikova OM, Healey S, McGuffog L, et al. Association of type and location of BRCA1 and BRCA2 mutations with risk of breast and ovarian cancer. JAMA 2015; 313: 1347-1361.

61. Verhoog LC, van den Ouweland AM, Berns E, van Veghel-Plandsoen MM, van Staveren IL, Wagner A, et al. Large regional differences in the frequency of distinct BRCA1/BRCA2 mutations in 517 Dutch breast and/or ovarian cancer families. Eur J Cancer 2001; 37: 2082-2090.

62. Finkelman BS, Rubinstein WS, Friedman S, Friebel TM, Dubitsky S, Schonberger NS,

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63. Oosterwijk JC, de Vries J, Mourits MJ and de Bock GH. Genetic testing and familial implications in breast-ovarian cancer families. Maturitas 2014; 78: 252-257.

64. Antoniou AC, Casadei S, Heikkinen T, Barrowdale D, Pylkas K, Roberts J, et al. Breast-cancer risk in families with mutations in PALB2. N Engl J Med 2014; 371: 497-506.

65. Adank MA, Hes FJ, van Zelst-Stams WA, van den Tol MP, Seynaeve C and Oosterwijk JC. CHEK2-mutation in Dutch breast cancer families: expanding genetic testing for breast cancer. Ned Tijdschr Geneeskd 2015; 159: A8910.

66. Mourits MJ and de Bock GH. Managing hereditary ovarian cancer. Maturitas 2009; 64: 172-176.

67. Rudolph A, Fasching PA, Behrens S, Eilber U, Bolla MK, Wang Q, et al. A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density. Breast Cancer Res 2015; 17: 110.

68. Fejerman L, Stern MC, John EM, Torres-Mejia G, Hines LM, Wolff RK, et al. Interaction between common breast cancer susceptibility variants, genetic ancestry, and non-genetic risk factors in Hispanic women. Cancer Epidemiol Biomarkers Prev 2015; doi: 10.1158/1055-9965.EPI-15-0392.

69. Prosperi MC, Ingham SL, Howell A, Lalloo F, Buchan IE and Evans DG. Can multiple SNP testing in BRCA2 and BRCA1 female carriers be used to improve risk prediction models in conjunction with clinical assessment? BMC Med Inform Decis Mak 2014; 14: 87.

70. Antoniou AC, Kuchenbaecker KB, Soucy P, Beesley J, Chen X, McGuffog L, et al. Common variants at 12p11, 12q24, 9p21, 9q31.2 and in ZNF365 are associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. Breast Cancer Res 2012; 14: R33.

71. Antoniou AC, Kartsonaki C, Sinilnikova OM, Soucy P, McGuffog L, Healey S, et al. Common alleles at 6q25.1 and 1p11.2 are associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers. Hum Mol Genet 2011; 20: 3304-3321.

72. Antoniou AC, Beesley J, McGuffog L, Sinilnikova OM, Healey S, Neuhausen SL,

et al. Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction. Cancer Res 2010; 70: 9742-9754.

73. Osorio A, Milne RL, Pita G, Peterlongo P, Heikkinen T, Simard J, et al. Evaluation of a candidate breast cancer associated SNP in ERCC4 as a risk modifier in BRCA1 and BRCA2 mutation carriers. Results from the Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA). Br J Cancer 2009; 101: 2048-2054.

74. Mavaddat N, Pharoah PD, Michailidou K, Tyrer J, Brook MN, Bolla MK, et al. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 2015; 107: djv036.

75. Peterlongo P, Chang-Claude J, Moysich KB, Rudolph A, Schmutzler RK, Simard J, et al. Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev 2015; 24: 308-316.

76. Amir E, Freedman OC, Seruga B and Evans DG. Assessing women at high risk of breast cancer: a review of risk assessment models. J Natl Cancer Inst 2010; 102: 680-691.

77. Evans DG, Lalloo F, Wallace A and Rahman N. Update on the Manchester Scoring System for BRCA1 and BRCA2 testing. J Med Genet 2005; 42: e39.

78. Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC, et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 2014; 110: 535-545.

79. Jacobi CE, de Bock GH, Siegerink B and van Asperen CJ. Differences and similarities in breast cancer risk assessment models in clinical practice: which model to choose?. Breast Cancer Res Treat 2009; 115: 381-390.

80. Panchal S, Bordeleau L, Poll A, Llacuachaqui M, Shachar O, Ainsworth P, et al. Does family history predict the age at onset of new breast cancers in BRCA1 and BRCA2 mutation-positive families?. Clin Genet 2010; 77: 273-279.

81. Mitchell G, Antoniou AC, Warren R, Peock S, Brown J, Davies R, et al. Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Res 2006; 66: 1866-1872.

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82. Tice JA, Miglioretti DL, Li CS, Vachon CM, Gard CC and Kerlikowske K. Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer. J Clin Oncol 2015; 33: 3137-3143.

83. Brand JS, Li J, Humphreys K, Karlsson R, Eriksson M, Ivansson E, et al. Identification of two novel mammographic density loci at 6Q25.1. Breast Cancer Res 2015; 17: 75.

84. Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, et al. Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography. BMC Cancer 2015; 15: 143.

85. Hunn J and Rodriguez GC. Ovarian cancer: etiology, risk factors, and epidemiology. Clin Obstet Gynecol 2012; 55: 3-23.

86. Friebel TM, Domchek SM and Rebbeck TR. Modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers: systematic review and meta-analysis. J Natl Cancer Inst 2014; 106: dju091.

87. Key TJ, Verkasalo PK and Banks E. Epidemiology of breast cancer. Lancet Oncol 2001; 2: 133-140.

88. Nationaal Borstkanker Overleg Nederland (NABON). Mammacarcinoma (breast cancer national guideline, version 2.0). 2012. Available at: http://www.oncoline.nl/mammacarcinoom (2012). Accessed 5 Oct 2015.

89. Vereniging Klinische Genetica Nederland (VKGN) en Stichting Opsporing Erfelijke Tumoren (STOET). Hereditair Mamma/Ovariumcarcinoom (Dutch national guideline hereditary breast and ovarian cancer). 2010. Available at: http://www.oncoline.nl/hereditair-mamma-ovariumcarcinoom. Accessed 5 Oct 2015.

90. Commissie Richtlijnen Gynaecologische Oncologie (CRGO) en Integraal Kankercentrum Nederland ( INKL). Richtlijn erfelijk en familiair ovariumcarcinoom (National guideline hereditary and familiar ovarian cancer). 2015. Available at: http://www.oncoline.nl/erfelijk-en-familiair-ovariumcarcinoom. Accessed 5 Oct 2015.

91. De Bock GH, Hesselink JW, Roorda C, De Vries J, Hollema H, Jaspers JP, et al. Model of care for women at increased risk of breast and ovarian cancer. Maturitas 2012; 71: 3-5.

92. van den Broek AJ, de Ruiter K, van ‘t Veer

LJ, Tollenaar RA, van Leeuwen FE, Verhoef S, et al. Evaluation of the Dutch BRCA1/2 clinical genetic center referral criteria in an unselected early breast cancer population. Eur J Hum Genet 2015; 23: 588-595.

93. Warlam-Rodenhuis CC, Koot VC, van der Luijt RB, Vasen HF and Ausems MG. A prospective study on predictive factors linked to the presence of BRCA1 and BRCA2 mutations in breast cancer patients. Eur J Cancer 2005; 41: 1409-1415.

94. Antoniou AC, Pharoah PD, McMullan G, Day NE, Stratton MR, Peto J, et al. A comprehensive model for familial breast cancer incorporating BRCA1, BRCA2 and other genes. Br J Cancer 2002; 86: 76-83.

95. Oldenburg RA, Meijers-Heijboer H, Cornelisse CJ and Devilee P. Genetic susceptibility for breast cancer: how many more genes to be found?. Crit Rev Oncol Hematol 2007; 63: 125-149.

96. Domchek SM, Friebel TM, Singer CF, Evans DG, Lynch HT, Isaacs C, et al. Association of risk-reducing surgery in BRCA1 or BRCA2 mutation carriers with cancer risk and mortality. JAMA 2010; 304: 967-975.

97. Heemskerk-Gerritsen BA, Menke-Pluijmers MB, Jager A, Tilanus-Linthorst MM, Koppert LB, Obdeijn IM, et al. Substantial breast cancer risk reduction and potential survival benefit after bilateral mastectomy when compared with surveillance in healthy BRCA1 and BRCA2 mutation carriers: a prospective analysis. Ann Oncol 2013; 24: 2029-2035.

98. De Felice F, Marchetti C, Musella A, Palaia I, Perniola G, Musio D, et al. Bilateral Risk-Reduction Mastectomy in BRCA1 and BRCA2 Mutation Carriers: A Meta-analysis. Ann Surg Oncol 2015; 22: 2876-2880.

99. Metcalfe KA. Prophylactic bilateral mastectomy for breast cancer prevention. J Womens Health (Larchmt) 2004; 13: 822-829.

100. Rebbeck TR, Friebel T, Lynch HT, Neuhausen SL, van ‘t Veer L, Garber JE, et al. Bilateral prophylactic mastectomy reduces breast cancer risk in BRCA1 and BRCA2 mutation carriers: the PROSE Study Group. J Clin Oncol 2004; 22: 1055-1062.

101. Xia C, Schroeder MC, Weigel RJ, Sugg SL and Thomas A. Rate of contralateral prophylactic mastectomy is influenced by preoperative MRI recommendations. Ann Surg Oncol 2014; 21: 4133-4138.

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102. Erdahl LM, Boughey JC, Hoskin TL, Degnim AC and Hieken TJ. Contralateral Prophylactic Mastectomy: Factors Predictive of Occult Malignancy or High-Risk Lesion and the Impact of MRI and Genetic Testing. Ann Surg Oncol 2015; doi: 10.1245/s10434-015-4660-7.

103. Meeuwissen PAM, Seynaeve C, Brekelmans CTM, Meijers-Heijboer HJ, Klijn JGM and Burger CW. Outcome of surveillance and prophylactic salpingo-oophorectomy in asymptomatic women at high risk for ovarian cancer. Gynecol Oncol 2005; 97: 476-482.

104. Olivier RI, Lubsen-Brandsma MAC, Verhoef S and Van Beurden M. CA125 and transvaginal ultrasound monitoring in high-risk women cannot prevent the diagnosis of advanced ovarian cancer. Gynecol Oncol 2006; 100: 20-26.

105. van der Velde NM, Mourits MJ, Arts HJ, de Vries J, Leegte BK, Dijkhuis G, et al. Time to stop ovarian cancer screening in BRCA1/2 mutation carriers?. Int J Cancer 2009; 124: 919-923.

106. Reade CJ, Riva JJ, Busse JW, Goldsmith CH and Elit L. Risks and benefits of screening asymptomatic women for ovarian cancer: a systematic review and meta-analysis. Gynecol Oncol 2013; 130: 674-681.

107. van Driel CM, de Bock GH, Arts HJ, Sie AS, Hollema H, Oosterwijk JC, et al. Stopping ovarian cancer screening in BRCA1/2 mutation carriers: effects on risk management decisions & outcome of risk-reducing salpingo-oophorectomy specimens. Maturitas 2015; 80: 318-322.

108. Rebbeck TR, Kauff ND and Domchek SM. Meta-analysis of risk reduction estimates associated with risk-reducing salpingo-oophorectomy in BRCA1 or BRCA2 mutation carriers. J Natl Cancer Inst 2009; 101: 80-87.

109. Heemskerk-Gerritsen BA, Seynaeve C, van Asperen CJ, Ausems MG, Collee JM, van Doorn HC, et al. Breast cancer risk after salpingo-oophorectomy in healthy BRCA1/2 mutation carriers: revisiting the evidence for risk reduction. J Natl Cancer Inst 2015; 107: djv033.

110. Chai X, Domchek S, Kauff N, Rebbeck T and Chen J. RE: Breast Cancer Risk After Salpingo-Oophorectomy in Healthy BRCA1/2 Mutation Carriers: Revisiting the Evidence for Risk Reduction. J Natl Cancer Inst 2015; 107: djv217.

111. Fakkert IE, Mourits MJ, Jansen L, van der Kolk DM, Meijer K, Oosterwijk JC, et al. Breast Cancer Incidence After Risk-Reducing Salpingo-Oophorectomy in BRCA1 and BRCA2 Mutation Carriers. Cancer Prev Res (Phila) 2012; 5: 1291-1297.

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Chapter 2Proven non-carriers in BRCA1/2 families

have an earlier age of onset of breast cancer

Janet R. VosGeertruida H. de Bock

Natalia Teixeira Dorina M. van der Kolk

Liesbeth Jansen Marian J.E. Mourits

Jan C. Oosterwijk

European Journal of Cancer 2013; 49(9):2101-6

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Abstract

BackgroundRisk estimates for proven non-carriers in BRCA mutation families are inconsistent for breast cancer and lacking for ovarian cancer. We aimed to assess the age-related risks for breast and ovarian cancer for proven non-carriers in these families.

MethodsA consecutive cohort study ascertained 464 proven non-carriers who had a first-degree relative with a pathogenic BRCA mutation. Kaplan–Meier analyses were used to estimate the age-related cancer risks, and we calculated standardised incidence ratios.

ResultsIn the 464 non-carriers, 17 breast cancers and two ovarian cancers were detected at a mean age of 47 years (95% confidence interval (CI) 32–61) and 49 years (95% CI 32–67), respectively. Overall, by the age of 50, the breast and ovarian cancer risks among non-carriers were 6.4% (95% CI 2.9–9.8%) and 0.4% (95% CI 0–1.3%), of which the breast cancer risk was statistically significantly higher than the risk in the general population. In particular, the number of breast cancers among non-carriers in BRCA1 families was higher than expected for the general population (standardised incidence ratio (SIR) 2.0, 95% CI 1.1–3.3). In the BRCA1 cohort, the mean number of breast cancer cases was higher in families in which non-carriers were diagnosed before the age of 50 (p = 0.04).

ConclusionThe age at diagnosis of breast cancer in non-carriers in BRCA mutation families is younger than expected, yielding an increased risk in the fifth decade. This effect is most evident in BRCA1 families. If our results are confirmed by others, this could affect the advice given on breast cancer screening to proven non-carriers between the age of 40 and 50 in such families.

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Proven non-carriers in BRCA1/2 families have an earlier age of onset of breast cancer

Introduction

Female carriers of a pathogenic mutation in the BRCA1/2 genes have a high risk of developing breast and ovarian cancer: lifetime risks range from 45% to 88% and 11% to 59%, respectively.1-6 Carriers are therefore enrolled in an intensive screening program and may opt to have preventive surgery. In the Netherlands, this program runs from the age of 25–60 years and consists of an annual physical examination, annual breast MRI and, from the age of 30, annual mammography.7 There is no screening program for ovarian cancer, but BRCA1/2 mutation carriers from the age of 35–40 may opt for risk-reducing salpingo-oophorectomy (RRSO).

It has been assumed that women who tested negative for their family-specific BRCA mutation were not at an increased risk.8-11 They are dismissed from intensive screening and referred to our national breast cancer screening program, which consists of biennial mammography from the age of 50–75 years. However, the cancer risk of these proven non-carriers in BRCA-positive families is under debate12 and several studies have published contradictory results on their residual breast cancer risk.8-11, 13-16

The reported risk ratios ranges from 0.39 to 5.3, while there are no figures available for residual ovarian cancer risk.

It is thus uncertain whether non-carriers in BRCA-positive families are rightly being advised to stop screening and to wait until they can enrol in the national program, and we do not know what advice to give them regarding their possible ovarian cancer risk. Our aim was to evaluate the breast and ovarian cancer risks for proven non-carriers who have a first-degree relative with a pathogenic BRCA mutation.

Methods

Our family cancer clinic in the University Medical Center Groningen provides genetic counselling and screening to women who may carry a BRCA mutation based on their personal and/or family history. If the patient or family fulfils the Dutch criteria for genetic testing, comprehensive BRCA1 and BRCA2 mutation testing is performed in one or more index cases.17 Once a pathogenic BRCA mutation has been detected, targeted genetic testing for this mutation is offered to all relatives, using a cascade protocol.18

Information was collected up to March 2008 and previously used to calculate the breast and ovarian cancer penetrance for BRCA mutation families3; this information was updated upto September 2011 for the current study. Data were retrieved from patients’ medical records and entered into a separate, anonymous, password-protected database. Under the Dutch law, this means no further approval from our institution’s Ethics Review Board was needed.

For all women, we collected information on the date of birth and death or last contact, as well as data on the familial gene mutation, their breast- and ovarian cancer status, and if and when a risk-reducing mastectomy (RRM) and/or RRSO had been performed. Data about breast- and ovarian cancer in the general population was

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obtained from the Dutch Comprehensive Cancer Centre.19, 20

All analyses were performed using PASW Statistics 18.0 software, and statistical significance was defined as p < 0.05. Descriptive statistics were applied to analyse patient characteristics, differences in continuous and categorical variables were tested two-sided with the Mann–Whitney U-test and Fishers’ exact test, respectively. Kaplan–Meier survival analyses were used to calculate the cumulative incidence rates. To calculate the breast cancer risk, right-censoring was applied at the age of RRM (N = 1), the age at RRSO if performed before the age of 50 (N = 4), at the last contact, or age at death. In the ovarian cancer risk analyses, women were censored at the age at RRSO (N = 4), at the last contact, or age at death. Standardised incidence ratios (SIRs) were calculated for the age-specific breast cancer incidence, both with and without stratification by the BRCA gene. The numbers of observed cases were compared with the numbers of expected cases, which were calculated using data from the Dutch Comprehensive Cancer Centre.19, 20 To account for possible ascertainment bias, SIRs were also calculated for the group of proven non-carriers expanded with the group of non-tested women. In unaffected women, the probability of testing negative increases with advancing age, so we divided women into 10-year age groups that had different probabilities of being negative. The numbers in each age group were multiplied by the probability of being negative and then added together to obtain the estimated number that would have tested negative.14

Results

In 365 BRCA-positive families (219 BRCA1 and 146 BRCA2 families), 1524 women were tested for a BRCA1 or BRCA2 mutation. Of these, 464 women tested negative for their family-specific BRCA mutation and were included in this study. In total there were 700 untested first-degree female relatives of 20 years or older, of whom 184 (26%) developed breast cancer.

With a mean age at last contact of 44.9 years for the group of non-carriers, 17 women had been diagnosed with breast cancer. Thirteen of these cases were among 283 non-carriers in BRCA1 families (one case was bilateral) and four were among 181 non-carriers in BRCA2 families. For the 17 cases the mean age at diagnosis was 46.5 years (standard deviation (SD) 7.0): 44.8 years (SD 7.2) in BRCA1 families and 51.9 years (SD 2.9) in BRCA2 families (p = 0.045). This mean age at diagnosis was lower than the mean age seen in the general population of 61.9 years (SD 14.3), but the difference was not significant (p = 0.17).3

Two cases of ovarian cancer had been detected, both in non-carriers in BRCA1 families. Their ages at diagnosis were 43 and 55 years, which were much lower than the mean age in the general population (65.5, SD 13.7).

The overall breast cancer risk for non-carriers in BRCA2 families was lower than in BRCA1 families, but this was not significant (hazard ratio = 0.44 (95% confidence interval (CI) 0.14–1.35), p = 0.15). By the age of 60, the non-carriers had a breast cancer risk of 9.5% (95% CI 5.0–14.1%), whereas women in the general population had a risk

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Table 1. Cumulative incidence of breast and ovarian cancer among proven BRCA non-carriers and the general population.

Age (years)

Breast cancer Ovarian cancerProven non-carriersa

General population19

Proven non-carriersa

General population19

40 1.3 (0.0–2.5) 0.6 0.0 (0.0–0.0) 0.150 6.4 (2.9–9.8) 2.5 0.4 (0.0–1.3) 0.160 9.5 (5.0–14) 5.2 1.4 (0.0–3.5) 0.4a 95% confidence interval shown in brackets

0

5

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30 40 50 60Cumulative incidence (%)

A. Breast cancer

Non-carriers

Population

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B. Ovarian cancer

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Age (years)

No. of non-carriers 384 248 141 64 384 252 146 65

Cumulative no. of cases in non-carriers - 4 13 17 - - 1 2

Figure 1. Cumulative incidence of breast cancer (A) and ovarian cancer (B) for non-carriers (with 95% confidence interval) and age-matched women from the general population

of 5.2% (Table 1).19 At all ages, the breast cancer risk was higher in the proven non-carriers than in the age-matched cohort from the general population (Fig. 1). By the age of 50 the breast cancer risk was significantly higher; the expected cumulative incidence was outside the confidence interval of the observed cumulative incidence. The ovarian cancer risk was slightly higher in non-carriers than in the general population from age 50 upwards, but this was not significant (Table 1).

We compared the observed number of breast cancers to the expected number of cases in the general population (Table 2). There were significantly more cases observed in the non-carriers in BRCA1 families in the age groups under 50 years: 30–39 years SIR 11 (95% CI 3.0–29) and 40–49 years SIR 4.5 (95% CI 1.8–9.2). In non-carriers in BRCA2 families, the number of observed cases was not significantly higher than expected. Except for the significantly raised SIRs in the BRCA2 group 40–49 years and the total BRCA group, the SIRs did not change significantly when the calculation was based on non-carriers and a proportion of the 700 women not tested (Table 2).

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The 19 symptomatic non-carriers came from 14 BRCA1 and 4 BRCA2 families. In 204 BRCA families, all the proven non-carriers were still so far free of breast and/or ovarian cancer, while another 143 BRCA families contained no known non-carriers. To assess the difference in cancer incidence due to genetic modifiers and/or environmental factors, we compared the relatives in BRCA families with symptomatic non-carriers to those families without symptomatic non-carriers (Table 3). We observed no differences in the numbers of cases or mean age at diagnosis, or in the cancer risk for either all family members or for the carriers alone. However, among the BRCA1 families, the number of breast cancers was significantly higher in families with non-carriers diagnosed with breast cancer before the age of 50 than in families with non-carriers affected after the age of 50, or in families with no affected non-carriers.

Discussion

We investigated the occurrence of breast and ovarian cancer in 464 proven non-carriers in BRCA families in a consecutive cohort study with a clinic-based ascertainment. We show that the cumulative incidence of breast cancer in proven non-carriers in their fifth decade is 2.6 times higher than in the general population, with a SIR of 3.5 (95% CI 1.6–6.7) and a mean age at diagnosis that was 15 years earlier. This study is the first to assess ovarian cancer risks for proven non-carriers. Only two cases were diagnosed at ages much younger than the mean age at diagnosis in the general population.

Previously published estimates on breast cancer risk in non-carriers in the BRCA families vary widely. We found an increased cancer risk for proven non-carriers at all ages compared with women from the general population. This is in line with three other clinic-based studies from England,14 Canada15 and Poland16 that reported a significantly increased risk of at least twofold. However, four other studies (two clinic-based studies from the United States8, 9 and one from Australia,11 and one population-based study from the United States10) report contradictory results that show that the risk of proven non-carriers is not increased or at least not twice as high as in the general population. Possible explanations may be differences in: (1) ascertainment, (2) study design, or (3) national screening protocols.10 First, studies with ascertainment by a family cancer clinic will probably result in higher risk estimates, since families referred to these clinics have a stronger history of breast cancer than the general population. Second, although a prospective study design is favored,27, 28 it might result in lower risk estimates as a substantial number of the family members have already been diagnosed before visiting the family cancer clinic, and non-symptomatic proven non-carriers are no longer followed-up in such clinics. As an illustration, when we applied left-censoring at the moment of the individual’s DNA test, the follow-up time was short and only a few breast cancer cases were observed in this period. Third, countries with more stringent inclusion criteria for genetic counselling or those in which additional screening for non-carriers is readily available will probably show a larger risk difference between non-carriers in proven BRCA families and the general population.21

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Table 2. Standardised incidence ratios of breast cancer by BRCA gene and age group a in (A) non-carriers and (B) non-carriers and assumed non-carriers.

AgeBRCA1 BRCA2 BRCA total

Obs. Exp. SIR 95% CI Obs. Exp. SIR 95% CI Obs. Exp. SIR 95% CI(A) Non-carriers

30–39 4 0.4 11 3.0–29 0 0.3 – – 4 0.6 6.4 1.7–16

40–49 7 1.6 4.5 1.8–9.2 2 0.9 2.1 0.3–7.6 9 2.6 3.5 1.6–6.7

50–59 2 2.6 0.8 0.1–2.8 2 1.8 1.2 0.1–4.4 4 4.5 0.9 0.2–2.3

Totalb 13 6.6 2.0 1.1–3.3 4 4.7 0.8 0.2–2.1 17 11.6 1.5 0.9–2.3

(B) Non-carriers and not-tested women

30–39 6.5 0.6 11 5.8–19 0.5 0.3 1.6 0.1–11 7 0.9 7.5 3.7–12

40–49 8.6 1.5 3.4 1.9–5.7 4.5 1.6 2.8 1.1–4.7 13 4.2 3.1 2.0–5.0

50–59 4 4.3 0.9 0.4–1.7 4 3.0 1.3 0.9–3.2 8 7.6 1.1 0.6–1.7

Totalb 19 11 1.7 1.0–2.5 9.1 8.3 1.1 0.7–1.9 28 20 1.4 1.0–2.0Abbreviations: obs. observed; exp. expected; SIR standarised incidence ratio; CI confidence intervala No breast cancers were observed after the age of 59 yearsb Ages: 20–69 years

Table 3. Family history of cancer in BRCA carriers and relatives at 50% risk but not tested, in families with and without affected proven non-carriers.

BRCA families a BRCA1 families b Relatives of affected non-carriers N = 115

Relatives of only non-affected non-carriers N = 1174

p Relatives of affected non-carriers with BC < 50 years N = 75

Relatives of (non-)affected non-carriers N = 1214

p

Mean age (standard deviation, SD)Breast cancer 46 (12) 45 (12) 0.45 45 (12.1) 43 (12) 0.41

Ovarian cancer 51 (11) 53 (12) 0.95 53 (12.0) 50(10) 0.29

Number (%)Breast cancers 48 (42%) 417 (36%) 0.19 34 (47%) 264 (34%) 0.04

Ovarian cancers 21 (18%) 169 (14%) 0.34 15 (21%) 131 (17%) 0.42

Abbreviations: BC, breast cancer.a Comparison of BRCA families with affected proven non-carriers with a diagnosis of breast or ovarian cancer and families with only proven non-carriers with no diagnosis of breast or ovarian cancer.b Comparison of BRCA1 families with non-carriers with a breast cancer diagnosis before the age of 50, on the one hand, and BRCA1 families with affected non-carriers at over 50 and BRCA1 families with no affected non-carriers, on the other hand.

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The younger age of proven non-carriers at diagnosis of breast cancer has not been discussed before. Their mean age of breast cancer diagnosis (46.5 years, SD 7.0) is considerably lower than the mean age for the general Dutch population (61.9 years, SD 14.3).3 This is mainly due to the high number of diagnoses in non-carriers in BRCA1 families in the 30–39 and 40–49 year age groups, resulting in SIRs of 11 and 4.5, respectively. Other studies in non-carriers have reported mean ages at diagnosis between 44.3 and 50.9 years.10, 15, 22 The different study approaches may explain the differences found in the mean age at breast cancer diagnosis. The figures we present here are based on a cohort study in a family cancer clinic setting, which included all non-carriers with a first-degree relative carrying a BRCA mutation. To date, the lowest mean age at diagnosis, 44.3 years, was reported in a clinic-based retrospective cohort study that consisted of only Ashkenazi Jewish families, which might explain the lower mean age at diagnosis.22 The highest mean age at diagnosis, 50.9 years, was reported in a population-based study in first-degree relatives in BRCA-negative families, but it also reported mean ages of 42.1 and 44.5 years in BRCA1 - and BRCA2 -positive families, respectively.10

Recent large studies have shown that the genetic variability in breast and ovarian cancer risks can be partly explained by common modifier alleles.14, 23, 24 Therefore, it is likely that a residual increased risk of breast cancer in proven non-carriers from BRCA families will be due to the presence of other familial, predisposing low-risk alleles and/or BRCA penetrance modifiers. We assumed that in families with such penetrance-increasing modifiers, the percentage of symptomatic mutation carriers and the percentage of bilateral cases would be higher, and that their mean age at diagnosis would be lower. We therefore compared these parameters between the families with symptomatic non-carriers and the families with only non-symptomatic non-carriers and found significantly more cases of breast cancer in BRCA1 families with non-carriers diagnosed before the age of 50 than in all other BRCA1 families with proven non-carriers. Future analyses of genetic modifiers and/or environmental factors in our cohort may explain these findings, but at the moment we have no overall explanation for the increased risk seen in young non-carriers from BRCA1 families.

Our study has various strengths, for example, its design as a consecutive cohort with a uniform, clinic-based ascertainment. We consider data obtained from non-carrier populations that are ascertained at family cancer clinics to be different to population-based data and, as such, more applicable to the genetic counselling setting. The women seen at the genetics clinics are the ones to whom the screening policies are actually applied and which are adapted according to their mutation status. Our study is the first to present an ovarian cancer risk assessment for proven non-carriers and the low risk figures appear to be reassuring.

Our study may have been affected by several limitations. First, it might be liable to recall bias because we used information on the family history of cancer reported by women during the course of regular care at the family cancer clinic. However, cases were validated by hospital records or information was provided by first-degree relatives, who are known to report their family cancer history accurately.25, 26 If any bias is present, we are more likely to have under- than overestimated because relatives are more likely to under-report than to over-report cancer. Second, our study could be

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subject to ascertainment bias. Once a non-symptomatic woman has tested negative, she is no longer monitored in a high-risk screening program, and BRCA2 families are less likely to be referred to a family clinic because of the older mean age at diagnosis of breast cancer. Both issues may lead to an under-reporting of cancer and consequently underestimate the cancer incidence in the study population and influence the mean age at diagnosis. However, there was only a minor significant change in the SIRs in the total BRCA group when first-degree relatives who had not been tested were included. Third, selection bias could play a role since no proven non-carriers were known in 143 BRCA families. However, we observed no other differences between these and the other BRCA families, so we would expect any potential effect to be small.

The results from our previous study3 and the current analyses show that female non-carriers in BRCA families are indeed at an increased risk of developing breast cancer from age 40 onwards, which is in line with the results of Smith et al.14 The number of observed cases in non-carriers in the age 40–49 group is significantly increased: SIR 3.5 (95% CI 1.6–6.7). Their risk increase is substantial and may justify starting screening from the age of 40,29 rather than waiting for the national screening protocol which starts at the age of 50.30, 31 The two ovarian cancer cases occurred at an earlier age than seen in the general population, but the very low incidence means that there is no need for medical intervention. Further research into lifestyle and genetic factors is needed to explain the increased breast cancer risk seen in proven BRCA non-carriers.

AcknowledgementWe thank Jackie Senior for editing the manuscript.

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References

1. Chen S, Parmigiani G. Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 2007;25:1329–33.

2. Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet 2003;72:1117–30.

3. van der Kolk DM, de Bock GH, Leegte BK, et al. Penetrance of breast cancer, ovarian cancer and contralateral breast cancer in BRCA1 and BRCA2 families: high cancer incidence at older age. Breast Cancer Res Treat 2010;124:643–51.

4. Evans DG, Shenton A, Woodward E, Lalloo F, Howell A, Maher ER. Penetrance estimates for BRCA1 and BRCA2 based on genetic testing in a clinical cancer genetics service setting: risks of breast/ovarian cancer quoted should reflect the cancer burden in the family. BMC Cancer 2008;8:155.

5. Ford D, Easton DF, Stratton M, et al. Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families: the breast cancer linkage consortium. Am JHum Genet 1998;62:676–89.

6. Easton DF, Ford D, Bishop DT. Breast and ovarian cancer incidence in BRCA1-mutation carriers: breast cancer linkage consortium. Am J Hum Genet 1995;56:265–71.

7. Comprehensive Cancer Centre the Netherlands. Mammacarcinoma (national guideline, version 2.0). Oncolines, cancer clinical practice guidelines. Cited 05/01/2012. Available from: http:// www.oncoline.nl/mammacarcinoom.

8. Domchek SM, Gaudet MM, Stopfer JE, et al. Breast cancer risks in individuals testing negative for a known family mutation in BRCA1 or BRCA2. Breast Cancer Res Treat 2010;119: 409–14.

9. Korde LA, Mueller CM, Loud JT, et al. No evidence of excess breast cancer risk among mutation-negative women from BRCA mutation-positive families. Breast Cancer Res Treat 2011;125: 169–73.

10. Kurian AW, Gong GD, John EM, et al. Breast cancer risk for noncarriers of family-specific BRCA1 and BRCA2 mutations: findings

from the breast cancer family registry. J Clin Oncol 2011;29:4505–9.

11. Harvey SL, Milne RL, McLachlan SA, et al. Prospective study of breast cancer risk for mutation negative women from BRCA1 or BRCA2 mutation positive families. Breast Cancer Res Treat 2011;130:1057–61.

12. Evans DG, Howell A. Breast cancer risk for noncarriers of family-specific BRCA1 and BRCA2 mutations: more trouble with phenocopies. J Clin Oncol 2012;30:1142–3, author reply 1143–4.

13. Katki HA, Gail MH, Greene MH. Breast-cancer risk in BRCAmutation-negative women from BRCA-mutation-positive families. Lancet Oncol 2007;8:1042–3.

14. Smith A, Moran A, Boyd MC, et al. Phenocopies in BRCA1 and BRCA2 families: evidence for modifier genes and implications for screening. J Med Genet 2007;44:10–5.

15. RowanE, PollA, Narod SA.A prospective studyof breast cancer risk in relatives of BRCA1/BRCA2 mutation carriers. JMed Genet 2007;44:e89, author reply e88.

16. Gronwald J, Cybulski C, Lubinski J, Narod SA. Phenocopies in breast cancer 1 (BRCA1) families: implications for genetic counselling. J Med Genet 2007;44:e76.

17. van der Hout AH, van den Ouweland AM, van der Luijt RB, et al. A DGGE system for comprehensive mutation screening of BRCA1 and BRCA2: application in a Dutch cancer clinic setting. Hum Mutat 2006;27:654–66.

18. de Bock GH, Hesselink JW, Roorda C, et al. Model of care for women at increased risk of breast and ovarian cancer. Maturitas 2011;71:3–5.

19. Comprehensive Cancer Centre the Netherlands. Dutch cancer figures. Cited 05/08/2012. Available from: http://www.cijfersover kanker.nl/ .

20. Curado MP, Edwards B, Shin HR, et al., editors. Cancer incidence in five continents, vol. IX. IARC Scientific Publications No. 160, Lyon, IACR.

21. Dorval M, Nogues C, Berthet P, et al. Breast and ovarian cancer screening of non-carriers from BRCA1/2 mutation ositive families: 2-year follow-up of cohorts from France and Quebec. Eur J Hum Genet 2011;19:494–9.

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22. Allweis TM, Sagi M, Peretz T. Sporadic breast cancer among relatives of BRCA mutation carriers. Genet Med 2005;7:655–6.

23. Barnes DR, Antoniou AC. Unravelling modifiers of breast and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers: update on genetic modifiers. J Intern Med 2012;271:331–43.

24. Antoniou AC, Kuchenbaecker KB, Soucy P, et al. Common variants at 12p11, 12q24, 9p21, 9q31.2 and in ZNF365 are associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. Breast Cancer Res 2012;14:R33.

25. Murff HJ, Spigel DR, Syngal S. Does this patient have a family history of cancer? An evidence-based analysis of the accuracy of family cancer history. JAMA 2004;292:1480–9.

26. Sijmons RH, Boonstra AE, Reefhuis J, et al. Accuracy of family history of cancer: clinical genetic implications. Eur J Hum Genet 2000;8:181–6.

27. Goldgar D, Venne V, Conner T, Buys S. BRCA phenocopies or ascertainment bias? J Med Genet 2007;44:e86, author reply e88.

28. Sasieni P. Phenocopies in families seen by cancer geneticists. JMed Genet 2007;44:e82.

29. van Ravensteyn NT, Miglioretti DL, Stout NK, et al. Tipping the balance of benefits and harms favor screening mammography starting at age 40 years. A comparative modeling study of risk. Ann Intern Med 2012;156:609–17.

30. Zonderland HM, Tuut MK, den Heeten GJ, et al. Revised practice guideline ‘screening and diagnosis of breast cancer’. Ned Tijdschr Geneeskd 2008;152:2336–9.

31. Moser K, Sellars S, Wheaton M, et al. Extending the age range for breast screening in England: pilot study to assess the feasibility and acceptability of randomization. J Med Screen 2011;18: 96–102.

Chapter 3Variation in mutation spectrum partly explains

regional diff erences in the breast cancer risk of female BRCA1/2 mutation carriers in the Netherlands

Janet R. Vos

Natalia TeixeiraDorina M. van der Kolk

Marian J.E. Mourits Matt i A. Rookus

Flora E. van LeeuwenMargriet Collée

Christi J. van AsperenArjen R. Mensenkamp

Margreet G.E.M. AusemsTheo A.M. van Os

Hanne E.J. Meijers-Heijboer Encarna B. Gómez-Garcia

Hans F. Vasen Richard M. Brohet

Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON)Annemarie H. van der Hout

Liesbeth Jansen Jan C. Oosterwijk

Geertruida H. de Bock

Cancer Epidemiology Biomarkers and Prevention 2014; 23(11): 2482-91

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Abstract

BackgroundWe aimed to quantify previously observed relatively high cancer risks in BRCA2 mutation carriers (BRCA2 carriers) older than 60 in the Northern Netherlands, and to analyze whether these could be explained by mutation spectrum or population background risk.

MethodsThis consecutive cohort study included all known pathogenic BRCA1/2 carriers in the Northern Netherlands (N = 1,050). Carrier and general reference populations were: BRCA1/2 carriers in the rest of the Netherlands (N = 2,013) and the general population in both regions. Regional differences were assessed with HRs and ORs. HRs were adjusted for birth year and mutation spectrum.

ResultsAll BRCA1 carriers and BRCA2 carriers younger than 60 had a significantly lower breast cancer risk in the Northern Netherlands; HRs were 0.66 and 0.64, respectively. Above age 60, the breast cancer risk in BRCA2 carriers in the Northern Netherlands was higher than in the rest of the Netherlands [HR, 3.99; 95% confidence interval (CI), 1.11–14.35]. Adjustment for mutational spectrum changed the HRs for BRCA1, BRCA2 <60, and BRCA2 ≥60 years by −3%, +32%, and +11% to 0.75, 0.50, and 2.61, respectively. There was no difference in background breast cancer incidence between the two regions (OR, 1.03; 95% CI, 0.97–1.09).

ConclusionsDifferences in mutation spectrum only partly explain the regional differences in breast cancer risk in BRCA2 carriers, and for an even smaller part in BRCA1 carriers.

ImpactThe increased risk in BRCA2 carriers older than 60 may warrant extension of intensive breast screening beyond age 60.

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Variation in the breast cancer risk of female BRCA1/2 mutation carriers in the Netherlands

Introduction

Breast cancer is the most prevalent type of cancer in women. In the Netherlands, women in the general population have a lifetime risk of approximately 11% of developing breast cancer and 1% of ovarian cancer,1 whereas carriers of a pathogenic BRCA1 or BRCA2 mutation have a much higher risk of developing breast and/or ovarian cancer. Two international meta-analyses have estimated a mean breast cancer risk by age 70 of 57% and 65% for BRCA1, and 45% and 49% for BRCA2 mutation carriers (BRCA1/2 carriers),2, 3 Because referred hereditary cases may have an even higher lifetime risk,4 counseling of BRCA1/2 carriers in the Netherlands is still based on an estimated lifetime breast cancer risk of 60% to 80%.5

In a previous study in the Northern Netherlands, relatively high risks were observed inBRCA carriers, especially in BRCA2 carriers older than 60.6 The cumulative incidence for breast cancer by age 70 with inclusion of the index cases was 71% [95% confidence interval (CI), 67%–76%] in BRCA1 carriers and 88% (95% CI, 82%–93%) in BRCA2 carriers. After excluding the index cases, these risks were 60% (95% CI, 55%–66%) and 78% (95% CI, 69%–88%), respectively. These figures, both with and without index cases, are at the high end of published risk estimates in several studies.2, 3, 6-10 Especially, the risk in BRCA2 carriers observed in the Northern Netherlands is high, i.e., higher than the Dutch risks used in counseling.5

Potential explanations for regional or national differences in breast cancer incidence rates are differences in genetic and nongenetic population factors, such as founder mutations, genetic modifiers, demographic composition, and lifestyle factors, as well as differences in ascertainment and methodology.10-16 The contribution of (founder) mutations in theBRCA genes in the ovarian cancer cluster region (OCCR) could, for instance, affect regional risk differences, because mutations within the OCCR are associated with a lower breast cancer risk.17, 18 Regional differences in the population breast cancer incidence, i.e., difference in the baseline risk, could also affect risk differences among BRCA1/2 carriers. We aimed to determine whether there are regional differences in the breast cancer risk in BRCA1/2 carriers in the Netherlands, and if so, whether they could be explained by mutation spectrum or population background risk.

Materials and Methods

The study cohortThe Family Cancer Clinic of the University Medical Center Groningen (UMCG; Groningen, the Netherlands) provides multidisciplinary counseling to residents of the Northern Netherlands.19 This is a stable population,20 and, therefore, feasible to assess the role of mutation spectrum in the existence of regional risk differences.21 The population of the study cohort included all (N = 1,050) women with a pathogenic BRCA mutation (either by testing or obligate carriers, i.e., a women with a child as well as a parent or sibling carrying a mutation) known at the UMCG by September 2011.

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Ascertainment and the DNA testing procedure were described previously.6 Women were included if they were born after 1910, and from a minimum age of 18 years. The index cases were women with: (i) the first detected BRCA1/2 mutation in their family, or (ii) the youngest age at diagnosis of breast or ovarian cancer when the first BRCA1/2 mutation in the family was detected in multiple females at the same time. No index case was defined in the family, when the first mutation was detected in a male or an unaffected woman.

Data collection in the study cohortIn the previous study, data were collected on the occurrence of breast and ovarian cancer in BRCA1/2 carriers in the Northern Netherlands and their first-degree relatives up to March 2008.6 For this study, the dataset was updated by retrieving the patient files, and extended to September 2011. The update included data of: known carriers (N = 233), new carriers (N = 122) in known families and carriers (N = 442) in newly ascertained families.

Information on women seen at the clinic was collected from their clinical genetic records, which also contained extensive and regularly updated pedigree information. Information on obligate carriers was obtained, with consent, from medical records. For all the women included, we recorded: date of birth, date of last contact/death, and data on the familial gene mutation (according to HGVS nomenclature) and individual carrier status, date of breast cancer diagnosis, date of ovarian cancer diagnosis, date of risk-reducing mastectomy (RRM) and, date of risk-reducing salpingo-oophorectomy (RRSO). These data were retrieved from the medical records of patients and entered into a separate, anonymous, password-protected database. According to the Dutch law, this means no further approval from the Institutional Review Board was needed.

Reference populationsThe carrier reference population consisted of all BRCA1/2 carriers from the rest of the Netherlands as registered in the Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) study (N = 2,013), a national cohort of BRCA1/2 families up to 2006.10, 22 The general reference populations were the general population from the Northern Netherlands and the general population in the rest of the Netherlands. Data on the population background risk, i.e., age-related breast cancer incidence, in both regions were collected from the Dutch Comprehensive Cancer Centre (CCN/IKNL) for the period 2005 to 2010.1

Statistical analysisIn the analyses, obligate carriers and proven carriers were considered as one group. The mutation spectrum was assessed by stratifying the mutations for both genes in three previously defined groups: 5′ to the OCCR, in the OCCR, and 3′ to the OCCR.10,17,18 The BRCA1 OCCR was defined as nucleotides 2,282 to 4,071, and the BRCA2 OCCR as nucleotides 2,831 to 6,401.10, 17, 18 The regions downstream and upstream of the OCCR were defined as the first nucleotide at the prime side up to the nucleotide before the start of the OCCR. Large rearrangements were classified in the according category based on their location.

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Descriptive statistics were used to describe the study population and the carrier reference population. Only the first primary breast cancer was considered as an event and censoring was applied at the age of RRM (N = 177), RRSO (N = 342), ovarian cancer diagnosis (N = 298), last moment of contact (N = 914), or death (N = 33). To estimate the cumulative incidence of breast cancer in BRCA1 and BRCA2 carriers in both regions, crude (unadjusted) age-related breast cancer rates were calculated using Kaplan–Meier survival analyses, and the corresponding confidence intervals were calculated with a log–log approach based on Greenwood SEs.23 To adjust for a possible birth cohort effect and mutation spectrum, normalized weights (one divided by the number of combination of the categories of the confounding variables) were calculated and applied in the Kaplan–Meier analyses. Through this weighing, the percentage of women in the different birth cohort categories (≤1920, 1921–1930, 1931–1940, 1941–1950, 1951–1960, 1961–1970 and ≥1971) and the mutation spectrum (5′ to OCCR, OCCR, and 3′ to OCCR) were identical in each category and also in the study and the carrier reference population, without affecting the total sample size.

Regional differences in the age-related breast cancer incidences in BRCA1/2 carriers in the Northern Netherlands compared with the rest of the Netherlands were analyzed using Cox regression analyses. All HRs were adjusted for birth year and mutation spectrum. To correct for ascertainment bias, these analyses were performed with and without the index cases. The assumption of proportionality was checked by assessing the log-minus-log plots and Schoenfeld residuals. The amount of confounding by the mutation spectrum was calculated as the change in the HR (24):

HRadjusted for birth year _ HRadjusted for bith year and mutation spectrum HRadjusted for bith year and mutation spectrum

Differences in the background breast cancer risk in the general population in the UMCG catchment area compared with the rest of the Netherlands were tested using ORs. The cumulative incidence in the general population was calculated using the cumulative rates, which were calculated as the sum of the age-specific breast cancer incidence rates in the general population, multiplied by the width of the age group (i.e., 5 years).25

All analyses were performed using SPSS version 20 (SPSS Inc.) and R version 3.0.1,26 and statistical significance was defined as p < 0.05.

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Results

Characteristics of study and carrier reference populationThe study population consisted of 1,050 BRCA carriers: 656 BRCA1 and 394 BRCA2 (Table 1, data excluding index cases; Supplementary Table S1, data including index cases). These included 29% BRCA1 and 32% BRCA2 index cases. The carrier reference population from the rest of the Netherlands consisted of 1,580 BRCA1 carriers, including 31% index cases, and 433 BRCA2 carriers, including 30% index cases. The study population consisted of relatively more BRCA2 carriers, but the family size of BRCAfamilies was not different between the two populations. The average birth year in the study population was earlier in BRCA1 carriers (1953 vs. 1955, p = 0.025) and BRCA2 carriers (1952 vs. 1957, p < 0.001) compared with the carrier reference population.

Table 1. Clinical characteristics of BRCA1/2 carriers, excluding index cases, in the Northern Netherlands (study population) and in the rest of the Netherlands (reference population)

Characteristics

BRCA1 carriers BRCA2 carriersNorthern Netherlands

Rest of the Netherlands

p Northern Netherlands


p

N = 467 N = 1,091 N = 269 N = 305Age at last follow-up, mean (SD) 47.6 (13.8) 42.1 (11.9) <0.001 48.2 (14.1) 44.9 (11.9) 0.003

Primary breast cancerN (%) 157 (34%) 373 (34%) 0.861 74 (28%) 95 (31%) 0.359Age, mean (SD) 43.6 (9.9) 41.2 (9.0) 0.006 49.1 (9.8) 44.5 (8.1) 0.001At age 60, N(% of all BC cases) 13 (8%) 12 (3%) 0.022 13 (18%) 3 (3%) 0.002

Ovarian cancerN (%) 75 (16%) 80 (7%) <0.001 16 (6%) 21 (7%) 0.735Age, mean (SD) 51.7 (10.0) 51.6 (9.7) 0.972 56.1 (9.6) 55.1 (11.5) 0.799

RRMN (%) 86 (19%) 173 (16%) 0.207 36 (14%) 38 (13%) 0.709

Age, mean (SD) 40.9 (9.7) 39.9 (10.0) 0.486 41.6 (8.8) 41.0 (7.3) 0.740RRSO

N (%) 146 (31%) 227 (21%) <0.001 83 (31%) 49 (16%) <0.001Age, mean (SD) 44.1 (8.5) 44.2 (8.4) 0.791 47.7 (9.6) 46.0 (8.8) 0.326

Presymptomatic BC at DNA test a

N (% of all tests) 252 (78%) 519 (73%) 0.093 180 (83%) 113 (75%) 0.114Older than 60, N (% of presymptomatic test)

23 (9%) 55 (11%) 0.528 19 (10%) 15 (13%) 0.574

Age, mean (SD) 40.3 (13.0) 40.6 (14.0) 0.792 42.2 (13.6) 43.1 (14.1) 0.582Abbreviation: BC, breast cancer.a Data on the demographic details of genetic testing were available for 74% of the populations.

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In the study cohort, including index cases, 46% BRCA1 and 44% BRCA2 carriers developed breast cancer. In the carrier reference population 45% BRCA1 and 42% BRCA2 carriers developed breast cancer (Supplementary Table S1). BRCA1 and BRCA2 carriers in the study population were diagnosed with breast cancer at an older mean age than carriers in the reference population, for BRCA1 42.4 (SD 10.1) versus 40.2 (SD 8.5) years (p = 0.001) and for BRCA2 47.1 (SD 10.6) versus 43.4 (SD 8.6) years (p < 0.001).

The mutation spectrum was known for all BRCA1 and BRCA2 carriers in the Northern Netherlands, and for 88% of BRCA1 and 83% of BRCA2 carriers in the rest of the Netherlands. In the Northern Netherlands, 39% BRCA1 carriers had a mutation within the OCCR versus 23% carriers in the reference population (p < 0.001; Fig. 1). For the BRCA2 mutation in the Northern Netherlands, 18% mutations were within the OCCR versus 65% in the rest of the Netherlands (p < 0.001). This large diff erence in the mutation spectrum between BRCA2 carriers in both populations was due mainly to the presence of three apparent northern founder mutations (c.9672dup, c.7419_7420delTG, and c.1310_1313del: all three outside the OCCR).

5' 15%

OCCR 65%

3' 20%

c.6275_6276delTT

c.5645C>A

c.5345dupA c.5351dupA

c.5213_5216delCTTA

c.5946delT

c.8067T>A

BRCA2 Rest of the Netherlands

5' 26%

OCCR 18%

3' 56%

c.1310_1313delAAGA

c.100G>T

c.3487delG

c.9672dup

c.7419_7420delTG

c.8956dup

c.8754+ 3G>C

BRCA2 Northern Netherlands

5' 29%

OCCR 23%

3' 47%

c.1292dupT c.66dupA

c.2197_2201del5

c.68_69 delAG

c.2685_2686delAA

c.2338C>T c.5333-36_5406+ 400del510

c.5277+ 1G>A

c.4186-1632_4357+2031del3835

c.5266dup

BRCA1 Rest of the Netherlands

5' 25%

OCCR 39%

3' 36%

c.1961delA

c.2685_2686delAA

c.2989_2990dupAA

c.5194-2840_5406+532del11395

c.5333-36_5406

+400del510

c.5503C>T

BRCA1 Northern Netherlands

Figure 1. Overview of mutation spectrum in the study population (Northern Netherlands) and reference population (rest of the Netherlands): 3′ to OCCR (3′), within OCCR (OCCR), and 5′ to OCCR (5′)

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Regional breast cancer risk estimates for carriersFor BRCA1 carriers, the crude cumulative incidence of breast cancer by age 70 was 58% (95% CI, 50%–66%) in the Northern Netherlands, and 68% (95% CI, 62%–73%) in de rest of the Netherlands (Table 2). At 70 years of age, 24 (5%) and 28 (3%) women were still at risk of developing cancer in the BRCA1 study and reference population, respectively (Supplementary Table S2). When the index cases were included in both populations, these risks were 72% (95% CI, 66%–78%) and 76% (95% CI, 71%–79%), respectively. Weighted breast cancer risks that excluded the index cases and incorporated the differences in birth cohorts and mutation spectrum between both populations, resulted in lower risk estimates: 53% (95% CI, 45%–61%) in the Northern Netherlands and 55% (95% CI, 47%–63%) in the rest of the Netherlands (Table 2, Fig. 2; Supplementary Table S3).

In BRCA2 carriers, the breast cancer risk at age 70 was 64% (95% CI, 50%–75%) in the Northern Netherlands and 61% (95% CI, 50%–69%) in the rest of the Netherlands. At 70 years of age, 11 (4%) and 14 (5%) women were still at risk of developing cancer, respectively. When the index cases were included, these risks were 78% (95% CI, 69%–85%) and 72% (95% CI, 64%–78%), respectively. For BRCA2 carriers, the weighted breast cancer risk, excluding the index cases, resulted in higher estimates than the crude risks: by age 70 these were 66% (95% CI, 54%–78%) in the Northern Netherlands and 64% (95% CI, 51%–77%) in the rest of the Netherlands (Table 2).

Weighted cumulative incidence curves stratified by mutation spectrum and the related relative risks are presented in Fig. 3 and in Supplementary Table S4, respectively. The different categories of the mutation spectrum were related to different breast cancer risks, with lower breast cancer risk estimates for mutations within the OCCR. These differences were more outspoken in BRCA2 carriers, and opposite effects (increased vs. decreased risks) were shown in the study population and reference population. No significant differences were revealed in regional comparisons of each specific mutation, but numbers were small (data not shown).

Regional breast cancer risks differencesBRCA1 carriers (excluding index cases) in the Northern Netherlands had a lower risk of developing breast cancer than those in the rest of the Netherlands, HR, 0.66 (95% CI, 0.54–0.81; Table 3, data excluding index cases; Supplementary Table S5, data including index cases). When only data from women with a known mutation spectrum were included, this HR was 0.73 (95% CI, 0.59–0.89). The amount of confounding by the mutation spectrum was 3%. Correction for the mutation spectrum increased the HR with this amount, and resulted in an HR of 0.75 (95% CI, 0.61–0.93).

For the incidence curves of the BRCA2 populations, the assumption of proportionality in the Cox model was not met; the lines crossed at approximately age 60 (Fig. 2). Below age 60, the breast cancer risk of BRCA2 carriers in the Northern Netherlands was lower than that in the rest of the Netherlands, both excluding index cases (HR, 0.64; 95% CI, 0.51–0.81) and including index cases (HR, 0.62; 95% CI, 0.49–0.78). Strikingly, correcting for the mutation spectrum reduced the HR by 32%, which resulted in a 50% lower breast cancer risk in the Northern Netherlands (HR, 0.50; 95% CI, 0.33–0.77). From age 60 onward, however, the breast cancer risk of BRCA2 carriers

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Table 2. Cumulative incidence of breast cancer in BRCA1/2 carriers, excluding index cases, in the study population (Northern Netherlands) and reference population (rest of the Netherlands)

Age, yBRCA1 carriers BRCA2 carriers

Northern Netherlands


Northern Netherlands


Crude risks N = 467 N = 1,091 N = 269 N = 305

≤30 2.8 (1.5–4.7) 3.7 (2.6–5.0) 0.4 (0.0–2.2) 0.7 (0.1–2.3)

≤40 16.0 (12.4–20.0) 23.1 (20.2–26.1) 7.3 (4.3–11.4) 13.3 (9.3–17.9)

≤50 37.8 (31.9–43.6) 46.6 (42.5–50.6) 28.2 (21.3–35.6) 37.6 (30.4–44.7)

≤60 50.1 (43.2–56.7) 61.1 (56.0–65.7) 46.3 (36.5–55.6) 54.8 (45.9–62.9)

≤70 58.4 (50.2–65.7) 67.9 (61.7–73.2) 63.9 (50.3–74.7) 60.6 (50.2–69.4)

≤75 61.2 (51.5–69.4) 71.0 (63.8–77.1) 68.4 (52.7–79.8) —

Weighted risks N = 467 N = 913 N = 269 N = 229

≤30 1.9 (0.8–4.4) 2.7 (1.4–5.4) 0.3 (0.0–6.4) 0.2(0.0–2.0)

≤40 11.8 (8.4–16.4) 17.0 (12.9–22.2) 7.6 (4.1–13.8) 9.5 (4.8–18.2)

≤50 32.3 (26.4–39.0) 36.0 (30.0–42.7) 29.0 (21.3–38.6) 29.9 (20.6–42.1)

≤60 46.8 (39.8–54.4) 49.9 (42.7–57.5) 46.8 (36.8–58.1) 49.1 (37.5–62.1)

≤70 52.8 (45.1–61.0) 54.6 (46.9–62.7) 66.2 (54.2–77.7) 63.7 (50.6–76.6)

≤75 54.2 (46.2–62.7) 58.6 (50.2–67.2) 68.2 (55.8–80.0) —NOTE: Estimation of the crude risk and risk weighted to an equal contribution from the different birth cohorts and OCCR regions in each population (weighted risks).

Table 3. Regional differences in the breast cancer risk of BRCA1/2 carriers, excluding index cases (adjusted for birth year), in the Netherlands: The study population (Northern Netherlands) compared with the reference population (the rest of the Netherlands)

Model

Regional differencesBRCA1 BRCA2 <60 BRCA2 ≥ 60

N(events) HR (95%CI) N(events) HR (95%CI) N(events) HR (95%CI)RegionReference population 1,091 (371) 1 305 (91) 1 29 (3) 1

Study population 467 (141) 0.66 (0.54–0.81) 269 (59) 0.64

(0.51–0.81) 38 (11) 3.99 (1.11–14.35)

Regiona

Reference population 913 (281) 1 224 (56) 1 20 (3) 1


(0.46–0.96) 38 (11) 2.92 (0.81–10.55)

Regiona corrected for OCCRReference population 913 (281) 1 224 (56) 1 20 (3) 1


(0.33–0.77) 38 (11) 2.61 (0.68–10.00)

a Including only carriers with known mutation spectrum.

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in the Northern Netherlands was at least twice as high: the HR was 3.99 (95% CI, 1.11–14.35), excluding the index cases, and 2.56 (95% CI, 1.91–5.48), including the index cases. When we looked at only carriers with known mutation spectrum data, the HRs decreased and became nonsignificant. Correcting for the mutation spectrum reduced the HR by 11% to a HR of 2.61 (95% CI, 0.68–10.0).

Population background incidenceThere seemed to be no significant differences in the breast cancer incidence in the general population between the Northern Netherlands and the rest of the Netherlands: the OR over the ages 20 to 75 was 1.03 (95% CI, 0.97–1.09), younger than 60, 1.02 (95% CI, 0.94–1.11); and older than 60, 1.03 (95% CI, 0.97–1.09). Neither were there birth cohort–related differences in the regional OR, and the cumulative incidence curves were parallel over time (Fig. 2).

Cumulative incidence of breast cancer in BRCA1/2 carriers, excluding index cases, and the general population in the study population (Northern Netherlands) and reference population

(rest of the Netherlands), with the carriers' risk weighted to an equal cont...

Janet R. Vos et al. Cancer Epidemiol Biomarkers Prev 2014;23:2482-2491

©2014 by American Association for Cancer Research

Figure 2. Cumulative incidence of breast cancer in BRCA1/2 carriers, excluding index cases, and the general population in the study population (Northern Netherlands) and reference population (rest of the Netherlands), with the carriers’ risk weighted to an equal contribution from the different birth cohorts and mutation spectrum in each population.

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Variation in the breast cancer risk of female BRCA1/2 mutation carriers in the NetherlandsCumulative incidence of breast cancer in BRCA1 (A) and BRCA2 (B) carriers, excluding index cases, in the Northern Netherlands (study population) and rest of the Netherlands (reference

population), with risk weighted to an equal contribution from the differe...

Janet R. Vos et al. Cancer Epidemiol Biomarkers Prev 2014;23:2482-2491

©2014 by American Association for Cancer Research

Figure 3. Cumulative incidence of breast cancer in BRCA1 (A) and BRCA2 (B) carriers, excluding index cases, in the Northern Netherlands (study population) and rest of the Netherlands (reference population), with risk weighted to an equal contribution from the different birth cohorts in each population.

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Discussion

We aimed to determine whether there were regional differences in the breast cancer risk in BRCA1/2 carriers ascertained and analyzed in one identical way, and if so, whether they could be explained by the mutation spectrum or population background risk. We found that all BRCA1 and the BRCA2 carriers younger than 60 had a significantly lower breast cancer risk in the Northern Netherlands, HRs excluding index cases were 0.66 (95% CI, 0.54–0.81) and 0.64 (95% CI, 0.51–0.81), respectively. From age 60, the breast cancer risk in BRCA2 carriers in the Northern Netherlands was higher than in the rest of the Netherlands (HR excluding index cases, 3.99; 95% CI, 1.11–14.35). Adjustment for the mutation spectrum changed these HRs for BRCA1, BRCA2 < 60, and BRCA2 ≥ 60 by −3%, 32%, and 11%, respectively. The background breast cancer incidence did not explain any risk difference: OR younger than 60 was 1.02 (95% CI, 0.94–1.11) and OR older than 60 was 1.03 (95% CI, 0.97–1.09).

This study confirmed regional breast cancer risk differences, especially for BRCA2 carriers. We estimated a cumulative incidence of breast cancer by age 70, excluding indexes, of 58% (95% CI, 50%–66%) for BRCA1 carriers and 64% (95% CI, 50%–75%) for BRCA2 carriers in the Northern Netherlands. For BRCA1 carriers this was similar to the previous estimate, but the BRCA2 risk decreased from 78% to 64%.6 The lower risk in thisBRCA2 cohort can be explained by the fact that now more carriers (+9%) have a mutation within the OCCR and more carriers (+8%) are born in the ≥1971 cohort as compared with the previous study. Besides, to enable comparison with the national HEBON cohort data, we applied censoring for all RRSOs, whereas in the previous study, censoring was only applied when RRSO was performed before 50 years of age.

Published estimations of the breast cancer life time risk of BRCA1/2 carriers show considerable variation: 40% to 87% for BRCA1 and 28% to 88% for BRCA2 carriers.2, 3,

7-9, 27 This variation can be explained by differences in population, in ascertainment and in methodology. Our current estimates of lifetime risks for the rest of the Netherlands are higher than those recently published in the same cohort 10: 68% (95% CI, 62%–73%) versus 45% (95% CI, 36%–52%) for BRCA1, and 61% (95% CI, 50%–69%) versus 27% (95% CI, 14%–38%) for BRCA2 carriers. These low estimates of Brohet and colleagues10 can be explained by inclusion of older birth cohorts (with lower breast cancer penetrance), and by the applied method (modified segregation analysis has a stronger correction for bias). When they included only cohorts from 1940 onward, their estimates substantially increased: from 45% to 66% for BRCA1 and 27% to 32% for BRCA2 by age 65. Though based on mainly retrospective data, our breast cancer risk estimates of the carriers in the Netherlands are very similar to those published in a recent prospective study: 60% (95% CI, 44%–75%) for BRCA1 and 55% (95% CI, 41%–70%) for BRCA2 carriers by age 70.27 However, in this prospective study the peak incidence among BRCA2 carriers was in the age group 40 to 49 years, which is earlier than in the Netherlands.

We found that differences in the mutation spectrum between the Northern Netherlands and the rest of the Netherlands partly explained the regional breast cancer risk differences, which was seen in the adjusted HRs and illustrated with weighted risk estimates. The magnitude of confounding by the mutation spectrum was largest

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(32%) among BRCA2 carriers below 60, as compared with 3% and 11% in BRCA1 and BRCA2 carriers older than 60, respectively. Our analyses showed that BRCA1 carriers and BRCA2 carriers younger than 60 that live in the Northern Netherlands have a lower breast cancer risk than those in the rest of the Netherlands: the HRs adjusted for birth year and OCCR were 0.75 and 0.50, respectively. Controversially, above age 60, BRCA2 carriers in the Northern Netherlands had a higher, though statistically nonsignificant, breast cancer risk (adjusted HR, 2.61; 95% CI, 0.68–10.00). When the crude and adjusted BRCA2 ≥60 model only included carriers with a known mutation spectrum, the risk difference was insignificant, which was probably due to a lack of power. The differences in the breast cancer risks between each gene region, and the different distribution of mutations between the Northern Netherlands and the rest of the Netherlands, underline the importance of the confounding effect of mutation spectrum. Strikingly, in BRCA2 the HRs of the 3′ versus the 5′ region were significantly different in the opposite direction in both the study and the reference population. This might indicate that smaller defined regions on the BRCA2 gene could explain breast cancer risk differences better, making the (previously found) regional differences in the frequency of specific BRCA1 or BRCA2 mutations in the Netherlands even more important.12

We found that the breast cancer incidence of women in the general population did not differ between the Northern Netherlands and the rest of the Netherlands (OR, 1.03; 95% CI, 0.97–1.09), and this cannot, therefore, explain the regional risk differences among BRCA1/2 carriers. In a recent report from the Dutch Institute for Public Health and the Environment, it was shown that in one of the three northern provinces of the Netherlands, there was a small, but statistically significant, increased breast cancer risk of 1.06 compared with the national average risk, whereas for the other two provinces the 1.02 and 1.03 risk increase was nonsignificant.28

The strengths of our study are the inclusion of the relevant target population of BRCA1/2 carriers (i.e., carriers who receive the actual counseling), the large sample size, and the partly prospectively collected data. Our study gives a new perspective on the existence and explanation of regional differences in the breast cancer risk of BRCA1/2 carriers, using a two-way approach involving genes (mutation spectrum) and environment (population background risk). Moreover, the study and the carrier reference population are family clinic–based populations, using the same national referral and DNA testing criteria and methodology, with well-documented information on carrier status and cancer development. Differences in the ascertainment between the study and reference carrier population could affect the results. However, comparison of indicators of the ascertainment of both populations showed that 76% of the tests were presymptomatic, and showed no statistically significant differences in proportion of (pre)symptomatic genetic tests, mean age at genetic test, proportion of test above age 60 and proportion of these tests per family. The population in the Northern Netherlands was ascertained up to September 2011 and the Rest of the Netherlands up to 2006, but there was also no indication for testing bias when only carriers ascertained up to 2006 were assessed. This more recent period of ascertainment is a likely explanation for the higher uptake of preventive surgery in the northern region. Up to 2006, women were offered the choice between ovarian screening and RRSO. From

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2007 onward, counseling changed and ovarian screening was gradually abandoned because of proven ineffectiveness. Our center was one of the first centers to change this policy. As a result, women more often choose for RRSO and RRM, and also at an earlier age.29 The RRSOs were truly prophylactic because before RRSO all women underwent transvaginal ultrasonography and serum marker CA125 to exclude manifest ovarian cancer.30 Underreporting of preventive surgery in the rest of the Netherlands was very unlikely as medical files of proven carriers were available.

A limitation of our study is that the BRCA1/2 carriers were ascertained through family cancer clinics, which may have resulted in an overestimation of the breast cancer risks. Moreover, the study population included both incident and prevalent breast cancer cases, which also could have led to overestimation. However, the overestimation is negligible, because the follow-up time of known carriers and former untested relatives (N = 273) was extended with 61 months (SD 40), and included 19 new primary breast cancers, which is only 6% of all cases.

Besides, the percentage of ovarian cancer and preventive surgery was higher in the study population as compared with the reference population. This may have led to a higher percentage of censored cases in the study population. Therefore, the breast cancer risk could be underestimated in the study population as compared with the carrier reference population, because after these censoring events some carriers will develop breast cancer.31 Because the medical files were available, underestimation of the risk due to missing data on breast cancer, ovarian cancer, or preventive surgery is unlikely. For the rest of the Netherlands, missing data for the age at cancer diagnosis in the pedigree were imputed on the basis of birth cohort–specific population data.10 However, it is unknown whether this was necessary for the carriers included in this study (born after 1910). Future linking to national pathology and cancer registries will help to identify and quantify missing data.

In conclusion, BRCA1/2 carriers in the Northern Netherlands were at lower risk of developing breast cancer than in the rest of the Netherlands, except for BRCA2 carriers older than 60, whose risk was doubled. Differences in the mutation spectrum between the two regions partly explain the risk differences seen in BRCA1/2 carriers, with a somewhat stronger effect in BRCA2 carriers. Both for BRCA1 and BRCA2 carriers, the detected regional risk differences could not be explained by differences in the background cancer risk in their respective general populations. Possible other explanations for the regional risk differences could be differences in (founder) mutations in modifier genes, lifestyle and/or gene–environment interactions. Especially, a large scale international study on the breast cancer risk and mutation position in BRCA carriers can be worthwhile due to the limited sample sizes in this study. The increased risk in BRCA2 carriers older than 60 in the Northern Netherlands should be a good reason to consider extending intensive breast cancer screening to BRCA2 carriers beyond the age of 60 in this region.

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AcknowledgmentsThe authors thank Jackie Senior for editing the final version of the article. HEBON thanks the registration teams of the Comprehensive Cancer Centre Netherlands and Comprehensive Centre South (together the Netherlands Cancer Registry) and PALGA (Dutch Pathology Registry) for part of the data collection.

The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) consists of the following Collaborating Centers: Coordinating center: Netherlands Cancer Institute, Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, F.E. van Leeuwen, S. Verhoef, M.K. Schmidt, J.L. de Lange, R. Wijnands; Erasmus Medical Center, Rotterdam, NL: M. Collée, A.M.W. van den Ouweland, M.J. Hooning, C. Seynaeve, C.H.M. van Deurzen, I.M. Obdeijn; Leiden University Medical Center, NL: C.J. van Asperen, J.T. Wijnen, R.A.E.M. Tollenaar, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Center, NL: C.M. Kets, A.R. Mensenkamp; University Medical Center Utrecht, NL: M.G.E.M. Ausems, R.B. van der Luijt; Academic Medical Center, NL: C.M. Aalfs, T.A.M. van Os; VU University Medical Center, Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital Maastricht, NL: E.B. Gómez-Garcia, M.J. Blok; University Medical Center Groningen, NL: J.C. Oosterwijk, A.H. van der Hout, M.J. Mourits, G.H. de Bock; The Netherlands Foundation for the Detection of Hereditary Tumours, Leiden, NL: H.F. Vasen; The Netherlands Cancer Registry: S. Siesling; The Dutch Pathology Registry (PALGA): L.I.H. Overbeek.

Grant SupportThe HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, and NKI2007-3756, the Netherlands Organization of Scientific Research grant NWO 91109024, the Pink Ribbon grant 110005, and the BBMRI grant NWO 184.021.007/CP46 (to M.A. Rookus and F.E. van Leeuwen).

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Supplementary Table 1. Clinical characteristics of BRCA1/2 carriers including index cases in the Northern Netherlands (study population) and in the rest of the Netherlands (reference population)

Characteristics

BRCA1 carriers BRCA2 carriers

Northern NetherlandsN = 656

Rest of the NetherlandsN = 1580

p Northern NetherlandsN = 394

Rest of the NetherlandsN = 433

p

FamiliesNumber 220 575 142 174Number carriers per family, median (IQR) 2 (1-4) 2 (1-3) 0.080 2 (1-4) 2 (1-3) 0.059

Age at last follow-up, mean (SD) 48.5 (13.3) 42.7 (11.4) <0.001 49.9 (13.5) 45.0 (11.4) <0.001

Primary breast cancer Number (%) 304 (47%) 714 (45%) 0.608 174 (44%) 183 (42%) 0.622Age, mean (SD) 42.4 (10.1) 40.2 (8.5) 0.001 47.1 (10.6) 43.4 (8.6) <0.001Above age 60, N (% of all breast cancers) 20 (7%) 16 (2%) 0.001 27 (16%) 9 (5%) 0.001

Ovarian cancerNumber (%) 136 (21%) 153 (10%) <0.001 43 (11%) 34 (8%) 0.121Age, mean (SD) 50.6 (9.3) 51.4 (9.2) 0.449 56.7 (9.6) 54.9 (10.1) 0.435

RRMNumber (%) 130 (20%) 259 (16%) 0.050 58 (15%) 53 (12%) 0.307

Age, mean (SD) 41.3 (9.4) 41.1 (9.6) 0.831 42.9 (8.1) 42.1 (7.7) 0.600RRSO

Number (%) 214 (33%) 355 (23%) <0.001 126 (32%) 80 (19%) <0.001Age, mean (SD) 45.4 (8.6) 44.8 (8.3) 0.420 47.9 (9.1) 46.6 (8.4) 0.302

Abbreviations: IQR: interquartile range, RRM: risk-reducing mastectomy; RRSO: risk-reducing salpingo-oophorectomy; RRSO: risk-reducing salpingo-oophorectomy

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lem

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ry T

able

2. O

verv

iew

of n

umbe

r of c

arri

ers (

excl

udin

g in

dex

case

s) a

t ris

k at

eac

h ag

e-de

cade

and

num

ber o

f bre

ast c

ance

r ev

ent f

or e

ach

age-

deca

de

Age

BRC

A1

carr

iers

BRC

A2

carr

iers

Nor

ther

n N

ethe

rlan

dsR

est o

f the

Net

herl

ands

Nor

ther

n N

ethe

rlan

dsR

est o

f the

Net

herl

ands

N

(N o

f eve

nt)

Inci

denc

e (9

5%C

I)N

(N

of e

vent

)In

cide

nce

(95%

CI)

N

(N o

f eve

nt)

Inci

denc

e (9

5%C

I)N

(N

of e

vent

)In

cide

nce

(9

5%C

I)

20-3

064

(10)

15.6

(8.7

-27.

1)15

9 (3

7)23

.3 (1

7.5-

30.7

)34

(1)

2.9

(0.0

-19.

1)26

(2)

7.7

(2.0

-27.

4)30

-40

142

(48)

33.8

(26.

7-42

.2)

410

(153

)37

.3 (3

2.8-

42.2

)65

(13)

20.0

(12.

1-31

.9)

99 (3

0)30

.3 (2

2.3-

40.4

)40

-50

133

(52)

39.1

(31.

4-47

.9)

301

(128

)42

.5 (3

7.2-

48.3

)76

(27)

35.5

(25.

9-47

.4)

98 (4

0)40

.8 (3

1.8-

51.2

)50

-60

64 (2

1)32

.8 (2

2.8-

45.8

)13

6 (4

2)30

.9 (2

3.9-

39.4

)55

(18)

32.7

(22.

0-46

.8)

52 (1

9)36

.5 (2

5.1-

51.1

)60

-70

37 (9

)24

.3 (1

3.5-

41.5

)47

(9)

19.2

(10.

5-33

.6)

27 (1

0)37

.0 (2

1.9-

57.9

)16

(3)

18.8

(6.5

-47.

5)70

-75

24 (1

)4.

2 (0

.6-2

6.1)

25 (2

)8.

0 (2

.1-2

8.4)

11 (1

)9.

1 (1

.3-4

9.2)

7 (0

)-

Supp

lem

enta

ry T

able

3. C

umul

ativ

e in

cide

nce

of b

reas

t ca

ncer

in B

RCA

1/2

carr

iers

, exc

ludi

ng in

dex

case

s, in

the

stu

dy p

opul

atio

n (N

orth

ern

Net

herl

ands

) and

ref

eren

ce p

opul

atio

n (r

est o

f the

Net

herl

ands

). Es

timat

ion

of r

isks

wei

ghte

d to

an

equa

l con

trib

utio

n fr

om

the

diffe

rent

bir

th c

ohor

ts in

eac

h po

pula

tion.

Age

, y

BRC

A1

carr

iers

BRC

A2

carr

iers

Nor

ther

n N

ethe

rlan

dsN

= 4

67R

est o

f the

Net

herl

ands

N =

109

1N

orth

ern

Net

herl

ands

N =

269

Res

t of t

he N

ethe

rlan

dsN

= 3

05

≤30

2.1

(1.0

-4.4

)3.

1 (1

.8-5

.3)

0.4

(0.0

-4.3

)0.

4 (0

.0-3

.9)

≤40

11.5

(8.3

-15.

8)17

.6 (1

4.1-

21.9

)7.

5 (4

.3-1

3.0)

10.3

(6.4

-16.

4)

≤50

31.1

(25.

6-37

.4)

37.0

(32.

0-42

.5)

28.1

(21.

2-36

.7)

26.8

(20.

0-35

.4)

≤60

44.0

(37.

4-51

.1)

52.4

(46.

5-58

.5)

48.8

(39.

5-58

.9)

44.7

(36.

0-54

.4)

≤70

50.9

(43.

6-58

.7)

58.7

(52.

4-65

.1)

64.3

(53.

5-75

.0)

52.6

(43.

0-62

.9)

≤75

53.1

(45.

3-61

.3)

63.4

(56.

7-70

.2)

68.0

(56.

5-79

.0)

-

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4. R

elat

ive

risk

s (ha

zard

ratio

s (95

% c

onfid

ence

inte

rval

)) of

bre

ast c

ance

r for

mut

atio

n sp

ectr

um, e

xclu

ding

inde

x ca

ses

BRC

A1

Ref

eren

ce a

mut

atio

ns

The

Net

herl

ands

bN

orth

ern

Net

herl

ands

cR

est o

f the

Net

herl

ands

c

5’ N =

394

OC

CR

N =

382

3’ N =

604

5’ N =

116

OC

CR

N =

182

3’ N =

169

5’ N =

278

OC

CR

N =

200

3’ N =

435

5’N

A1.

04(0

.79-

1.36

)1.

33*

(1.0

6-1.

68)

NA

0.76

(0

.50-

1.16

)1.

06

(0.7

0-1.

61)

NA

1.26

(0

.88-

1.80

)1.

47*

(1.1

2-1.

94)

OC

CR

0.97

(0.7

3-1.

27)

NA

1.29

*(1

.01-

1.64

)1.

32(0

.86-

2.02

)N

A1.

39(0

.95-

2.06

)0.

79(0

.56-

1.13

)N

A1.

17(0

.85-

1.60

)

3’0.

78*

(0.6

1-0.

99)

0.75

* (0

.60-

0.94

)N

A0.

94

(0.6

2-1.

43)

0.72

(0

.49-

1.06

)N

A0.

68*

(0.5

2-0.

90)

0.86

(0.6

3-1.

17)

NA

BRC

A2

Ref

eren

ce a

mut

atio

ns

The

Net

herl

ands

bN

orth

ern

Net

herl

ands

cR

est o

f the

Net

herl

ands

c

5’ N =

105

OC

CR

N =

200

3’ N =

194

5’ N =

73

OC

CR

N =

48

3’ N =

148

5’ N =

32

OC

CR

N =

152

3’ N =

45

5’N

A0.

44*

(0.2

7-0.

70)

0.72

(0.4

8-1.

10)

NA

0.43

* (0

.20-

0.91

)0.

55*

(0.3

3-0.

91)

NA

0.53

(0.2

7-1.

05)

1.22

(0.5

8-2.

57)

OC

CR

2.29

*(1

.43-

3.68

)N

A1.

66*

(1.0

5-2.

62)

2.35

*(1

.10-

5.01

)N

A1.

28(0

.61-

2.69

)1.

89(0

.95-

3.75

)N

A2.

30*

(1.3

0-4.

06)

3’1.

39

(0.9

1-2.

10)

0. 6

0*

(0.3

8-0.

96)

NA

1.83

*(1

.10-

3.04

)0.

78

(0.3

7-1.

63)

NA

0.82

(0

.39-

1.73

)0.

44*

(0.2

5-0.

77)

NA

Abb

revi

atio

ns: N

A: n

ot a

pplic

able

a The

BRC

A1

OC

CR

was

defi

ned

as n

ucle

otid

es 2

282

to 4

071,

and

the

BRCA

2 O

CC

R as

nuc

leot

ides

283

1 to

640

1 (1

0, 1

7, 1

8). T

he re

gion

s do

wns

trea

m a

nd

upst

ream

of t

he O

CC

R w

ere

defin

ed a

s th

e fir

st n

ucle

otid

e at

the

prim

e si

de u

p to

the

nucl

eotid

e be

fore

the

star

t of t

he O

CC

R. T

he c

ateg

orie

s lis

ted

as th

e re

fere

nce

mut

atio

ns a

re th

e re

fere

nce

cate

gory

in th

e C

ox re

gres

sion

mod

el.;

b Adj

uste

d fo

r reg

ion

and

birt

h ye

ar; c A

djus

ted

for b

irth

yea

r, * S

igni

fican

t (p

< 0.

05)

55

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Supplementary Table 5. Regional differences in the breast cancer risk of BRCA1/2 carriers including index cases (adjusted for birth year) in the Netherlands: the study population (Northern Netherlands) compared to the reference population (the rest of the Netherlands)

Model

Regional differencesBRCA1 BRCA2 <60 BRCA2 ≥ 60

N(events) HR (95%CI) N(events) HR (95%CI) N(events) HR (95%CI)RegionReference population 1580 (711) 1 305 (91) 1 29 (3) 1

Study population 656 (279) 0.66 (0.58-0.77) 269 (59) 0.62

(0.49-0.78) 38 (11) 2.56 (1.91-5.48)

Regiona

Reference population 1384 (612) 1 224 (56) 1 20 (3) 1


(0.47-0.77) 38 (11) 2.02 (0.94-4.34)

Regiona corrected for OCCRReference population 1384 (612) 1 224 (56) 1 20 (3) 1


(0.35-0.61) 38 (11) 1.88 (0.80-4.41)

a Including only carriers with known mutation spectrum

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21. Lutke Holzik MF, Sonneveld DJ, Hoekstra HJ, Te Meerman GJ, Sleijfer DT, Schaapveld M. Do the eastern and northern parts of the Nether lands differ in testicular cancer? Urology 2001;58:636–7.

22. Van Asperen CJ, Brohet RM, Meijers-Heijboer EJ, Hoogerbrugge N, Verhoef S, Vasen HF, et al. Cancer risks in BRCA2 families: estimates for sites other than breast and ovary. J Med Genet 2005;42:711–9.

23. Greenwood M. The errors of sampling of the survivorship tables. Reports on public health and statistical subjects. HMSO 1926;33: 1–26

24. Hosmer D, Lemeshow S, May S. Applied survival analysis—regression modeling of time to event data. Hoboken: Wiley-Internscience, 2011.

25. Dos Santos Silva I, editor. Cancer epidemiology: principles and methods. Lyon, France: International Agency for Research on Cancer, 1999.

26. R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; c2013. Avail able from: http://www.R-project.org/

27. Mavaddat N, Peock S, Frost D, Ellis S, Platte R, Fineberg E, et al. Cancer risks for BRCA1 and BRCA2 mutation carriers: results from prospective analysis of EMBRACE. J Natl Cancer Inst 2013;105:812–22.

28. Den Hertog FRJ, Van Dijk BAC, Luth TK. [Number of invasive breast tumours 2006–2009] Aantal invasieve borsttumoren 2006–2009. Volksgezondheid Toekomst Verkenning, Nationale Atlas Volksge-zondheid. Bilthoven: RIVM; c2011. Available from: http://www.zor gatlas.nl/gezondheid-en-ziekte/ziekten-en-aandoeningen/kanker/ aantal-invasieve-borsttumoren/

29. Van Driel CM, Eltahir Y, de Vries J, Jaspers JP, Oosterwijk JC, Mourits MJ, et al. Risk-reducing mastectomy in BRCA1/2 mutation carriers: factors influencing uptake and timing. Maturitas 2014;77:180–4.

30. Reitsma W, de Bock GH, Oosterwijk JC, Bart J, Hollema H, Mourits MJ. Support of the ‘fallopian tube hypothesis’ in a prospective series of risk-reducing salpingo-oophorectomy specimens. Eur J Cancer 2013; 49:132–41.

31. Fakkert IE, Mourits MJ, Jansen L, van der Kolk DM, Meijer K, Oosterwijk JC, et al. Breast cancer incidence after risk-reducing salpingo-oophorectomy in BRCA1 and BRCA2 mutation carriers. Cancer Prev Res 2012;5:1291–7.

Chapter 4

Bias correction methods explain much of the variation seen in breast cancer risks of

BRCA1/2 mutation carriers

Janet R. VosLi Hsu

Richard M. Brohet Marian J.E. Mourits

Jakob de Vries Kathleen E. Malone

Jan C. OosterwijkGeertruida H. de Bock

Journal of Clinical Oncology 2015; 33(23): 2553-62

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Abstract

Purpose Recommendations for treating patients who carry a BRCA1/2 gene are mainly based on cumulative lifetime risks (CLTRs) of breast cancer determined from retrospective cohorts. These risks vary widely (27% to 88%), and it is important to understand why. We analyzed the effects of methods of risk estimation and bias correction and of population factors on CLTRs in this retrospective clinical cohort of BRCA1/2 carriers.

Patients and Methods The following methods to estimate the breast cancer risk of BRCA1/2 carriers were identified from the literature: Kaplan-Meier, frailty, and modified segregation analyses with bias correction consisting of including or excluding index patients combined with including or excluding first-degree relatives (FDRs) or different conditional likelihoods. These were applied to clinical data of BRCA1/2 families derived from our family cancer clinic for whom a simulation was also performed to evaluate the methods. CLTRs and 95% CIs were estimated and compared with the reference CLTRs.

Results CLTRs ranged from 35% to 83% for BRCA1 and 41% to 86% for BRCA2 carriers at age 70 years width of 95% CIs: 10% to 35% and 13% to 46%, respectively). Relative bias varied from −38% to +16%. Bias correction with inclusion of index patients and untested FDRs gave the smallest bias: +2% (SD, 2%) in BRCA1 and +0.9% (SD, 3.6%) in BRCA2.

Conclusion Much of the variation in breast cancer CLTRs in retrospective clinical BRCA1/2 cohorts is due to the bias-correction method, whereas a smaller part is due to population differences. Kaplan-Meier analyses with bias correction that includes index patients and a proportion of untested FDRs provide suitable CLTRs for carriers counseled in the clinic.

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Bias correction methods and breast cancer risks of BRCA1/2 mutation carriers

Introduction

Since the discovery of the BRCA genes 20 years ago, numerous retrospective studies have been performed to estimate the cumulative lifetime risk (CLTR) of breast cancer for pathogenic BRCA1/2 gene mutation carriers.1-44 However, results of these studies show considerable variation: CLTRs by the age of 70 years vary from 27% to 88%, and the width of the 95% CI estimates range from 6% to 97%. Recently, estimates from prospectively collected cohorts were obtained. These were, for BRCA1, 55% to 60% (95% CI, 37% to 76%) and, for BRCA2, 55% to 72% (95% CI, 41% to 88%).45, 46 However, because prospective data are limited and available estimates vary, recommendations for managing BRCA1/2 carriers are still primarily based on retrospective risk estimates. Therefore, it is important to identify the source of the large variation in these retrospective estimates. The current lack of clarity can be troublesome for BRCA1/2 carriers and their physicians, particularly in the context of considering preventive treatment options.

The wide range of risk estimates in the retrospective cohorts of BRCA carriers may be attributable to a combination of two main factors: population differences, such as genetic, demographic, and lifestyle factors, and methodologic differences, such as population ascertainment and referral criteria, methods of risk estimation, and correction for selection bias.47-49 Although the observed variation in risk has often been attributed to population differences, it is unclear if some analytic approaches generate systematically higher or lower breast cancer risk estimates and which methods yield more precise estimates than others.

Our objective was to assess the effects of systematically identified risk estimation and bias-correction methods and population factors on CLTR point estimates and 95% CIs. We specifically surveyed published methods, applied them to the Family Cancer Clinic database at our university medical center, and compared our results with a reference using simulated datasets on the basis of this clinical data as well as to published prospective and retrospective data.

Patients and Methods

Methods to Estimate the Risk of Breast Cancer in BRCA1/2 CarriersWe searched the literature using the keywords breast cancer, BRCA, and risk in the subject heading and/or title and abstract fields in three databases (PubMed, Embase, and Web of Science) to systematically identify the different risk estimation and bias-correction methods applicable to a clinically ascertained cohort of carriers with a pathogenic BRCA1/2 gene mutation. The search was restricted to studies published in English through July 2014 that included a study population of a clinical cohort of female mutation carriers. A flow diagram of the search is presented in the Data Supplement. The selection procedure and an additional search of the selected articles’ reference lists yielded 201 reports of potential relevance, which were then reviewed in detail for their risk-estimation methods. Of these, 184 studies were excluded because

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the method was not applicable to a retrospective clinical cohort or because only risk ratios were presented.

In total, 19 methods for risk estimation were identified and applied to our data (Fig. 1 and Data Supplement). Eleven were Kaplan-Meier analyses (including three analyses of incident cases and two analyses with bootstrapping),6, 14, 19, 21, 28, 37, 40, 44, 50-53

four were frailty models, and four were modified segregation analyses.24, 25, 27, 29, 41, 54

Kaplan-Meier analysisKaplan-Meier analysis allows estimation of survival over time. This nonparametric model can only incorporate independent observations; therefore, familial clustering and subject ascertainment are not taken into account. Bias correction was performed by one or a combination of the following: excluding index patients, including all untested female first-degree relatives (FDRs) who were treated as carriers, including only incident breast cancer cases, or including a proportion of untested female FDRs. The proportion of FDRs was estimated as the ratio of positive and negative DNA tests per age group defined by a 10-year interval from our data.

Kaplan-Meier analysis with bootstrapping at the family levelKaplan-Meier analysis with bootstrapping at the family level is a nonparametric analysis in which the 95% CI was corrected for familial clustering by bootstrapping with families as sampling units. Bias correction was performed by including untested FDRs that were weighted on the basis of the calculated posterior probabilities of untested FDRs carrying the mutation given their phenotypes and mutational frequency.

Frailty modelThe frailty model is a semiparametric model in which the familial clustering was accounted for by a hypothetical frailty for shared risk among family members. The frailty term has a multiplicative effect on the baseline hazard and provides a family-specific cancer risk. The marginal or population-averaged CLTR was calculated by integrating out the frailty term.55, 56 In this analysis, a semiparametric frailty model with a gamma frailty distribution was used,57 and included only carriers, or carriers and untested relatives.

Modified segregation analysisThe modified segregation analysis is a semiparametric analysis in which the familial clustering was accounted for by polygenic effects. All members in the pedigree, that is, FDRs and beyond, were included. CLTRs were calculated on the basis of estimated age group–specific hazard ratios and the cancer incidence of the general population.20

Correction for genetic testing and ascertainment bias was performed by maximizing the conditional likelihood of observing the genotypes and phenotypes in the pedigree, given the genotype and phenotype of the index patient or index carrier and the phenotypes of other family members in the pedigree or given all phenotypes only.

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Box 1. Definitions• Index carrier: The first family member (male or female) who tested positive for the

mutation, irrespective of their cancer status at the time of the DNA test.• Index patient: If the index carrier was affected by breast and/or ovarian cancer at the

time of the DNA test, he/she becomes the index patient. The index patients are a subgroup of the index carriers.

• Untested FDRs: Women who did not undergo genetic testing and who are FDRs of a male or female carrier, and therefore have a 50% a priori chance of being a carrier.

• Proportion of untested FDRs: The estimated proportion of assumed carriers among the untested FDRs. The proportion of FDRs assumed to be carriers were included in our analyses and treated as carriers.

• Incident breast cancer cases: Cases that have arisen after the first positive DNA test in the family, that is, after the date of the index carrier’s test. Only years at risk and events from this date forward were included in our analyses.

Application DatasetTo assess the effect of the different methods for statistical analyses and bias correction, we applied them to a well-defined, retrospective clinical cohort consisting of 192 extended BRCA mutation-positive families (112 BRCA1 families and 80 BRCA2 families) from our family cancer clinic.51, 52 We also simulated data on the basis of our clinic database and applied all methods to these simulated data. As the true estimates are known in simulation, this helped us to assess the bias of overestimation or underestimation of the CLTR of these methods.

This family cancer clinic at the University Medical Center Groningen is the sole provider of genetic counseling in the northern region of the Netherlands. Information on breast and ovarian cancer and prophylactic surgery was available for 395 female BRCA1 and 232 female BRCA2 carriers and their untested female FDRs (349 in BRCA1 and 176 in BRCA2 families) ≥ 18 years old (Table 1). Pedigree information was available for 2,255 BRCA1 and 1,359 BRCA2 family members, including FDRs and beyond (Table 2). Only one proven carrier was present in 27 (14%) of the 192 families

During the normal course of genetic risk counseling, patients were asked to provide information on their family history, and family pedigrees were drawn. In a previous study that included 185 of the current families, pedigrees were drawn and data on family members were collected.51 Data from this previous study were recorded in a database and updated through September 2011.52 The database contained information on the BRCA mutation, pedigree structure, date of birth, date of death or last contact, date of breast and/or ovarian cancer diagnosis, date of prophylactic surgery, and carrier status of family members. Missing were 2% to 3% of the dates of death or dates of breast and/or ovarian cancer and 10% of the dates of birth. These missing values were imputed by using national tumor-, period-, and/or age-specific incidence and/or survival rates.53

This clinical dataset was used as basis for generating 50 datasets with 100,000 three-generation families consisting of 18 relatives. For each individual, we generated a mutational status for the BRCA genes, a polygenic component that represents other familial risk factors, follow-up time, breast cancer status, and censoring events (Appendix, online only).

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Table 1. Characteristics of Individual Female BRCA1/2 Mutation Carriers (including index patients) and Their Untested First-Degree Female Relatives

Characteristics

BRCA1 BRCA2Carriers(n = 395)

FDRs(n = 349)

Carriers(n = 232)

FDRs(n = 176)

Genetic testAge of index patient at testing, mean (SD)Age at index carriers’ test, mean (SD)

48.7 (9.8)47.1 (19.3)

NA63.1 (29.7)

50.6 (10.5)48.7 (17.9)

NA64.2 (27.3)

Breast cancer in index patientsNo. (%)Age, years, mean (SD)

Breast cancerNo. (%)Age, years, mean (SD)

78 (80.4)40.1 (9.0)

182 (46.1)42.5 (9.8)

NANA

59 (16.9)45.7 (13.0)

56 (90.3)44.9 (9.3)

105 (45.3)46.7 (10.3)

NANA

43 (24.4)51.1 (12.0)

Ovarian cancer in index patientsNo. (%)Age, years, mean (SD)

Ovarian cancerNo. (%)Age, years, mean (SD)

34 (35.1)48.4 (7.6)

89 (22.5)51.0 (10.1)

NANA

41 (11.7)51.4 (10.1)

14 (22.6)54.5 (12.1)

25 (10.8)55.7 (11.9)

NANA

11 (6.3)62.9 (11.8)

RRMNo. (%)Age, years, mean (SD)

84 (21.3)41.5 (9.9)

1 (0.3)36.5 (NA)

48 (20.7)43.1 (8.0)

0 (0)NA

RRSONo. (%)Age, years, mean (SD)

155 (39.2)45.6 (9.0)

3 (0.9)45.8 (17.7)

100 (43.1)47.9 (9.4)

1 (0.6)41.5 (NA)

Abbreviations: RRM, risk-reducing mastectomy; RRSO, risk-reducing salpingo-oophorectomy; NA, notapplicable.

Table 2. Characteristics of BRCA1/2 Mutation Families

Characteristics

BRCA1 families (n = 112) BRCA2 families (n = 80)

OverallNo. (%)

Per family *median No. (IQR)

OverallNo. (%)

Per family *median No. (IQR)

Family membersFemales

2,255 (100) 1,171 (51.9)

15 (10-28)7 (4-14)

1,359 (100)677 (9.8)

13 (10-19)7 (4-9)

Index casesFemales

97 (4.3)97 (100)

1 (1-1)1 (1-1)

66 (4.9)62 (93.9)

1 (1-1)1 (1-1)

Index carriersFemales

112 (5.0)111 (99.1)

1 (1-1)1 (1-1)

80 (5.9)73 (91.3)

1 (1-1)1 (1-1)

Mutation carriers 511 (22.7) 3 (2-6) 318 (23.4) 3 (2-5)Untested relatives 1,105 (49.0) 7 (5-14) 615 (45.3) 6 (4-8)Non-carriers 639 (28.3) 4 (2-8) 426 (31.3) 4 (2-7)Female cancer #

Female breast cancerOvarian cancer

257 (21.9)138 (11.8)

2 (1-3)2 (1-2)

158 (23.3)40 (5.9)

2 (1-2)0 (0-1)

Male breast cancer # 2 (0.2) 0 (0-0) 7 (1.0) 0 (0-0)Abbreviations: IQR, interquartile range; NA, not applicable.* Data are presented irrespective of the family size ( i.e., not weighted by family size)# Numbers and percentages per gender

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Statistical AnalysisPopulation-averaged CLTRs and 95% CIs (floating 95% CIs for modified segregation analysis20) were estimated by using the different risk-estimation and bias-correction methods we had identified. In all analyses, primary breast cancer cases were counted as events, and the censoring time was defined as the first date of the following events: diagnosis of ovarian cancer, risk-reducing mastectomy, risk-reducing salpingo-oophorectomy, or death or last contact.

First, the effects of the risk-estimation and bias-correction methods were assessed by comparing the CLTR estimates by age 70 and the width of the corresponding 95% CI in our real clinic data. Second, the CLTR estimates and 95% CIs were compared with the reference in our simulated data. We specifically calculated mean CLTRs and 95% CIs widths for the 50 simulated datasets. Third, we assessed the effect of study-population factors by comparing the CLTR estimates and 95% CIs from our clinic data to the published CLTR estimates that had been obtained by the same method.

Kaplan-Meier and frailty model analyses were performed with a statistical program (version 22; SPSS, Chicago, IL) and with R software (R Foundation for Statistical Computing, Vienna, Austria).57, 58 Modified segregation analyses were performed in MENDEL (Department of Human Genetics, University of California, Los Angeles, CA) using additional subroutines.20, 59, 60

Box 2. Statistical Terms• Right censoring: By the time that a censoring event occurs, a woman has not

developed breast cancer. Years at risk and events after the right censoring are not counted in the analyses.

• Bootstrapping at family level: Randomly drawing samples (with the same sample size) from the original dataset to estimate the CI. The samples are of the same size as the original dataset; therefore, one family can be included multiple times in the same data sample.

• Width of 95%CI: Indicator of the uncertainty around the CLTRs. It is calculated by subtracting the lower CI from the upper CI.

• Relative bias: Measure of underestimation and overestimation of the reference CLTR, calculated as: (estimated CLTR − reference CLTR)/reference CLTR.

Results

Comparison of Breast Cancer Risk Estimates and CIs Across Analytical MethodsTable 3 shows the CLTR estimate and 95% CI for each method on the basis of the real data. Kaplan-Meier analyses (including all carriers with bias correction by excluding index patients, including all untested FDRs, or including a proportion of untested FDRs) yielded estimates by age 70 years of 35% to 66% (width of the 95% CI, 10% to 19%) for BRCA1 carriers and 41% to 73% (width of the 95% CI, 13% to 26%) for BRCA2 carriers. Overall, analyses that excluded the index patients and included all untested female FDRs yielded the lowest CLTRs (for BRCA1, 35%; 95% CI, 30% to 40%; and for BRCA2, 41%; 95% CI, 34% to 49%).

Including only incident cases yielded the highest CLTRs and the widest 95% CIs,

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with values of 67% to 83% (width of the 95% CI, 34% to 35%) for BRCA1 carriers and 73% to 86% (width of the 95% CI, 42% to 45%) for BRCA2 carriers. Estimates from the incident cases analyses including all carriers and FDRs were similar to the estimated CLTRs without any correction. For BRCA1, the result was 66% (95% CI, 59% to 74%) and for BRCA2, 73% (95% CI, 63% to 82%).

The bootstrap approach (including all carriers, with bias corrected by excluding index patients and including a proportion of FDRs) yielded estimates by age 70 years of 66% to 73% (width of the 95% CIs, 15% to 17%) for BRCA1 carriers and 70% to 80% (width of the 95% CIs, 18% to 32%) for BRCA2 carriers. Their point estimates were higher and their 95% CIs were wider than those of the Kaplan-Meier analyses that included a proportion of FDRs.

The frailty model, including all carriers, with bias corrected by excluding index patients and/or including all untested FDRs, produced point estimates similar to those of the Kaplan-Meier analyses. However, the range of the 95% CIs was somewhat wider. The CLTRs were 35% to 67% (width of the 95% CI, 11% to 19%) for BRCA1 carriers and 41% to 74% (width of the 95% CI, 14% to 29%) for BRCA2 carriers.

Modified segregation analyses with a conditional joint likelihood yielded lower CLTRs by age 70 years. Results were 37% to 57% (width of the 95% CI, 24% to 32%) for BRCA1 carriers and 42% to 53% (width of the 95% CI, 32% to 46%) for BRCA2 carriers. When the likelihood was conditional solely on the basis of phenotypes, the CLTR of 53% (95% CI, 43% to 61%) for BRCA1 carriers was still relatively low. However, the CLTR of 67% (95% CI, 56% to 76%) for BRCA2 carriers was relatively high. The analyses with conditioning of the genotype on the basis of index carriers or index patients were most comparable with the Kaplan-Meier analyses that included all FDRs, while excluding or including index patients.

Relative Bias of Breast Cancer Risk Estimates in Simulated Data Across Analytical MethodsThe CLTR of all methods varied from 35% to 66% in BRCA1 mutation carriers and from 43% to 74% in BRCA2 mutation carriers (Fig 2). Compared with the reference, this translated into a variation in the relative bias of −38% to +16% and −36% to +11%, respectively (Appendix Table 2, online only).

Bias-correction methods that yielded the smallest bias and uncertainty were Kaplan-Meier analysis with inclusion of index patients and untested FDRs (+2.0%; SD, 2.1, in BRCA1 carriers and +0.9%; SD, 3.6, in BRCA2 carriers) and the modified segregation analysis conditioned on phenotype only (+2.7%; SD, 2.2, in BRCA1 carriers and +2.5%; SD, 3.4, in BRCA2 carriers). Kaplan-Meier analysis with bootstrapping at the family level was, on average, the least biased, but its uncertainty was relatively higher because relative bias differed for all datasets, with +0.0%, (SD, 5.7) in BRCA1 carriers and −1.8% (SD, 8.7) in BRCA2 carriers.

Kaplan-Meier analyses with exclusion of the index patient and inclusion of FDRs, as well as the modified segregation analyses conditioned on all phenotypes and genotypes of the index patient or carrier, produced the most underestimated risk with relative biases greater than 20%. However, these methods yielded risk estimates that approximated the risk of a carrier in the general population.

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Cum

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g in

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clud

ing

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ses

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clud

ing

prop

ortio

n of

unt

este

d FD

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clud

ing

inde

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ses

& in

clud

ing

all u

ntes

ted

FDRs

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udin

g in

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case

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clud

ing

inde

x ca

ses

& in

clud

ing

prop

ortio

n of

unt

este

d FD

RsEx

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ing

inde

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ses

& in

clud

ing

all u

ntes

ted

FDRs

161/

395

212/

590

218/

744

87/2

9813

8/49

314

4/64

7

66.4

54.5

43.6

54.3

45.4

34.9

58.7

-74.

049

.0-6

0.3

38.9

-48.

545

.2-6

4.0

39.4

-52.

031

.1-4

0.2

101/

232

139/

332

144/

408

46/1

7084

/270

89/3

46

72.9

63.6

51.9

55.7

52.1

40.5

63.2

-81.

856

.2-7

0.9

45.5

-58.

643

.0-6

9.1

43.6

-61.

233

.7-4

8.1

Kap

lan-

Mei

er in

cide

nt c

ases

ana

lysi

s ǂ

Excl

udin

g in

dex

case

sEx

clud

ing

inde

x ca

ses

& in

clud

ing

prop

ortio

n of

unt

este

d FD

RsEx

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ing

inde

x ca

ses

& in

clud

ing

all u

ntes

ted

FDRs

23/1

6725

/232

26/2

89

83.4

75.6

67.2

62.5

-96.

256

.3-9

0.9

49.1

-84.

2

10/1

1410

/139

10/1

37

86.0

77.6

72.7

56.9

-99.

051

.5-9

5.5

47.6

-92.

7K

apla

n-M

eier

ana

lysi

s w

ith b

oots

trap

ping

at f

amily

-leve

lIn

clud

ing

inde

x ca

ses

& in

clud

ing

prop

ortio

n of

unt

este

d FD

RsEx

clud

ing

inde

x ca

ses

& in

clud

ing

prop

ortio

n of

unt

este

d FD

Rs20

8/49

513

6/40

372

.866

.065

.4-8

0.2

57.5

-74.

413

9/33

284

/270

80.4

70.5

71.6

-89.

354

.3-8

6.6

Frai

lty m

odel

ana

lysi

sIn

clud

ing

inde

x ca

ses

Incl

udin

g in

dex

case

s &

incl

udin

g al

l unt

este

d FD

RsEx

clud

ing

inde

x ca

ses

Excl

udin

g in

dex

case

s &

incl

udin

g al

l unt

este

d FD

Rs

161/

395

218/

744

87/2

9814

4/64

7

67.4

44.7

54.4

35.1

59.6

-75.

139

.4-4

9.9

45.0

-63.

829

.8-4

0.4

101/

232

144/

408

46/1

7089

/346

73.9

53.3

56.2

41.3

64.2

-83.

746

.5-6

0.2

41.7

-70.

733

.9-4

8.8

Mod

ified

seg

rega

tion

anal

ysis

#

Join

t lik

elih

ood

cond

ition

ed o

n ge

noty

pe o

f ind

ex c

arri

ers

and

all p

heno

type

sJo

int l

ikel

ihoo

d co

nditi

oned

on

geno

type

of i

ndex

cas

es a

nd a

ll ph

enot

ypes

Join

t lik

elih

ood

cond

ition

ed o

n ge

noty

pe o

f ind

ex c

ases

and

phe

noty

pes

at ti

me

of in

dex

case

s’ D

NA

-test

Retr

ospe

ctiv

e lik

elih

ood

cond

ition

ed o

nly

on a

ll ph

enot

ypes

156/

1,06

015

8/1,

074

158/

1,07

423

0/1,

171

36.6

40.7

57.1

52.8

18.8

-50.

425

.6-5

2.8

43.7

-67.

343

.2-6

0.8

96/6

0498

/615

98/6

1515

1/67

7

42.4

49.4

53.2

67.4

14.9

-61.

030

.5-6

3.1

34.8

-66.

455

.8-7

5.9

Abb

revi

atio

ns: C

LTR,

cum

ulat

ive

lifet

ime

risk

; FD

Rs, fi

rst-d

egre

e re

lativ

es; n

, tot

al n

umbe

r of e

vent

s (i.

e., f

emal

e br

east

can

cer)

; N, t

otal

num

ber o

f wom

en a

t ri

sk in

the

anal

ysis

. * R

ight

-cen

sori

ng a

t dat

e of

firs

t eve

nt (w

hich

mig

ht b

e di

agno

sis

of b

reas

t can

cer,

ovar

ian

canc

er, r

isk-

redu

cing

mas

tect

omy,

risk

-red

ucin

g sa

lpin

go-o

opho

rect

omy,

or l

ast c

onta

ct o

r dea

th).

ǂ Inc

iden

t cas

e an

alys

is in

clud

es o

nly

year

s at

risk

and

eve

nts

afte

r the

dat

e of

the

first

pos

itive

DN

A-te

st in

th

e fa

mily

. # M

odel

ing

the

prob

abili

ty o

f bre

ast c

ance

r con

ditio

ned

on th

e ge

noty

pe a

nd p

heno

type

of t

he in

dex

case

s or

inde

x ca

rrie

rs, a

nd/o

r the

phe

noty

pe o

f re

lativ

es.

69

CH

AP

TE

R 1

CH

AP

TE

R 2

CH

AP

TE

R 3

CH

AP

TE

R 4

CH

AP

TE

R 5

CH

AP

TE

R 6

CH

AP

TE

R 7

CH

AP

TE

R 8

AP

PE

ND

ICE

S

Bias correction methods and breast cancer risks of BRCA1/2 mutation carriersComparison of each method's cumulative lifetime risks (CLTRs; 95% CI) by age 70 years with the reference estimate in (A) BRCA1 and (B) BRCA2 mutation carriers on the basis of the simulated

data.

Janet R. Vos et al. JCO 2015;33:2553-2562

©2015 by American Society of Clinical Oncology

Figure 2. Comparison of each method’s cumulative lifetime risks (CLTRs; 95% CI) by age 70 years with the reference estimate in (A) BRCA1 and (B) BRCA2 mutation carriers on the basis of the simulated data. The solid and dashed horizontal lines represent the CLTR and 95% CI of the reference for clinic-based cohorts, and the dotted line represents the reference CLTR for population-based cohorts.Abbreviations: Cond, conditioned on; Excl, excluding; FDR, first-degree relative; Incl, including; KM, Kaplan-Meier; MSA, modified segregation analysis.

●

●

●

●

●

●●

●

● ●

●

●

●

●

●

●

●

● ●

●

●

a) BRCA1 carriers

CLT

R (

%)

3040

5060

7080

popu

lation

clinic

incl in

dex

incl in

dex +

% FD

Rs

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

incl in

dex +

% FD

Rs

excl

index

+ % FD

Rs

incl in

dex

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l FDRs

index

case

s

index

carri

ers

index

case

s & D

NA date

Only ph

enoty

pe

Reference KM KM incident KM bootstrap Frailty MSA

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

● ●

●

●

b) BRCA2 carriers

CLT

R (

%)

3040

5060

7080

popu

lation

clinic

incl in

dex

incl in

dex +

% FD

Rs

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

incl in

dex +

% FD

Rs

excl

index

+ % FD

Rs

incl in

dex

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l FDRs

index

case

s

index

carri

ers

index

case

s & D

NA date

Only ph

enoty

pe


●

●

●

●

●

●●

●

● ●

●

●

●

●

●

●

●

● ●

●

●

a) BRCA1 carriersC

LTR

(%

)

3040

5060

7080

popu

lation

clinic

incl in

dex

incl in

dex +

% FD

Rs

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

incl in

dex +

% FD

Rs

excl

index

+ % FD

Rs

incl in

dex

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l FDRs

index

case

s

index

carri

ers

index

case

s & D

NA date

Only ph

enoty

pe


●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

● ●

●

●

b) BRCA2 carriers

CLT

R (

%)

3040

5060

7080

popu

lation

clinic

incl in

dex

incl in

dex +

% FD

Rs

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

excl

index

excl

index

+ inc

l % FD

Rs

excl

index

+ inc

l FDRs

incl in

dex +

% FD

Rs

excl

index

+ % FD

Rs

incl in

dex

incl in

dex +

FDRs

excl

index

excl

index

+ inc

l FDRs

index

case

s

index

carri

ers

index

case

s & D

NA date

Only ph

enoty

pe


70

CH

AP

TE

R 1

C

HA

PT

ER

2C

HA

PT

ER

3C

HA

PT

ER

4C

HA

PT

ER

5C

HA

PT

ER

6C

HA

PT

ER

7C

HA

PT

ER

8A

PP

EN

DIC

ES

Chapter 4

Tabl

e 4.

Com

pari

son

Betw

een

This

Stu

dy a

nd P

ublis

hed

Stud

ies o

f the

Cum

ulat

ive

Life

time

Risk

of B

reas

t Can

cer b

y A

ge 7

0 an

d 95

% C

Is

of R

ight

-Cen

sore

d A

naly

ses

by M

etho

d of

Ana

lysi

s BRC

A1

BRC

A2

Our

stu

dyPu

blis

hed

*O

ur s

tudy

Publ

ishe

d *

Ana

lyse

sN

CLT

R

(95%

CI)

NC

LTR

(9

5%C

I)St

udy

NC

LTR

(9

5%C

I)N

CLT

R

(95%

CI)

Stud

yK

apla

n-M

eier

ana

lysi

sIn

clud

ing

inde

x ca

ses

395

66 (5

9-74

)40 30

865

648

315

8026

4

64 (3

9-78

)71

(67-

82)

72 (6

6-78

)73

(68-

78)

76 (7

1-79

)85

(75-

97)

Beri

stai

n et

al 50

Van

der K

olk

et a

l 51

Vos

et a

l 52

Bros

e et

al 19

Vos

et a

l 52

Kro

iss

et a

l 28

232

73 (6

3-82

)50 43

339

417

822

0

69 (4

0-84

)72

(64-

78)

78 (6

9-85

)88

(82-

93)

88 (8

1-95

)

Beri

stai

n et

al 50

Vos

et a

l 52

Vos

et a

l 52

Van

der K

olk

et a

l 51

Tea

et a

l 53

Incl

udin

g in

dex

case

s an

d in

clud

ing

prop

ortio

n of

un

test

ed F

DRs

590

55 (4

9-60

)83

968

(65-

71)

Evan

s et

al 40

332

64 (5

6-71

)60

375

(72-

78)

Evan

s et

al 40

Excl

udin

g in

dex

case

s16

754

(45-

64)

2416

fam

7714

fam

462

467

214

1091

36 (5

-57)

± 52

(NA

)53

(35-

75)

± 57

(NA

)58

(51-

66)

58 (5

0-66

)60

(55-

66)

68 (6

2-73

)

Beri

stai

n et

al 50

Dor

um e

t al 6

Vog

l et a

l 37

Dor

um e

t al 6

Hei

mda

l et a

l 21

Vos

et a

l 52

Van

der K

olk

et a

l 51

Vos

et a

l 52

114

56 (4

3-69

)34 30

526

912

0

38 (1

2-56

)61

(50-

69)

64 (5

0-75

)78

(69-

88)

Beri

stai

n et

al 50

Vos

et a

l 52

Vos

et a

l 52

Van

der K

olk

et a

l 51

Mod

ified

seg

rega

tion

ana

lysi

sJo

int l

ikel

ihoo

d co

nditi

oned

on

gen

otyp

e of

inde

x ca

rrie

rs

and

all p

heno

type

s

112

fam

37 (1

9-50

)58

2 fa

m15

5 fa

m2

fam

25 fa

m

45 (3

6-52

)52

(26-

69)

64 (2

8-96

)72

(0-9

3)

Broh

et e

t al 54

Miln

e et

al 41

Teso

rier

o et

al 29

Ant

onio

u et

al 30

80 fa

m42

(15-

61)

176

fam

164

fam

27 fa

m6

fam

27 (1

4-38

)47

(29-

60)

75 (

0-97

)79

(48-

98)

Broh

et e

t al 54

Miln

e et

al 41

Ant

onio

u et

al 30

Te

sori

ero

et a

l 29

Join

t lik

elih

ood

cond

ition

ed

on g

enot

ype

of in

dex

case

s an

d al

l phe

noty

pes

112

fam

41 (2

6-53

)28

fam

48 (2

2-82

)Sc

ott e

t al 24

80 fa

m49

(31-

63)

23 fa

m74

(50-

93)

Scott

et a

l 24

Join

t lik

elih

ood

cond

ition

ed

on a

ll ph

enot

ypes

112

fam

53 (4

3-61

)1

fam

1 fa

m49

(13-

96)

39 (2

9-49

)So

uthe

y et

al 25

Vog

l et a

l 3780

fam

67 (5

6-76

)N

AN

AN

A

Abb

revi

atio

ns: C

LTR,

cum

ulat

ive

lifet

ime

risk

; 95%

CI,

confi

denc

e in

terv

al; f

am, n

umbe

r of f

amili

es; F

DRs

, firs

t-deg

ree

rela

tives

; N, n

umbe

r of s

ubje

cts,

NA

, not

app

licab

le. *

Es

timat

es fr

om s

tudi

es id

entifi

ed in

our

lite

ratu

re s

earc

h

71

CH

AP

TE

R 1

CH

AP

TE

R 2

CH

AP

TE

R 3

CH

AP

TE

R 4

CH

AP

TE

R 5

CH

AP

TE

R 6

CH

AP

TE

R 7

CH

AP

TE

R 8

AP

PE

ND

ICE

S


Comparison With Published Results from Retrospective Studies Using the Same MethodsThe risk difference between our CLTRs and estimates from the identified publications with the same method varied from 1% to 35% for BRCA1 mutation carriers and from 1% to 37% for BRCA2 mutation carriers (Table 4). Median risk variation in the CLTRs from all Kaplan-Meier analyses was 6% for BRCA1 and 8% for BRCA2 carriers. Median variation was 14% and 25%, respectively for the modified segregation analyses. For some methods, complete comparison was not possible because the published estimates were for the combined event of breast or ovarian cancer,6, 14, 21, 44 or the estimates were only for BRCA1 carriers.25, 37

Discussion

Published CLTRs of breast cancer in BRCA1/2 carriers vary widely, most likely because of a combination of differences in the study populations and applied methods. We aimed, first, to assess the effects of different methods of risk estimation and bias correction on the CLTRs and 95% CIs generated in a large, homogeneous, retrospective clinic-based cohort of BRCA1/2 carriers and, second, to assess the effect of differences in study populations. We applied 19 methods that resulted in CLTRs between 35% and 83% for BRCA1 carriers and between 41% and 86% for BRCA2 carriers; widths of the 95% CIs varied between 10% and 35% and between 11% and 46%, respectively. Bias correction by including index patients and a proportion of untested FDRs or by conditioning the likelihood function only on phenotypic data yielded rather accurate CLTRs for the context of our family cancer clinic. Comparison of our CLTRs with retrospective CLTRs estimated by applying the same method showed risk variations between 1% and 37%.

Without any bias correction, the CLTR in our study population was 67% (95% CI, 59% to 74%) for BRCA1 carriers and 73% (95% CI 63% to 82%) for BRCA2 carriers. Bias correction resulted in a stepwise decreasing effect in the CLTRs compared with the unadjusted CLTR. The only exception was the bootstrap approach for which including a proportion of FDRs resulted in higher risk estimates compared with no inclusion of FDRs. The posterior probability of assumed carriers among the untested FDRs was probably overestimated and led to overestimation of the number of carriers among affected FDRs or to underestimation of carriers among unaffected FDRs. In the simulation, however, this bootstrap approach with exclusion of index patients yielded, on average, the least biased CLTRs: +0% (SD, 5.7) for BRCA1 and −1.8% (SD, 8.7) for BRCA2. Because this uncertainty is high, this method needs further exploration.

Overall, low CLTRs were produced from the analyses that excluded all index patients but included all untested FDRs (for BRCA1, 35%; 95% CI, 31% to 40%; and for BRCA2, 41%; 95% CI, 34% to 48%) and by the modified segregation analysis in which the likelihood was conditioned on the genotype and phenotype of the index carriers and all other phenotypes in the family (for BRCA1, 36%; 95% CI, 19% to 50%; and BRCA2, 42%; 95% CI, 15% to 61%). Kaplan-Meier analyses excluding index

72

CH

AP

TE

R 1

C

HA

PT

ER

2C

HA

PT

ER

3C

HA

PT

ER

4C

HA

PT

ER

5C

HA

PT

ER

6C

HA

PT

ER

7C

HA

PT

ER

8A

PP

EN

DIC

ES

Chapter 4

patients and including FDRs and modified segregation analyses with conditioning on the basis of the genotype and phenotypes produced estimates approximating the risk for carriers in the general population. Here, no ascertainment bias is present. However, because not all of these carriers will enter the family cancer clinic, these estimates are substantially lower.

High CLTRs were produced by the incident case analyses that included only carriers. The result for BRCA1 was 83% (95% CI, 63% to 96%) and for BRCA2, 86% (95% CI, 57% 99%). This could have been a result of genetic testing bias among relatives and to having more follow-up information about affected relatives than about unaffected relatives. This explanation is likely given the simulation results, for which follow-up was complete and the CLTR was underestimated (≥ −9%). However, because the number at risk and the number of events were low, and because the CIs were large and overlapped with the reference CLTRs, results regarding this method still are uncertain.

The width of the 95% CI depends on two main factors: first, the number of women at risk and the number of events in the analysis and, second, whether familial clustering is taken into account. The Kaplan-Meier analyses excluding index patients, the analyses of incident cases, and the modified segregation analyses all led to relatively large SEs. Accounting for familial clustering in the analyses of individual subjects (ie, frailty model and Kaplan-Meier analysis with bootstrapping at the family level) had only a small positive effect on the 95% CIs: width of the 95% CIs, > 0% to 4.3% for BRCA1 and > 0.5% to 14.7% for BRCA2. This small effect was probably because not all the women in the family were FDRs. The greatest effect on the CI was seen in the bootstrap approach and was probably because the approach used to calculate the proportions for including FDRs and because no structure was imposed for familial clustering.

In general, risk estimates from prospective studies are considered most reliable. CLTRs most similar to those of the largest prospective clinic-based cohort (EMBRACE [Epidemiological Study of Familial Breast Cancer])45 were the Kaplan-Meier analyses with bias correction by either including index patients with a proportion of FDRs (risk difference compared with EMBRACE, −5.5% for BRCA1 and +6.0% for BRCA2) or by solely excluding index patients (risk difference, −5.7% for BRCA1 and +1.3% for BRCA2), and those of the modified segregation analyses with conditioning of the phenotypes restricted to those at the time of the index carrier’s DNA test (risk difference, −2.9% for BRCA1 and +3.4% for BRCA2). Although population differences may interfere with the comparison, the good performance of the first method was confirmed in the simulation.

Methods of previous retrospective cohort studies included in this study produced estimated CLTRs of 30% to 85% for BRCA1 carriers and 27% to 88% for BRCA2 carriers.6,19, 21, 24-26, 28-30, 40, 50-54 These risk ranges are broader than the range of estimates on the basis of our current dataset. However, for each method, we still observed considerable variation (as high as 37%) when we compared our estimates with previously published estimates. This demonstrates that there are other factors in addition to the risk- and bias-correction methods that affect the CLTR. These could include population and demographic factors (eg, birth cohorts, founder mutations, mutation type, family history) and/or other methodological issues. For example, these include the events chosen for right censoring, the decision to censor at the age of

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ovarian cancer or age of risk-reducing salpingo-oophorectomy, and how many times these events occur in the study population.6, 48 Differences in these choices are related to issues of competing risks and informative censoring, which will affect the occurrence of breast cancer. Some authors have therefore published risk estimates for developing breast or ovarian cancer, that is, with the cancer event defined as primary breast cancer or ovarian cancer instead of primary breast cancer only (ie, with or without censoring at ovarian cancer).6, 14, 21, 30, 44

Some researchers using the modified segregation analyses adopted a fixed population incidence24, 25, 30, 41 as input for the model, whereas others used a birth cohort–specific incidence,54 which might have an effect on the estimated CLTR. However, in an additional sensitivity analysis on the modified segregation model, we found that the model was, in fact, quite robust for possible mis-specification of the population incidence input; a 10% increase in the input incidence resulted in a 1% to 3% increase in the CLTR.

The strength of our study was that it demonstrated the effects of a large number of bias-correction methods in one large, well-defined BRCA cohort and a simulated reference cohort. Some of the methods have been applied in several cohorts at the same time,20, 37 but most authors present their CLTRs only with the inclusion and exclusion of the index patients.50-52 Women participating in a clinical cohort have already undergone genotype analysis, and data are gathered in the course of their standard care. This process makes this type of ascertainment the most straightforward and feasible manner for estimating breast cancer risk. However, this common design incorporates an ascertainment bias and a genetic testing bias, and these should both be avoided by properly correcting for them.

A limitation of our study is that the simulation was restricted to one scenario and tailored to the Dutch setting. Differences in genetic testing or ascertainment bias patterns (eg, as a result of different screening and referral guidelines) in other clinic-based cohorts, presumably from other countries, could affect performance of the methods. However, in simulations with a higher input value for the polygenic variance, ascertainment was more biased, but conclusions on the performance of the methods did not change (data not shown). Another limitation is that we applied only one approach for censoring events, whereas the estimation of the CLTRs could be affected by the chosen events.

In conclusion, when tested systematically in one retrospective clinical cohort of BRCA1/2 carriers, much of the variation in the CLTRs and CIs seems to be due to the method of bias correction used, whereas a smaller part is due to population differences. The modified segregation analysis is a complex method that concentrates on correcting all biases affecting the risk estimation.20 Our study shows that the modified segregation analysis, with ascertainment correction on the basis of the genotype of the indexes and all phenotypes in the family, yields estimates that most closely approach that of an unselected carrier in the general population. Most consistent estimates for carriers counseled in the clinic were estimated with the Kaplan-Meier method with bias corrected by including a proportion of untested FDRs. Compared with the other methods, this might be a simpler and more robust method to apply to clinical retrospective datasets. Future studies should focus on family-specific breast cancer

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risk estimates in BRCA carriers instead of population-averaged risks, and investigators should assess the effect of competing risks on the risk estimates and CIs.

AcknowledgmentWe thank A.C. Antoniou, PhD, for advice on the modified segregation analysis and Jackie Senior for editing the manuscript.

FundingSupported in part by a grant from the Dutch Cancer Society (to J.R.V.)

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Appendix 1: Simulation Study

Structure of FamiliesBased on our clinical database, a general population was generated consisting of 100,000 families. All were three-generation families with a fixed pedigree structure similar to the current average Dutch families (Data Supplement; Jonker et al: J Med Genet 40:e25, 2003). Age at last contact in the first generation was generated following a normal distribution N (85,3). In the second and third generation, the age at contact was based on the mean age of the parents minus an age difference between the generations. This age difference was N (25,2) and N (26,2), respectively.

Genes and Polygenic FactorsBRCA1 and BRCA2 gene mutations were generated using gene dropping, with mutation frequencies of 0.003 and 0.001, respectively, and following a Mendelian transmission with an autosomal-dominant inheritance pattern (Jonker et al: J Med Genet 40:e25, 2003). Individuals could not have both mutations, mutation carriers were always heterozygote for the mutation, and in-laws were considered always negative for the mutation.

A polygenic risk factor, following a normal distribution, was generated to represent other familial risk factors affecting the individuals’ cancer risk (Pankratz et al: Genet Epidemiol 28:97-109, 2005).38 In the first generation, the mean of the distribution was zero, in the second and third generations, mean of the distribution was equal to mean of the parents’ polygenic component. In the first generation, the variance of the distribution was equal to input value 1.5, and in the second and third generation, the variation was equal to the half of the input value (Pankratz et al: Genet Epidemiol 28:97-109, 2005).38

Cancer and Censoring EventsThe age at cancer (≥ 20 years) and death were generated following a Weibull distribution on the basis of Dutch population data, and for male carriers, a relative risk was used to generated the cancer incidence (Table 1; Thompson and Easton: Am J Hum Genet 68:410-419, 2001; Liede et al: J Clin Oncol 22:735-742, 2004; Netherlands Cancer Registry:http://www.cijfersoverkanker.nl/selecties/dataset_1/img54b79b31474b4; Statistics Netherlands: http://statline.cbs.nl/Statweb/publication/?DM=SLNL&PA=7052_95&D1=0&D2=1-2&D3=a&D4=56-61&VW=T).

An age-related probability for undergoing risk-reducing mastectomy or risk-reducing mastectomy salpingo-oophorectomy was applied using age-dependent probabilities on the basis of our clinical database. Female carriers ≥ 25 years old without breast cancer and ≥ 30 years old without ovarian cancer were eligible for risk-reducing mastectomy and risk-reducing mastectomy salpingo-oophorectomy, respectively.

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Genetic Testing and the Index PersonWhen more individuals in the family fulfilled the Dutch referral criteria for genetic counseling and testing, the affected person with the youngest age at diagnosis was tested for the mutation (Mammacarcinoma, http://www.oncoline.nl/breastcancer). Then, when more individuals in the family fulfilled the referral criteria and only unaffected individuals were still alive at the time of referral, the individual most closely related to the cancer patient was tested.

When the index patient was positive for a BRCA1 or BRCA2 mutation, genetic testing was offered to the family. If the index patient tested negative for the gene mutation, the family was not offered further testing.

Affected family members were tested irrespective of any cascade protocol, and their probability of being tested was greater than their unaffected relatives. Unaffected family members were tested following a cascade protocol. The genetic testing probability was based on the clinical database, and was gender, phenotype, and age dependent.

Risk Analyses in a Clinic-Based CohortDutch referral criteria for genetic counseling and testing were used to mimic the ascertainment bias seen in the family cancer clinic cohorts. Subsequently, the genetic testing bias was mimicked by making the probability for genetic testing in all relatives of the index carrier gender, age, and phenotype dependent (Oosterwijk et al: Maturitas 78:252-257, 2014).

In total, 50 datasets were generated with the same input values but with a different random seed. All methods were applied to each dataset with these ascertainment and genetic testing biases (Table 2). Because the aim of the study was to assess the risk estimates for BRCA1/2 carriers seen in the family cancer clinic, we obtained the reference risk by Kaplan-Meier estimation using the same cohort with complete information on all genotypes. Thus, the reference estimate for the clinic would be a cohort affected by the same ascertainment bias but not by the genetic testing bias, whereas the general population cohort would not be affected by either.

Table A1. Weibull Scale and Shape Input Parameters and Relative RisksFemales Males

Scale Shape Scale ShapeBreast cancer Non-carriers BRCA1 carriers BRCA2 carriers

151.2872.1970.59

3.292.463.12

263.16 5.9RR = 3RR = 70

Ovarian cancer Non-carriers BRCA1 carriers BRCA2 carriers

242.7284.2291.86

4.063.584.52

NA

Death 113.64 7.5 113.64 8.3Abbreviations: NA, not applicable; RR, relative risk

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Tabl

e A

2. E

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.

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Supp

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s an

d co

nsec

utiv

e br

east

an

d ov

aria

n ca

ncer

se

ries

, Nor

way

, fa

mili

es h

arbo

ring

fo

unde

r mut

atio

n 81

6del

GT,

113

5ins

A,

1675

delA

or

3347

delA

G

Kap

lan-

Mei

er

anal

ysis

Incl

. all

fem

ale

mut

atio

n ca

rrie

rs (d

emon

stra

ted,

affe

cted

or

obl

igat

e), e

xclu

ding

inde

x ca

ses

RRM

, OC

, dea

th

or la

st c

onta

ct58

(51-

66)

NA

NA

NA

Incl

. all

fem

ale

mut

atio

n ca

rrie

rs (d

emon

stra

ted,

affe

cted

or

obl

igat

e), e

xclu

ding

inde

x ca

ses

Dea

th, l

ast

cont

act o

r 110

yrs

N

AN

A84

(SE:

2)

NA

Incl

. all

fem

ale

mut

atio

n ca

rrie

rs (d

emon

stra

ted,

affe

cted

or

obl

igat

e) a

nd th

eir u

ntes

ted

unaff

ecte

d FD

Rs, e

xclu

ding

in

dex

case

s

NA

NA

62 (S

E: 2

)N

A

Incl

. all

fem

ale

mut

atio

n ca

rrie

rs (d

emon

stra

ted,

affe

cted

or

obl

igat

e) a

nd a

pro

port

ion

of

thei

r unt

este

d un

affec

ted

FDRs

, ex

clud

ing

inde

x ca

ses

NA

NA

70 (S

E: -

)N

A

Scott

et a

l 2420

03H

igh-

risk

fam

ilies

an

d kn

own

BRCA

fa

mili

es, A

ustr

alia

(k

Con

Fab)

Mod

ified

se

greg

atio

n an

alys

is(M

LE: j

oint

lik

elih

ood)

Max

imiz

ed th

e co

nditi

onal

lik

elih

ood

of a

ll ph

enot

ypic

an

d ge

noty

pic

info

rmat

ion

in th

e fa

mily

giv

en th

e br

east

ca

ncer

sta

tus

and

age

at

diag

nosi

s or

els

e ag

e in

terv

iew

of

all

fam

ily m

embe

rs, a

nd

gene

tic in

form

atio

n of

the

inde

x ca

se

RRM

, RRS

O,

deat

h, la

st

cont

act o

r 85

yrs

48 (2

2-82

)74

(50-

93)

NA

NA

Sout

hey

et a

l 2520

03Fa

mily

can

cer

clin

ic s

erie

s, B

RCA

1 fa

mili

es w

ith

puta

tive

splic

e si

te

mut

atio

n IV

S6-

2del

A, A

ustr

alia

(k

Con

Fab)

Mod

ified

se

greg

atio

n an

alys

is(M

LE: j

oint

lik

elih

ood)

Max

imiz

ed th

e co

nditi

onal

lik

elih

ood

of a

ll ph

enot

ypic

an

d ge

noty

pic

info

rmat

ion

in th

e fa

mily

giv

en th

e br

east

ca

ncer

sta

tus

of a

ll fa

mily

m

embe

rs

Dea

th o

r las

t co

ntac

t49

(13-

96)

NA

NA

NA

80

CH

AP

TE

R 1

C

HA

PT

ER

2C

HA

PT

ER

3C

HA

PT

ER

4C

HA

PT

ER

5C

HA

PT

ER

6C

HA

PT

ER

7C

HA

PT

ER

8A

PP

EN

DIC

ES

Chapter 4

Stud

yYe

arA

scer

tain

men

tA

naly

sis

Bias

cor

rect

ion

met

hod

Cen

sori

ng,

at a

ge o

f

BC b

y ag

e 70

CLT

R (9

5% C

I)BC

/OC

by

age

70C

LTR

(95%

CI)

BRC

A1

BRC

A2

BRC

A1

BRC

A2

Mar

roni

et a

l 2620

04Fa

mily

can

cer

clin

ic s

erie

s in

cl.

high

-ris

k fa

mili

es

both

pos

itive

an

d ne

gativ

e fo

r BR

CA1/

2 m

utat

ions

, Ita

ly

MC

MC

Re

tros

pect

ive

likel

ihoo

d co

nditi

oned

on

all p

heno

typi

c da

ta

-39

(27-

52)

44 (2

9-58

)N

AN

A

Kro

iss

et a

l 2820

05C

onse

cutiv

e co

hort

of

fem

ale

BRCA

1/2

mut

atio

n ca

rrie

rs

coun

sele

d at

the

fam

ily c

ance

r clin

ic,

Aus

tria

Kap

lan-

Mei

er

anal

ysis

-RR

M, R

RSO

, de

ath

or la

st

cont

act

85 (7

5-97

)N

AN

AN

A

Teso

rier

o et

al 29

2005

Hig

h-ri

sk fa

mili

es

and

know

n BR

CA

fam

ilies

, BRC

A1/

2 fa

mili

es w

ith

splic

e si

te v

aria

nts,

A

ustr

alia

and

New

Ze

alan

d (k

Con

Fab)

Mod

ified

se

greg

atio

n an

alys

is

Join

t lik

elih

ood

cond

ition

ed

on a

ll ph

enot

ypic

dat

a in

the

fam

ily a

nd th

e ge

noty

pic

info

rmat

ion

of th

e in

dex

carr

ier

RRM

, RRS

O,

deat

h, la

st

cont

act o

r 85

yrs

64 (2

8-96

)79

(48-

98)

NA

NA

Ant

onio

u et

al 30

2006

Hig

h-ri

sk F

renc

h-C

anad

ian

brea

st

and/

or o

vari

an

canc

er fa

mili

es

Mod

ified

se

greg

atio

n an

alys

is

Join

t lik

elih

ood

cond

ition

ed

on a

ll ph

enot

ypic

dat

a in

the

fam

ily a

nd th

e ge

noty

pic

info

rmat

ion

of th

e in

dex

carr

ier

OC

, dea

th, l

ast

cont

act o

r 70

yrs

72 (0

-93)

75 (0

-97)

NA

NA

Dea

th, l

ast

cont

act o

r 70

yrs

NA

NA

83 (3

4-96

)89

(34-

98)

Che

n et

al 31

2006

Popu

latio

n-ba

sed

and

clin

ic-b

ased

hi

gh-r

isk

fam

ilies

MC

MC

Men

delia

n re

tros

pect

ive

likel

ihoo

d co

nditi

oned

on

all

phen

otyp

ic d

ata

-46

(39-

54)

43 (3

6-51

)N

A

Vog

l et a

l 3720

07H

igh-

risk

fam

ily

BRCA

1 m

utat

ion

4056

C>T

, USA

Kap

lan-

Mei

er

anal

ysis

In

cl. a

ll pr

oven

fem

ale

mut

atio

n ca

rrie

rs, e

xclu

ding

as

cert

ainm

ent c

ases

Dea

th o

r las

t co

ntac

t(R

RM N

=0)

53 (3

5-75

)N

AN

AN

A

Segr

egat

ion

anal

ysis

Retr

ospe

ctiv

e lik

elih

ood

cond

ition

ed o

n al

l phe

noty

pic

data

39 (2

9-49

)N

AN

AN

A

Segr

egat

ion

anal

ysis

C

ondi

tiona

l lik

elih

ood

(MLO

D)

on a

ll aff

ecte

d in

divi

dual

s30

(17-

47)

NA

NA

NA

81

CH

AP

TE

R 1

CH

AP

TE

R 2

CH

AP

TE

R 3

CH

AP

TE

R 4

CH

AP

TE

R 5

CH

AP

TE

R 6

CH

AP

TE

R 7

CH

AP

TE

R 8

AP

PE

ND

ICE

S


Stud

yYe

arA

scer

tain

men

tA

naly

sis

Bias

cor

rect

ion

met

hod

Cen

sori

ng,

at a

ge o

f

BC b

y ag

e 70

CLT

R (9

5% C

I)BC

/OC

by

age

70C

LTR

(95%

CI)

BRC

A1

BRC

A2

BRC

A1

BRC

A2

Evan

s et

al 40

2008

Fam

ily c

ance

r cl

inic

s, E

ngla

ndK

apla

n-M

eier

an

alys

is

Incl

. pro

ven

and

oblig

ate

fem

ale

mut

atio

n ca

rrie

rs, a

nd a

pr

opor

tion

of F

DRs

RRM

, OC

, RRS

O,

deat

h or

last

co

ntac

t

68 (6

5-71

)75

(72-

78)

NA

NA

Incl

. una

ffect

ed c

arri

ers

and

FDRs

at t

ime

of fa

mily

as

cert

ainm

ent

30-7

9yr:

annu

al

inci

denc

e of

2%

NA

NA

Miln

e et

al 41

2008

Fam

ily c

ance

r clin

ic,

Spai

nM

odifi

ed

segr

egat

ion

anal

ysis

Join

t lik

elih

ood

cond

ition

ed

on a

ll ph

enot

ypic

dat

a in

the

fam

ily a

nd th

e ge

noty

pic

info

rmat

ion

of th

e in

dex

carr

ier

RRM

, oth

er

canc

ers,

RRS

O,

deat

h, la

st

cont

act o

r age

70

52 (2

6-69

)47

(29-

60)

NA

NA

Car

deno

sa e

t al 44

2010

Fam

ily c

ance

r clin

ic,

Spai

nK

apla

n-M

eier

an

alys

is

-La

st c

onta

ctN

AN

A78

(71-

85)

Beri

stai

n et

al 50

2010

Fam

ily c

ance

r clin

ic,

Spai

nK

apla

n-M

eier

an

alys

is

Incl

. ind

ex c

ases

O

C, R

RSO

, dea

th

or la

st c

onta

ct(R

RM N

=0)

64 (3

9-78

)69

(40-

84)

NA

NA

Excl

udin

g in

dex

case

s36

(5-5

7)38

(12-

56)

NA

Van

der K

olk

et a

l 5120

10Fa

mily

can

cer

clin

ic, N

orth

ern-

N

ethe

rlan

ds

Kap

lan-

Mei

er

anal

ysis

Incl

. ind

ex c

ases

RRM

, RRS

O<5

0 yr

s, d

eath

or l

ast

cont

act

71 (6

7-82

)88

(82-

93)

NA

NA

Excl

udin

g in

dex

case

s60

(55-

66)

78 (6

9-88

)N

AN

A

Tea

et a

l5320

14Fa

mily

Can

cer

Clin

ic, A

ustr

iaK

apla

n-M

eier

an

alys

isIn

cl. i

ndex

cas

es, e

xclu

ding

ob

ligat

e ca

rrie

rsRR

M,R

RSO

, de

ath

or la

st

cont

act

NA

88 (8

1-95

)N

AN

A

Broh

et e

t al 54

2014

Fam

ily c

ance

r cl

inic

ser

ies,

the

Net

herl

ands

Mod

ified

se

greg

atio

n an

alys

is

Join

t lik

elih

ood

cond

ition

ed

on a

ll ph

enot

ypic

dat

a in

the

fam

ily a

nd th

e ge

noty

pic

info

rmat

ion

of th

e in

dex

carr

ier

RRM

, OC

, RR

SO, d

eath

, la

st c

onta

ct, l

ast

DN

A-te

st fa

mily

m

embe

r or 7

0 yrs

45 (3

6-52

)27

(14-

38)

NA

NA

Vos

et a

l 5220

14Fa

mily

can

cer

clin

ics,

the

Net

herl

ands

Kap

lan-

Mei

er

anal

ysis

Incl

. ind

ex c

ases

RRM

, OC

, RRS

O,

deat

h or

last

co

ntac

t

72 (6

6-78

)76

(71-

79)

78 (6

9-85

)72

(64-

78)

NA

NA

Excl

udin

g in

dex

case

s58

(50-

66)

68 (6

2-73

)64

(50-

75)

61 (5

0-69

)N

AN

A

Abb

revi

atio

ns:

BC,

brea

st c

ance

r; FD

Rs,

first

-deg

ree

rela

tives

; M

CM

C,

Mar

kov

Cha

in M

onte

Car

lo;

MLE

, m

axim

um l

ikel

ihoo

d es

timat

e; M

LOD

, m

axim

um

loga

rith

m o

f the

odd

s; O

C, o

vari

an c

ance

r; RR

M, r

isk-

redu

cing

mas

tect

omy;

RRS

O, r

isk-

redu

cing

sal

ping

o-oo

phor

ecto

my;

NA

, not

app

licab

le.

82

CH

AP

TE

R 1

C

HA

PT

ER

2C

HA

PT

ER

3C

HA

PT

ER

4C

HA

PT

ER

5C

HA

PT

ER

6C

HA

PT

ER

7C

HA

PT

ER

8A

PP

EN

DIC

ES

Chapter 4

Scre

enin

g

In

clud

ed

Id

entif

icat

ion

Additional records included

Records identified through reference lists

N = 3

Records title/ abstract screening

Studies assessing the breast cancer risk of carriers of a know pathogenic BRCA1/2 mutation

N = 1974

Records full text screening

Studies including BRCA mutation carriers

N =201

Records excluded

N = 1773

Records excluded

Studies presenting only hazard ratios, relative risks

or odds ratios Studies using methods not applicable to a clinic-based

cohort

N = 184

Studies included

N = 20

Records identified through database searching

Pubmed (N = 1328) Embase (N = 1199)

Web of Science (N = 424)

N = 2951

Duplicate records removed

N = 155

Supplementary Figure 1. Flow diagram of the literature search

Supplementary Figure 2. Simulated pedigree structure

83

CH

AP

TE

R 1

CH

AP

TE

R 2

CH

AP

TE

R 3

CH

AP

TE

R 4

CH

AP

TE

R 5

CH

AP

TE

R 6

CH

AP

TE

R 7

CH

AP

TE

R 8

AP

PE

ND

ICE

S


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R 1

C

HA

PT

ER

2C

HA

PT

ER

3C

HA

PT

ER

4C

HA

PT

ER

5C

HA

PT

ER

6C

HA

PT

ER

7C

HA

PT

ER

8A

PP

EN

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Chapter 4

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34. Tryggvadottir L, Sigvaldason H, Olafsdottir GH, et al: Population-based study of changing breast cancer risk in Icelandic BRCA2 mutation carriers, 1920-2000. J Natl Cancer Inst 98:116-122, 2006

35. Chen S, Parmigiani G: Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 25: 1329-1333, 2007

36. Fu R, Harris EL, Helfand M, et al: Estimating risk of breast cancer in carriers of BRCA1 and BRCA2 mutations: a meta-analytic approach. Stat Med 26:1775-1787, 2007

37. Vogl FD, Badzioch MD, Steele L, et al: Risks of cancer due to a single BRCA1 mutation in an extended Utah kindred. Fam Cancer 6:63-71, 2007

38. Antoniou AC, Cunningham AP, Peto J, et al: The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions. Br J Cancer 98:1457-1466, 2008

39. Begg CB, Haile RW, Borg A, et al: Variation of breast cancer risk among BRCA1/2 carriers. JAMA 299:194-201, 2008

40. Evans DG, Shenton A, Woodward E, et al: Penetrance estimates for BRCA1 and BRCA2 based on genetic testing in a clinical cancer genetics service setting: risks of breast/ovarian cancer quoted should reflect the cancer burden in the family. BMC Cancer 8:155, 2008

41. Milne RL, Osorio A, Cajal TRY, et al: The average cumulative risks of breast and ovarian cancer for carriers of mutations in BRCA1 and BRCA2 attending genetic counseling units in Spain. Clin Cancer Res 14:2861-2869, 2008

42. Chen L, Hsu L, Malone K: A frailty-modelbased approach to estimating the a ge-dependent penetrance function of candidate genes using population-based case-control study designs: an application to data on the BRCA1 gene. Biometrics 65:1105-1114, 2009

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43. Hashemian AH, Hajizadeh E, Kazemnejad A, et al: Penetrance of BRCA1/BRCA2 specific gene mutations in Iranian women with breast cancer. Saudi Med J 30:41-44, 2009

44. Cardenosa EE, Bolufer GP, de Juan Jimenez I, et al: Relationship of BRCA1 and BRCA2 mutations with cancer burden in the family and tumor incidence. Fam Cancer 9:291-295, 2010

45. Mavaddat N, Peock S, Frost D, et al: Cancer risks for BRCA1 and BRCA2 mutation carriers: results from prospective analysis of EMBRACE. J Natl Cancer Inst 105:812-822, 2013

46. Evans DG, Harkness E, Lalloo F, et al: Longterm prospective clinical follow-up after BRCA1/2 presymptomatic testing: BRCA2 risks higher than in adjusted retrospective studies. J Med Genet 51: 573-580, 2014

47. De Bock GH, Mourits MJ, Oosterwijk JC: One risk fits all? J Clin Oncol 25:3383-3384, 2007

48. Kramer JL, Velazquez IA, Chen BE, et al: Prophylactic oophorectomy reduces breast cancer penetrance during prospective, long-term follow-up of BRCA1 mutation carriers. J Clin Oncol 23:86298635, 2005

49. Gadzicki D, Evans DG, Harris H, et al: Genetic testing for familial/hereditary breast cancercomparison of guidelines and recommendations from the UK, France, the Netherlands and Germany. J Community Genet 2:53-69, 2011

50. Beristain E, Ibanez B, Vergara I, et al: Breast and ovarian cancer risk evaluation in families with a disease-causing mutation in BRCA1/2. J Community Genet 1:91-99, 2010

51. Van der Kolk DM, de Bock GH, Leegte BK, et al: Penetrance of breast cancer, ovarian cancer and contralateral breast cancer in BRCA1 and BRCA2 families: high cancer incidence at older age. Breast Cancer Res Treat 124:643-651, 2010

52. Vos JR, Teixeira N, Van der Kolk DM, et al: Variation in mutation spectrum partly explains regional differences in the breast cancer risk of female BRCA mutation carriers in the Netherlands. Cancer Epidemiol Biomarkers Prev 23:2482-2491, 2014

53. Tea MK, Kroiss R, Muhr D, et al: Central European BRCA2 mutation carriers: Birth cohort status correlates with onset of breast cancer. Maturitas 77:68-72, 2014

54. Brohet RM, Velthuizen ME, Hogervorst FB, et al: Breast and ovarian cancer risks in a large series of clinically ascertained families with a high proportion of BRCA1 and BRCA2 Dutch founder mutations. J Med Genet 51:98-107, 2014

55. Chatterjee N, Wacholder S: A marginal likelihood approach for estimating penetrance from kincohort designs. Biometrics 57:245-252, 2001

56. Hsu L, Chen L, Gorfine M, et al: Semiparametric estimation of marginal hazard function from casecontrol family studies. Biometrics 60:936-944, 2004

57. Rondeau V, Mazroui Y, Gonzalez JR: Frailtypack: An R package for the analysis of correlated survival data with frailty models using penalized likelihood estimation or parametric estimation. J Stat Softw 47:1-28, 2012

58. R Foundation for Statistical Computing: R: A language and environment for statistical computing. 2013. http://www.R-project.org

59. Lange K, Papp JC, Sinsheimer JS, et al: Mendel: The Swiss Army knife of genetic analysis programs. Bioinformatics 29:1568-1570, 2013

60. Lange K, Weeks D, Boehnke M: Programs for pedigree analysis: MENDEL, FISHER, and dGENE. Genet Epidemiol 5:471-472, 1988

Chapter 5Inverse birth cohort eff ects in ovarian cancer:

Increasing risk in BRCA1/2 mutation carriers and decreasing risk in the general population

Janet R. Vos Marian J.E. Mourits

Natalia Teixeira Liesbeth Jansen

Jan C. Oosterwijk Geertruida H. de Bock

Gyneacological Oncology 2015, in press

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Abstract

ObjectiveBRCA1/2 carriers are at increased risk of ovarian cancer, and some reports suggest an increasing risk in more recent birth cohorts. In contrast, decreasing incidences have been observed in the general population. The aim was to assess the birth cohort effect on ovarian cancer risk in BRCA1/2 carriers relative to their background general population.

MethodsData on ovarian cancer incidence was collected for a cohort of 1,050 BRCA1/2 mutation carriers ascertained by our regional clinic and retrieved from the general Dutch population cancer registry. Birth cohorts were categorized as pre-1935, 1935-1953, post-1953. Birth cohort effects on the ovarian cancer risk were estimated using hazard ratios (HRs) in BRCA1/2 carriers and Poisson rate ratios in the general population. Standardized incidence ratios (SIRs) were calculated to compare populations. HRs were adjusted for mutation position and family history.

ResultsCompared to the pre-1935 cohort, BRCA1 carriers in the 1935-1953 and post-1953 cohorts had an increased ovarian cancer risk of HRadjusted 1.54 (95%CI 1.11-2.14) and 2.40 (95%CI 1.56-3.69), respectively. BRCA2 carriers in the 1935-1953 cohort had an HRadjusted of 3.01 (95%CI 1.47-6.13). The SIRs for the 1935-1953 and post-1953 cohorts were 1.7 and 2.7, respectively, for the BRCA1 carriers and 1.6 times and 2.4 times, respectively, for BRCA2 carriers.

ConclusionsMutation carriers, particularly BRCA1 carriers, born in the most recent cohorts, have the highest additional ovarian cancer risk as compared to the general population.

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Inverse trends in the ovarian cancer risks of BRCA1/2 carriers and the general population

Introduction

Women in the general population have a 1.1-1.7% cumulative lifetime risk (CLTR) of developing ovarian cancer (OC).1-3 About 10-15% of epithelial OC cases are associated with a mutation in the BRCA1 or BRCA2 gene.4,5 Two large meta-analyses have estimated the OC risk by age 70 to be 39% (95%CI 18–54%)6 and 40% (95%CI 35- 46%)7

for BRCA1 mutation carriers and 11% (95%CI 2.4–19%)6 and 18% (95%CI 13- 23%)7 for BRCA2 mutation carriers. However, higher risk estimates were derived in the Family Cancer Clinic in our region which covers the Northern-Netherlands: 59% (95%CI 54-64%) for BRCA1 carriers and 35% (95%CI 25-44%) for BRCA2 mutation carriers.8 For BRCA1 carriers this higher risk (59%, 95%CI 43-76%) was also observed in a prospective analysis in an UK clinic-based cohort, but estimated figures were lower for BRCA2 carriers (17%, 95%CI 8-34%).9

In BRCA1 carriers, an increased risk of breast cancer (BC) is observed in more recent birth cohorts compared to older birth cohorts.2,10,11 However, studies on birth-cohort effects on OC risk have produced contradictory results. For BRCA1 carriers, all studies show an increasing trend in more recent birth cohorts, but the effect size and significance differ. No significant birth cohort effect has yet been reported for BRCA2 carriers.10-13 Recent reports on the general population in several countries actually present a reverse trend of gradually decreasing OC risk: a lower risk in younger birth cohorts compared to older birth cohorts.1,14

We wondered whether these inverse OC risk trends could be confirmed in our population, and what the relative risk of developing OC was for BRCA1/2 mutation carriers compared to the general population when these inverse cohort trends were taken into account. Our aim was to assess the effect of birth cohorts on the OC risk in BRCA1/2 mutation carriers, as well as in their background general population, and to assess the birth-cohort-specific added risk for OC in mutation carriers.

Methods

Mutation carriersThis study included female carriers of a pathogenic BRCA1 or BRCA2 mutation seen at the Family Cancer Clinic of the University Medical Centre Groningen.15,16 Women could be included in the cohort if they were born in 1910 or later.

Information was collected up to September 2011, with follow-up information for 1,050 carriers (49,742 person years) from 364 BRCA1/2 families.8,17,18 Data were collected about mutation carrier ship status and type and location of the mutation and the following relevant dates: birth, death, last moment of contact, BC, OC, risk-reducing mastectomy and risk-reducing salpingo-oophorectomy (RRSO). Data were retrieved from patients’ medical records and entered into a separate, anonymous, password-protected database. According to Dutch law, this meant no further approval from our Medical Ethical Committee was needed.

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General populationFor the general population of the Netherlands, information was collected on the age-related OC incidence in the diagnosis periods 1960-1962, 1978-1982, 1983-1987, 1986-1988, and 1988-1992, which were available from the database of the International Agency for Research on Cancer, and in the diagnosis years 1989-2014, which were available from the Dutch Cancer Registry, the Netherlands.19,20

Outcome and independent variablesBirth cohorts were defined similarly for BRCA1/2 carriers and the general population. To define birth cohorts with sufficient group size and to maximize the follow-up time in each of the birth cohorts, three birth cohorts were defined: pre-1935, 1935-1953, and post-1953. Using this definition, CLTRs could be assessed up to age 55 for all birth cohorts, because all the cohorts included at least some women with follow-up to age 55. In addition, for the two oldest birth cohorts, the CLTRs up to age 70 could be assessed.

For BRCA1/2 carriers, mutation location definition was based on the OC cluster region (OCCR): 5 prime to OCCR, within OCCR, and OCCR to 3 prime.17,21,22 Family history of BC and OC was defined by two variables: (1) having any first- and/or second-degree relative with BC or not and (2) having any first- and/or second-degree relative with OC or not.

For the general population, age-specific incidences for each birth year were calculated using data on the incidence per 5-year age-group per year of diagnosis. By combining all data, an average incidence per age per birth year could be derived. For example, the incidence in the age group 50-54 for 2010 provided data for women born between 1956 and 1960, and similarly, for 2011, this age category consisted of women born between 1957 and 1961.

Statistical analysisFor mutation carriers, the effect of birth cohort on the CLTR of OC was assessed using Cox regression survival analysis and expressed as hazard ratios (HRs). The effect of birth cohort was adjusted for mutation location and family history. In the Cox models, robust standard errors were calculated to take the familial clustering into account. The proportionality of the HRs was examined using log-minus-log plots and Schoenfeld residuals. The CLTRs per birth cohort were calculated using Kaplan-Meier survival analyses. In the survival analyses, right-censoring was applied at the woman’s age at RRSO, or the last moment of follow-up, or age at death, or at age 70. To correct for ascertainment and genetic-testing bias, all these analyses were also performed with the inclusion of a proportion of untested FDRs (N=690; 35,553 person years) of mutation carriers, because these FDRs have no genetic-testing bias among them. We did not correct for bias by excluding the index cases, because this would have resulted in low numbers and because the vast majority of index cases were born in the 1935-1953 birth cohort. The proportion of FDRs was calculated based on the ratio of positive DNA tests of all presymptomatically tested women per age group and incident cancer status (i.e. cancer diagnosis after DNA testing in order to avoid overestimating the proportion due to genetic-testing bias). The calculated proportion reflects the proportion of assumed mutation carriers among the untested FDRs.23

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For the general population, CLTRs and the effect of birth cohort on the CLTRs (age-adjusted Poisson rate ratios (PRRs)) were assessed by applying Poisson regression analyses.

For a direct comparison between the birth-cohort-specific incidence in mutation carriers and the general population, standardized incidence ratios (SIRs) were calculated and corrected for bias by including the proportion of assumed mutation carriers among the untested FDRs.

The analyses were performed using IBM SPSS statistics version 22 and R, and statistical significance was defined as p < 0.05.24 Continuous data is presented with a median and interquartile range (IQR), i.e. 25th percentile – 75th percentile.

Results

Mutation carriersIn total, we included 656 BRCA1 carriers and 445 untested FDRs (consisting of both carriers and non-carriers) from 220 BRCA1 families, and 394 BRCA2 carriers and 245 untested FDRs from 144 BRCA2 families were included. BRCA1 carriers were followed until a median age of 48.2 years (IQR 38.4-57.3) and BRCA2 carriers until 49.5 years (IQR 40.1-59.5). In total, 136 (21%) BRCA1 and 43 (11%) BRCA2 carriers developed OC, at a median age of 49.4 years (IQR 43.9-56.1) and 57.8 years (IQR 52.2-62.7), respectively. RRSO was performed in 214 (33%) of the BRCA1 and 126 (32%) of the BRCA2 carriers at a median age of 43.9 years (IQR 39.9-50.9) and 47.8 years (IQR 39.1-53.3), respectively.

Overall, the median year of birth was 1957 (IQR 1945-1969) for BRCA1 and 1957 (IQR 1946-1968) for BRCA2 carriers. Among the untested FDRs this was 1944 (IQR 1926-1963) and 1942 (IQR 1926-1962), respectively.

Ovarian cancer risk in mutation carriers by birth cohortFor BRCA1 carriers, the CLTR by age 55 was 18.9% (95%CI 9.8-27.2%) in the pre-1935 birth cohort, 28.6% (95%CI 21.1-35.4%) in the 1935-1953 birth cohort, and 43.4% (95%CI 26.5-56.3%) in the post-1953 birth cohort (Table 1). For BRCA2 carriers, the CLTR by age 55 was 6.8% (95%CI 0.0-13.9%) in the pre-1935 birth cohort, 7.8% (95%CI 2.4-12.8%) in the 1935-1953 birth cohort, and 25.2% (95%CI 0.0-45.5%) in the post-1953 birth cohort. CLTRs at other ages, and CLTRs for carriers including the assumed carriers among the FDRs, are presented in Table 1. The CLTRs and number of women included in the analyses are presented separately for mutation carriers and assumed carriers in Fig 1.

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Tabl

e 1.

Bir

th-c

ohor

t-spe

cific

cru

de c

umul

ativ

e lif

etim

e ri

sks

(CLT

Rs) b

y ag

es 5

5 an

d 70

yea

rs in

the

BRCA

1/2

mut

atio

n ca

rrie

rs a

nd in

th

e ge

nera

l pop

ulat

ion

Birt

h co

hort

BRC

A1

BRC

A2

Gen

eral

po

pula

tion

Car

rier

sC

arri

ers

& F

DR

sC

arri

ers

Car

rier

s &

FD

Rs

Age

55

N (e

vent

s)a

CLT

R (9

5% C

I)N

(eve

nts)

aC

LTR

(95%

CI)

N (e

vent

s)a

CLT

R (9

5% C

I)N

(eve

nts)

aC

LTR

(95%

CI)

CLT

R (9

5% C

I)

pre-

1935

58 (1

5)18

.9

(9.8

-27.

2)13

3 (1

5)20

.9 (1

4.7-

26.6

)37

(3)

6.8

(0

-13.

9)86

(6)

6.0

(1.2

-10.

5)0.

38 (0

.24-

0.60

)

1935

-195

394

(46)

28.

6 (2

1.1-

35.4

)11

6 (6

0)28

.8 (2

2.2-

34.9

)86

(8)

7.8

(2.4

-12.

8)10

9 (1

0)7.

8 (3

.1-1

2.2)

0.37

(0.2

8-0.

49)

post

-195

34

(37)

43.4

(26.

5-56

.3)

4 (3

9)40

.1 (2

4.6-

52.5

)1

(6)

25.2

(0

-45.

5)2

(6)

21.5

(0

-39.

1)0.

29 (0

.23-

0.35

)

Age

70

N (e

vent

s)a

CLT

R (9

5% C

I)N

(eve

nts)

aC

LTR

(95%

CI)

N (e

vent

s)a

CLT

R (9

5% C

I)N

(eve

nts)

aC

LTR

(95%

CI)

CLT

R (9

5% C

I)

pre-

1935

32 (2

9)41

.4 (2

8.2-

52.2

)83

(61)

36.3

(28.

4-43

.3)

26 (7

)18

.3

(4.9

-29.

8)58

(13)

15.2

(7

.1-2

2.6)

0.98

(0.6

3-1.

54)

1935

-195

36

(67)

56.5

(43.

1-66

.8)

13 (8

2)52

.1 (4

1.1-

61.1

)5

(26)

44.0

(24.

7-58

.3)

6 (2

9)39

.2 (2

2.6-

52.2

)0.

93 (0

.71-

1.23

)

post

-195

3N

AN

AN

A

a N

umbe

r of w

omen

stil

l at r

isk

at th

e in

dica

ted

age.

Bet

wee

n br

acke

ts: t

he c

umul

ativ

e nu

mbe

r of O

Cs

from

age

18

up to

the

indi

cate

d ag

e.

Abb

revi

atio

ns: F

DRs

, firs

t-deg

ree

rela

tives

; NA

, Not

app

licab

le.

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Age

Cum

ulat

ive

lifet

ime

risk

(%)

20 30 40 50 60 70

010

2030

4050

60

47 47 44 40 33 26 ) ) ) ) ) )( ( ( ( ( ( 0 0 1 1 2 3 BRCA2 Number at risk (new events)Carriers <1935

64 63 62 57 41 32 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 2 2 3

BRCA2 Number at risk (new events)

FDRs <1935115 115 114 102 48 5 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 4 13 9


Carriers 1935−195340 39 37 30 12 1 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 1 2 1


FDRs 1935−1953231 197 124 30 ) ) ) )( ( ( ( 0 1 1 1


Carriers >195339 28 15 2 ) ) ) )( ( ( ( 0 0 0 0


FDRs >1953

Carriers <1935

FDRs <1935

Carriers 1935−1953

FDRs 1935−1953

Carriers >1953

FDRs >1953

Age

Cum

ula

tive

life

tim

e r

isk (

%)

20 30 40 50 60 70

010

20

30

40

50

60


119 117 107 92 67 51 ) ) ) ) ) )( ( ( ( ( ( 0 1 3 9 14 5


FDRs <1935188 188 181 134 58 9 ) ) ) ) ) )( ( ( ( ( ( 0 0 5 23 28 11


Carriers 1935−195364 64 53 32 16 4 ) ) ) ) ) )( ( ( ( ( ( 0 0 3 8 4 1


FDRs 1935−1953379 320 169 28 ) ) ) )( ( ( ( 0 0 10 23


Carriers >195394 65 21 2 ) ) ) )( ( ( ( 0 1 0 1


FDRs >1953

Carriers <1935

FDRs <1935


FDRs 1935−1953

Carriers >1953

FDRs >1953

Figure 1. Cumulative life-time risk (CLTR) and 95%CI of ovarian cancer in BRCA1 (A) and BRCA2 (B) stratified by birth cohort and carrier status (i.e. carriers and assumed mutation carriers among FDRs).Abbreviations: FDRs, first-degree relatives

Age

Cum

ulat

ive

lifet

ime

risk

(%)

20 30 40 50 60 70

010

2030

4050

60


119 117 107 92 67 51 ) ) ) ) ) )( ( ( ( ( ( 0 1 3 9 14 5


FDRs <1935188 188 181 134 58 9 ) ) ) ) ) )( ( ( ( ( ( 0 0 5 23 28 11


Carriers 1935−195364 64 53 32 16 4 ) ) ) ) ) )( ( ( ( ( ( 0 0 3 8 4 1


FDRs 1935−1953379 320 169 28 ) ) ) )( ( ( ( 0 0 10 23


Carriers >195394 65 21 2 ) ) ) )( ( ( ( 0 1 0 1


FDRs >1953

Carriers <1935

FDRs <1935


FDRs 1935−1953

Carriers >1953

FDRs >1953

Age

Cum

ula

tive

life

tim

e r

isk (

%)

20 30 40 50 60 70

010

20

30

40

50

60


64 63 62 57 41 32 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 2 2 3


FDRs <1935115 115 114 102 48 5 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 4 13 9


Carriers 1935−195340 39 37 30 12 1 ) ) ) ) ) )( ( ( ( ( ( 0 0 0 1 2 1


FDRs 1935−1953231 197 124 30 ) ) ) )( ( ( ( 0 1 1 1


Carriers >195339 28 15 2 ) ) ) )( ( ( ( 0 0 0 0


FDRs >1953

Carriers <1935

FDRs <1935


FDRs 1935−1953

Carriers >1953

FDRs >1953

AgeBRCA1 Number at risk (new events)

AgeBRCA2 Number at risk (new events)

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Effe

ct o

f bi

rth

coho

rt o

n th

e C

LTR

of o

vari

an c

ance

r by

age

s 55

and

70

year

s in

(a

ssum

ed) B

RCA

1/2

mut

atio

n ca

rrie

rs a

nd in

the

gene

ral p

opul

atio

n Bi

rth

coho

rtBR

CA

1BR

CA

2 G

ener

al p

opul

atio

nC

arri

ers

Car

rier

s &

FD

Rs

Car

rier

sC

arri

ers

& F

DR

sA

ge 5

5H

R (9

5%C

I)p

HR

(95%

CI)

pH

R (9

5%C

I)p

HR

(95%

CI)

pPR

R (9

5%C

I)p

Birt

h co

hort

(cru

de)

pre-

1935

1935

-195

3po

st-1

953

Ref

1.49

(0.8

1-2.

76)

3.02

(1.6

6-5.

48)

<0.0

01

0.20

0<0

.001

Ref

1.41

(0.9

7-2.

06)

2.41

(1.5

7-3.

69)

<0.0

01

0.07

5<0

.001

Ref

1.08

(0.2

8-4.

15)

2.49

(0.5

5-11

.3)

0.35

4

0.90

60.

238

Ref

1.26

(0.4

8-3.

34)

2.64

(0.8

3-8.

44)

0.22

7

0.64

20.

101

NA

Birt

h co

hort

(adj

uste

d)a

pre-

1935

1935

-195

3po

st-1

953

Ref

1.57

(0.8

4-2.

90)

3.14

(1.7

2-5.

72)

<0.0

01

0.15

6<0

.001

Ref

1.41

(0.9

7-2.

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7

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Birth cohort effect in mutation carriersFor BRCA1 carriers, the effect of birth cohort on the CLTRs by age 55 and age 70 was significant (p < 0.001) and the HRs were similar (Table 2). When compared to the pre-1935 birth cohort, the HRs adjusted for mutation location and family history by age 55 for the 1935-1953 and post-1953 birth cohorts were 1.57 (95%CI 0.84-2.90, p = 0.156) and 3.14 (95%CI 1.72-5.72, p < 0.001), respectively. When we included the assumed carrier-fraction of the FDRs, these HRs were 1.41 (95%CI 1.97-2.07, p = 0.075) and 2.40 (95%CI 1.56-3.69, p < 0.001), respectively (Table 2).

For BRCA2 carriers, the overall effect of birth cohort on the CLTRs by ages 55 and 70 was not significant (Table 2). However, by age 70 the risk was increased in the 1935-1953 birth cohort compared to the pre-1935 birth cohort. The adjusted HR was 2.88 (95%CI 1.03-8.02, p = 0.043), and with inclusion of assumed carriers among the FDRs, it was 3.01 (95%CI 1.47-6.13, p = 0.002).

Birth cohort effect in general populationIn the general population, an opposite trend was observed with similar PRRs by ages 55 and 70 (Table 2). The PRRs by age 55 for the 1935-1953 and post-1953 birth cohorts were 0.90 (95%CI 0.87-0.92, p < 0.001) and 0.69 (95%CI 0.87-0.92, p < 0.001) compared to the pre-1935 birth cohort.

Table 3. Birth-cohort-specific standardized incidence ratios (SIRs) with 95% confidence intervals for BRCA1/2 mutation carriers

Age

Pre-1935 1935-1953 Post-1953a

SIR (95%CI) SIR (95%CI)p-value

SIR vs. SIR<1935SIR (95%CI)

p-value SIR vs. SIR<1935

BRCA1

30-44 43.8 (22-78) 61.2 (35-99) 0.351 144.3 (91-217) <0.001

45-54 51.1 (33-75) 108.2 (78-146) 0.002 268.6 (150-443) <0.001

55-70 27.3 (17-41) 58.5 (37-88) 0.012 NA NA

Total 20-55 48.7 (35-67) 81.5 (62-105) 0.012 129.3 (92-177) <0.001

Total 20-70 37.6 (29-48) 73.5 (59-91) <0.001 NA NABRCA2

30-44 6.7 (0-37) 5.7 (0-32) 0.917 9.5 (0-53) 0.825

45-54 15.8 (5-37) 29.3 (14-55) 0.265 76.3 (21-195) 0.009

55-70 12.3 (5-25) 65.4 (39-102) <0.001 NA NA

Total 20-55 12.3 (5-27) 19.3 (9-35) 0.376 29.2 (11-64) 0.152

Total 20-70 12.3 (7-2) 35.5 (24-51) 0.001 NA NAa Maximum age of follow-up in this birth cohort is 55 to 57 yearsAbbreviations: NA, Not applicable because there were no women at risk

Tabl

e 2.

Effe

ct o

f bi

rth

coho

rt o

n th

e C

LTR

of o

vari

an c

ance

r by

age

s 55

and

70

year

s in

(a

ssum

ed) B

RCA

1/2

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atio

n ca

rrie

rs a

nd in

the

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ral p

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rth

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CA

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2 G

ener

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Car

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R (9

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HR

(95%

CI)

pH

R (9

5%C

I)p

HR

(95%

CI)

pPR

R (9

5%C

I)p

Birt

h co

hort

(cru

de)

pre-

1935

1935

-195

3po

st-1

953

Ref

1.49

(0.8

1-2.

76)

3.02

(1.6

6-5.

48)

<0.0

01

0.20

0<0

.001

Ref

1.41

(0.9

7-2.

06)

2.41

(1.5

7-3.

69)

<0.0

01

0.07

5<0

.001

Ref

1.08

(0.2

8-4.

15)

2.49

(0.5

5-11

.3)

0.35

4

0.90

60.

238

Ref

1.26

(0.4

8-3.

34)

2.64

(0.8

3-8.

44)

0.22

7

0.64

20.

101

NA

Birt

h co

hort

(adj

uste

d)a

pre-

1935

1935

-195

3po

st-1

953

Ref

1.57

(0.8

4-2.

90)

3.14

(1.7

2-5.

72)

<0.0

01

0.15

6<0

.001

Ref

1.41

(0.9

7-2.

07)

2.40

(1.5

6-3.

69)

<0.0

01

0.07

5<0

.001

Ref

1.02

(0.2

8-3.

78)

2.22

(0.4

9-9.

98)

0.43

7

0.97

40.

300

Ref

1.21

(0.4

5-3.

23)

2.51

(0.7

5-8.

37)

0.28

4

0.78

50.

136

Ref

0.90

(0.8

7-0.

92)

0.69

(0.6

7-0.

72)

<0.0

01

<0.0

01<0

.001

Age

70

HR

(95%

CI)

pH

R (9

5%C

I)p

HR

(95%

CI)

pH

R (9

5%C

I)p

PRR

(95%

CI)

pBi

rth

coho

rt (c

rude

)pr

e-19

3519

35-1

953

post

-195

3 b

Ref

1.49

(0.9

5-2.

34)

2.98

(1.7

6-5.

04)

<0.0

01

0.08

5<0

.001

Ref

1.54

(1.1

0-2.

15)

2.53

(1.6

5-3.

86)

<0.0

01

0.01

01<0

.001

Ref

2.76

(1.0

5-7.

27)

5.26

(1.1

1-24

.8)

0.07

8

0.04

10.

036

Ref

2.90

(1.4

4-5.

62)

4.75

(1.5

0-15

.1)

0.00

4

0.00

20.

008

NA

Birt

h co

hort

(adj

uste

d)a

pre-

1935

1935

-195

3po

st-1

953

b

Ref

1.60

(1.0

1-2.

53)

3.15

(1.8

4-5.

39)

<0.0

01

0.04

5<0

.001

Ref

1.54

(1.1

1-2.

14)

2.51

(1.6

4-3.

85)

<0.0

01

0.01

0<0

.001

Ref

2.88

(1.0

3-8.

02)

5.03

(1.0

2-24

.8)

0.09

5

0.04

30.

047

Ref

3.01

(1.4

7-6.

13)

4.60

(1.3

8-15

.4)

0.00

7

0.00

20.

013

Ref

0.90

(0.8

7-0.

92)

0.70

(0.6

7-0.

73)

<0.0

01

<0.0

01<0

.001

a Th

e m

odel

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he B

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he m

odel

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ear a

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s.b

In th

is b

irth

coh

ort t

he m

axim

um a

ge o

f fol

low

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is a

ppro

xim

atel

y 55

to 5

7 ye

ars

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revi

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ns: R

ef re

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coho

rt; F

DRs

firs

t-deg

ree

rela

tives

; NA

not

app

licab

le.

96

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Comparison of incidence carriers and general populationFor BRCA1 carriers, the SIRs by age 55 for the pre-1935, 1935-1953, and post-1953 birth cohorts were 57.3 (95%CI 32-95), 93.5 (95%CI 69-125) and 160.9 (95%CI 113-222), respectively. In comparison with the pre-1935 birth cohort, SIRs were significantly higher in the 1935-1953 (p < 0.001) and post-1953 (p = 0.012; Table 3) birth cohorts.

For BRCA2 carriers, the SIRs by age 55 were not significantly different for the pre-1935, 1935-1953, and post-1953 birth cohorts: 12.3 (95%CI 5-27), 19.3 (95%CI 9-35) and 29.2 (95%CI 11-64), respectively. However, significantly increased SIRs were seen from age 55 onwards for the pre-1935 and 1935-1953 birth cohorts: 12.3 (95%CI 5-7) and 35.5 (95%CI 24-51), respectively (p = 0.001).

Discussion

Increased OC risks were observed for BRCA carriers born in the two more recent birth cohorts. Compared to carriers born pre-1935, the HRs by age 55 were 1.41 (95%CI 0.97-2.07) for BRCA1 carriers born between 1935 and 1953, and 2.40 (95%CI 1.56-3.69) for those born post-1953. For BRCA2 carriers, these HRs were 1.21 (95%CI 0.45-3.23) and 2.51 (95%CI 0.75-8.37), respectively. Over the same time span, the OC risk decreased in more recent birth cohorts in the general background population, leading to higher additional risks for OC in carriers born more recently. Compared to pre-1935, the SIRs by age 55 were 1.7 times (p = 0.012) and 2.7 times (p < 0.001) higher in BRCA1 carriers born between 1935 and 1953 and post-1953, and these SIRs were 1.6 times (p = 0.376) and 2.4 times (p = 0.152) higher in BRCA2 carriers born between 1935 and 1953 and post-1953. Thus, this trend only reached statistical significance in BRCA1 carriers.

Our findings on the increased risk of developing OC in BRCA1 mutation carriers born more recently are in line with several previous clinic-ascertained studies that indicated a higher OC risk for BRCA1 carriers from more recent birth cohorts.[10-13] One study, which included the index cases, detected significant differences in birth-cohort-specific CLTR in BRCA1 carriers by ages 40 and 60.12 The CLTR by age 40 was 4 times higher in a birth cohort post-1958 compared to pre-1958, and by age 60 it was 2.5 times higher in birth cohort post-1940 compared to pre-1941. Another study, which excluded the index cases, showed similar but non-significant trends for BRCA1 carriers. Compared to pre-1920, the HRs by age 70 for a 1920-1939 and post-1939 cohorts were 1.8 (95%CI 0.6-5.6) and 3.7 (95%CI 0.9-15.8), respectively.11

For BRCA2 carriers, no significant effect of birth cohort on the OC risk has been observed thus far.10-13 This could be due to the smaller numbers of BRCA2 carriers and of OCs, in combination with the later onset of OC in BRCA2 carriers compared to onset in BRCA1 carriers. The study that included the index cases found no effect by age 40 for birth cohort (pre-1958 vs. post-1958).10 We did find a significantly increased risk in more recent birth cohorts, which is probably due to the longer follow-up time in our study, since we only detected a significant effect by age 70 and not by age 55.

In the Dutch general population, we found decreasing CLTRs in more recent birth cohorts, irrespective of age. When compared to the pre-1935 birth cohort, the relative

97

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R 2

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R 4

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risks of OC were statistically significantly lower in more recent birth cohorts (PRRs were 0.9 (p < 0.001) and 0.7 (p < 0.001) for the 1935-1953 and post-1953 birth cohorts, respectively). A decreasing trend was also reported for some North American and Western European populations.1,2

The uptake of RRSO among our BRCA1/2 mutation in carriers is lower (i.e. 32-33%) than seen in recent cohorts with uptakes up to 87%.25 This is because our carrier cohort included women born in 1910 or later whereas the uptake of RRSO started to increase gradually over the last 2 decades following the discovery of BRCA1/2. And it is only since 2009 that RRSO is advised proactively, following the reports showing the ineffectiveness of screening in reducing ovarian/tubal cancer mortality.26-28

A number of reproductive and hormonal factors are known to have impact on the risk of both BC and OC in more recent birth cohorts.29 These factors include fewer full-term pregnancies, an older age at first full-term pregnancy, less breastfeeding, and more hormonal replacement therapy.29-32 However, the use of oral contraceptives is associated with an increased BC risk but a decreased OC risk. For BC, the risk-increases over time in both the general population as well as in the BRCA carriers are concordant.2,10,11 Both trends can be attributed to changes in reproductive and hormonal factors, an unhealthier lifestyle (e.g. alcohol consumption, physical activity, BMI), and an increase in BC screening; factors which will play a role in both populations.33-37 The opposite trends in OC risk in the general population and in BRCA mutation carriers are difficult to explain from an underlying genetic or environmental mechanism, as it is expected that both populations have in general a similar distribution of risk factors other than BRCA. Such an explanation could not be assessed in this study because those data were not available, and data on interaction between these risk factors and BRCA mutations is scarce. However, since 1970, oral contraceptives have increasingly been used in the general population, which is seen as the major explanation for the decreased OC risk.38 This suggests at least one possible explanation for the divergent risks: if BRCA carriers use oral contraceptives less often than women in the general population because oral contraceptives increase their risk of BC, then BRCA carriers would not benefit from the protective effect provided by oral contraceptives for OC. No data is currently available to explore this hypothesis.

To our knowledge, this is the first study to assess the effect of birth cohort on the OC risk in both BRCA mutation carriers and their background general population. The follow-up time in this study was long enough to present risks by age 55 for all birth cohorts, and by age 70 for the two older birth cohorts. At both ages the risk was increased similarly, which indicates that the risk curve did not shift due to an earlier age at diagnosis. Though, the HRs up to age 70 in the post-1953 cohort should be interpreted carefully as only a few women in this cohort were older than age 55. The actual decrease in the OC risk in non-carriers is likely to be even a little stronger than that seen in the Dutch cancer registry general population data, since carriers are also included in this population data. We did not adjust for this in the analyses, as this requires multiple uncertain assumptions regarding the age- and birth cohort related percentage of BRCA-related OC.39,40 No registry data was available before calendar year 1960 or for the period 1963-1977, and the average incidence in the adjacent years was used. We assume that this did not affect our results, since PRRs were stable over time

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and the SIRs showed the expected age-related variation. The data from the mutation carriers was collected in the Northern Netherlands, whereas the data on the general population was not specific for this region as only national data was available for older calendar years. However, the population of The Netherlands is relatively small and population incidence rates of OC are comparable throughout the country.

In conclusion, there are inverse trends in the OC risk in BRCA1/2 mutation carriers compared to the general population. Mutation carriers born in more recent birth cohorts have a substantially higher additional risk for OC, and this is especially true for BRCA1 carriers. It is difficult to explain the inverse trends in the OC risk in BRCA carriers compared to the general population, indicating that further analysis of the influence of lifestyle, hormonal and reproductive factors is needed.

AcknowledgementsWe thank Jackie Senior and Kate Mc Intyre for editing the manuscript.

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2. Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC, et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 2014;110:535-45.

3. Dutch ovarian cancer risk. Dutch Cancer Registry. Available at: http://www.cijfersoverkanker.nl/selecties/dataset_2/img5535236f89122?language=en. Accessed 13 Apr 2015.

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11. Brohet RM, Velthuizen ME, Hogervorst FB, Meijers-Heijboer HE, Seynaeve C, Collee MJ, et al. Breast and ovarian cancer risks in a large series of clinically ascertained families with a high proportion of BRCA1 and BRCA2 Dutch founder mutations. J Med Genet 2014;51:98-107.

12. Kroiss R, Winkler V, Bikas D, Fleischmann E, Mainau C, Frommlet F, et al. Younger birth cohort correlates with higher breast and ovarian cancer risk in European BRCA1 mutation carriers. Hum Mutat 2005;26:583-9.

13. Evans DG, Shenton A, Woodward E, Lalloo F, Howell A, Maher ER. Penetrance estimates for BRCA1 and BRCA2 based on genetic testing in a Clinical Cancer Genetics service setting: risks of breast/ovarian cancer quoted should reflect the cancer burden in the family. BMC Cancer 2008;8:155.

14. Cancer in the Netherlands till 2020, trends and prognoses [Kanker in Nederland tot 2020, trends en prognoses]. The Dutch Cancer registry in collaboration with the Dutch Cancer Society. Available at: http://repository.kwfkankerbestrijding.nl/PublishingImages/Kanker%20in%20Nederland%20tot%202020.pdf. Oisterwijk: VDB Almedeon bv, 2011. Accessed 13 Apr 2015.

15. Van der Hout AH, van den Ouweland AM, van der Luijt RB, Gille HJ, Bodmer D, Bruggenwirth H, et al. A DGGE system for comprehensive mutation screening of BRCA1 and BRCA2: application in a Dutch cancer clinic setting. Hum Mutat 2006;27:654-66.

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17. Vos JR, Teixeira N, Van der Kolk DM, Mourits MJE, Matti MA, Van Leeuwen FE, et al. Variation in mutation spectrum partly explains regional differences in the breast cancer risk of female BRCA mutation carriers in the Netherlands. Cancer Epidemiol Biomarkers Prev. 2 2014;23:2482-91.

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18. Vos JR, de Bock GH, Teixeira N, van der Kolk DM, Jansen L, Mourits MJ, et al. Proven non-carriers in BRCA families have an earlier age of onset of breast cancer. Eur J Cancer 2013;49:2101-6.

19. Cancer Incidence in Five Continents, Volumes I to X. International Agency for Research on Cancer. Available at: http://ci5.iarc.fr/CI5I-X/Pages/download.aspx. Accessed 11 November 2014.

20. Dutch ovarian cancer incidence. Dutch Cancer Registry. Available at: http://www.cijfersoverkanker.nl/selecties/Dataset_2/img552b78d4a97e3?language=en. Accessed 13 Apr 2015.

21. Thompson D, Easton D, Breast Cancer Linkage Consortium. Variation in BRCA1 cancer risks by mutation position. Cancer Epidemiol Biomarkers Prev 2002;11:329-36.

22. Thompson D, Easton D. Variation in cancer risks, by mutation position, in BRCA2 mutation carriers. Am J Hum Genet 2001; 68:410-9.

23. Vos JR, Hsu L, Brohet RM, Mourits MJ, de Vries J, Malone KM, et al. Bias correction methods explain much of the variation seen in breast cancer risks of BRCA1/2 mutation carriers. J Clin Oncol 2015; JCO.2014.59.0463.

24. R Core Team. R Foundation for Statistical Computing: R: A Language and Environment for Statistical Computing (ed http://www.R-project.org/). Vienna, Austria, R Foundation for Statistical Computing, 2013

25. Van der Aa JE, Hoogendam JP, Butter ES, Ausems MG, Verheijen RH, Zweemer RP. The effect of personal medical history and family history of cancer on the uptake of risk-reducing salpingo-oophorectomy. Fam Cancer 2015; DOI 10.1007/s10689-015-9827-7

26. Meeuwissen PAM, Seynaeve C, Brekelmans CTM, Meijers-Heijboer HJ, Klijn JGM, Burger CW. Outcome of surveillance and prophylactic salpingo-oophorectomy in asymptomatic women at high risk for ovarian cancer. Gynecol Oncol 2005;97:476-82.

27. Olivier RI, Lubsen-Brandsma MAC, Verhoef S, Van Beurden M. CA125 and transvaginal ultrasound monitoring in high-risk women cannot prevent the diagnosis of advanced ovarian cancer. Gynecol Oncol 2006;100:20-6.

28. van der Velde NM, Mourits MJ, Arts HJ, de Vries J, Leegte BK, Dijkhuis G, Oosterwijk JC, de Bock GH. Time to stop ovarian cancer

screening in BRCA1/2 mutation carriers? Int J Cancer 2009;124:919-23.

29. Friebel TM, Domchek SM, Rebbeck TR. Modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers: systematic review and meta-analysis. J Natl Cancer Inst 2014;106:dju091.

30. Hunn J, Rodriguez GC. Ovarian cancer: etiology, risk factors, and epidemiology. Clin Obstet Gynecol 2012;55:3-23.

31. Key TJ, Verkasalo PK, Banks E. Epidemiology of breast cancer. Lancet Oncol 2001;2:133-140.

32. Collaborative Group on Hormonal Factors in Breast Cancer. Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet 2001;358:1389-99.

33. Romieu I, Scoccianti C, Chajes V, de Batlle J, Biessy C, Dossus L, et al. Alcohol intake and breast cancer in the European prospective investigation into cancer and nutrition. Int J Cancer 2015;137:1921-30.

34. Monninkhof EM, Elias SG, Vlems FA, van der Tweel I, Schuit AJ, Voskuil DW, van Leeuwen FE, TFPAC. Physical activity and breast cancer: a systematic review. Epidemiology 2007;18:137-57.

35. Pijpe A, Manders P, Brohet RM, Collee JM, Verhoef S, Vasen HF, Hoogerbrugge N, van Asperen CJ, Dommering C, Ausems MG, Aalfs CM, Gomez-Garcia EB, HEBON, Van’t Veer LJ, van Leeuwen FE, Rookus MA. Physical activity and the risk of breast cancer in BRCA1/2 mutation carriers. Breast Cancer Res Treat 2010;120:235-44.

36. Gathirua-Mwangi WG, Zollinger TW, Murage MJ, Pradhan KR, Champion VL. Adult BMI change and risk of Breast Cancer: National Health and Nutrition Examination Survey (NHANES) 2005-2010. Breast Cancer 2015; DOI 10.1007/s12282-015-0638-3

37. Manders P, Pijpe A, Hooning MJ, Kluijt I, Vasen HF, Hoogerbrugge N, van Asperen CJ, Meijers-Heijboer H, Ausems MG, van Os TA, Gomez-Garcia EB, Brohet RM, HEBON, van Leeuwen FE, Rookus MA. Body weight and risk of breast cancer in BRCA1/2 mutation carriers. Breast Cancer Res Treat 2011;126:193-202.

38. Collaborative Group on Epidemiological Studies of Ovarian Cancer, Beral V, Doll

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R, Hermon C, Peto R, Reeves G. Ovarian cancer and oral contraceptives: collaborative reanalysis of data from 45 epidemiological studies including 23,257 women with ovarian cancer and 87,303 controls. Lancet 2008;371:303-14.

39. Giannakeas V, Sopik V, Shestopaloff K, Iqbal J, Rosen B, Akbari M, et al. A model for estimating ovarian cancer risk: Application for preventive oophorectomy. Gynecol Oncol 2015; doi:10.1016/j.ygyno.2015.08.020

40. Pearce CL, Stram DO, Ness RB, Stram DA, Roman LD, Templeman C, et al. Population distribution of lifetime risk of ovarian cancer in the United States. Cancer Epidemiol Biomarkers Prev 2015;24:671-6.

Chapter 6Bias explains most of the parent-of-origin eff ect on

breast cancer risk in BRCA1/2 mutation carriers

Janet R. VosJan C. Oosterwijk

Cora M. Aalfs Matt i A. Rookus

Muriel A. Adank Annemarie H. van der Hout

Christi J. van Asperen Encarna B. Gómez Garcia

Arjen R. Mensenkamp Agnes Jager

Margreet G.E.M. Ausems Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON)

Marian J. Mourits Geertruida H de Bock

Submitt ed for publication

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Abstract

BackgroundPaternal transmission of a BRCA mutation has been reported to increase the risk of breast cancer in offspring more than when the mutation is maternally inherited. As this effect might be caused by referral bias, the aim of this study was to assess the parent-of-origin effect of the BRCA1/2 mutation on the breast cancer lifetime risk, when adjusted for referral bias.

MethodsA Dutch national cohort including 1,314 proven BRCA1/2 mutation carriers and covering 54,752 person years. Data were collected by family cancer clinics, via questionnaires and from the national Dutch Cancer Registry. The parent-of-origin effect was assessed using Cox regression analyses, both unadjusted and adjusted for referral bias. Referral bias was operationalized by number of relatives with cancer or personal cancer history.

ResultsThe mutation was of paternal origin in 330 (42%, p < 0.001) BRCA1 and 222 (42%, p < 0.001) BRCA2 carriers. Paternal origin increased the risk of prevalent breast cancer for BRCA1 (HR = 1.54, 95%CI 1.19-2.00) and BRCA2 carriers (HR = 1.40, 95%CI 0.95-2.06). Adjusted for referral bias by family history, these HRs were 1.63 (95%CI 1.19-2.24) and 1.46 (95%CI 0.92-2.32), respectively. Adjusted for referral bias by personal history, these HRs were 0.66 (95%CI 0.25-1.71) and 1.14 (95%CI 0.42-3.15), respectively.

ConclusionOur results indicate that the parent-of-origin effect mainly depends on how one corrects for referral bias: correction for family history does not substantially impact this effect, while correction for personal cancer history does. In a larger prospective cohort, the combined impact of referral bias by family and personal history should be addressed.

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The parent-of-origin effect on breast cancer risk in BRCA1/2 mutation carriers

Introduction

Information about family history is an important factor in the risk assessment of breast cancer. It serves as a predictor for estimating both the cancer risk and the probability of being a mutation carrier, e.g. a carrier of a BRCA1 or BRCA2 mutation.1-4 Once a BRCA mutation has been detected within a family, the family history of breast or ovarian cancer remains a relevant risk factor.5, 6 In addition, it has been suggested that a paternal origin of the BRCA mutation increases breast cancer risk while decreasing ovarian cancer risk.7-9 The mechanism for this parental origin effect might be a difference in maternal and paternal imprinting of the BRCA genes and their modifier genes.7, 8 However, it has also been suggested that the parent-of-origin effect of the BRCA gene may be caused by biases due to the referral criteria, which are mainly based on the number of affected relatives and their ages at diagnosis.8, 10 Women with a paternal origin of the BRCA mutation may be less likely to be referred for genetic testing because they are more likely to have a smaller mean number of affected first-degree relatives (FDRs). In addition, women with a paternal origin of the mutation might be more likely to have a higher number of affected second-degree relatives (SDRs), to have more early-onset FDRs or to have early breast cancer themselves compared to women with a maternal origin of the mutation. For this reason, some studies have taken referral bias into account by including only BRCA carriers who were unaffected at baseline and correcting for breast cancer in FDRs in combination with environmental factors,8 or by correcting for the year of birth and year of referral.7

Nonetheless, it could be that this referral bias is only relevant for index carriers, because once a mutation is detected in the family, genetic testing becomes available to the rest of the family following a cascade protocol.11 In the Netherlands, this means that family members who test positive for a (familial) mutation are provided with a letter to help inform their relatives about hereditary cancer. It has, however, been shown that the sharing of this information about carrier-ship depends on the gender, age and degree-of-relatedness of the index carrier. In hereditary breast-ovarian cancer, male relatives, in particular, are observed to be ‘blockers’ of this communication.12-16 Therefore, it might be that women with a paternal origin of the mutation are less often ‘triggered’ to undergo genetic testing until they develop cancer themselves, which causes subsequent referral bias (or genetic testing bias).

To assess the possible impact of these referral biases on the parent-of-origin effect, it might be relevant to consider only factors related to referral criteria and aspects of these criteria that include the family history of both breast and ovarian cancer in first- and second-degree relatives, and prevalent and/or incident cancer cases. Therefore, the aim of this study was to assess the effect of the parental origin of the BRCA mutation on the breast cancer risk in proven BRCA1/2 mutation carriers, and whether this effect still remains when only all dimensions of referral bias by family history or personal history of cancer are taken into account.

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Methods

Study cohortFor this study, data from the Dutch national HEBON study (Hereditary Breast and Ovarian cancer study, the Netherlands) were used. The HEBON study was approved by the medical ethical committees of all participating hospitals, and subjects signed an informed consent form upon participation. From 1999 onwards, subjects who underwent genetic testing for the BRCA1/2 mutation in the course of genetic counselling at any of the Family Cancer Clinics in The Netherlands were invited to participate in the HEBON study. From 2011 onwards, all subjects were invited to fill in a (follow-up) questionnaire on clinical history and risk factors. Thus, the data in this study consists of retrospective data collection with prospective follow-up of carriers’ cancer status via linkage with the National Dutch Cancer Registry and questionnaires. The clinics provided data on the date of birth, the cancer status, the mutation status, and the date of the DNA test. Data on the carriers’ breast cancer status and ovarian cancer status was also obtained by linkage with the Dutch Cancer Registry with national coverage for the calendar years 1989-2011. Data on cancer status, risk-reducing surgeries and family history were self-reported by means of the questionnaire.

The current study included only proven female BRCA1/2 mutation carriers who completed the questionnaire. Exclusion criteria were: being the index carrier in the family, i.e. the first member who tested positive for the mutation and who was affected at the time of DNA-testing (N = 655); no available information on the parental origin of the BRCA mutation (data either missing or reported as unknown) (N = 124); carrying a mutation from both parents or carrying both a BRCA1 and BRCA2 mutation (N = 48); or when a risk-reducing mastectomy (RRM) was performed but the age at RRM was unknown in women without breast cancer (N = 7).

Outcome eventThe outcome was defined as primary breast cancers. The subjects’ breast cancer and ovarian cancer status was either registry-confirmed or self-reported. If a woman reported that a malignancy was detected at the time of the RRM or a risk-reducing salpingo-oophorectomy (RRSO) in a calendar year outside the coverage of the Dutch Cancer Registry, her breast cancer or ovarian cancer status was adapted accordingly.

DeterminantsReferral bias was operationalized by family history or by personal history of cancer (Box 1).

Referral bias by family history was evaluated by taking into account: a) the year of the family’s ascertainment, because referral criteria have become slightly less stringent over time; b) referral criteria and c) other family history of cancer. Data on the family history of breast cancer, ovarian cancer and other cancers was available for both FDRs and SDRs. For some FDRs and SDRs, the family history of cancer for one or more family members was not reported. In those cases we assumed that the family history was negative. Separate covariates where created per tumor type, for early-onset tumors, and for degree of relatedness (Box 1).

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Referral bias by personal history of cancer was evaluated by considering only incident and semi-incident cases. Incident cases were defined as breast cancer cases occurring ≥3 months after a woman’s DNA test date. Semi-incident cases were defined as breast cancer cases occurring after the DNA test date of the family’s index carrier.

Box 1. Operationalization of referral biasa) Year of the family’s ascertainment, i.e. year of index carriers’ genetic testingb) Having a family history of cancer that meets the current referral criteria:

≥1 FDR or SDR with breast cancer by age 35; ≥1 FDR or SDR with ovarian cancer; ≥1 male FDR or SDR with breast cancer; ≥2 FDRs with breast cancer of which ≥1 case by age 50; or ≥3 FDRs or SDRs with breast cancer of which ≥1 affected FDR by

age 50 or ≥1 affected SDR by age 60c) Having a family history of cancer in males, females or both:

≥1 parent, ≥1 siblings, ≥1 FDRs, ≥1 siblings or kids, or ≥1 SDRs affected with breast cancer by age 40, age 50, age 60 or any age;

A mother, ≥1 siblings, ≥1 FDRs, ≥1 siblings or kids, or ≥1 SDRs affected with ovarian cancer by age 40, age 50, age 60 or any age;

≥1 parent, ≥1 siblings, ≥1 FDRs, ≥1 siblings or kids, or ≥1 SDRs affected with a cancer other than breast and ovarian cancer or cancer of unknown type by age 40, age 50, age 60 or any age;

d) Personal history of breast or ovarian cancer

Statistical analysisDescriptive statistics were used to give an overview of the study population characteristics, and appropriate tests were used to test for differences between BRCA1 and BRCA2 mutation carriers.

The effect of the parental origin of the BRCA mutation on the risk of developing breast cancer was estimated using Cox regression survival analyses. Robust standard errors were calculated to account for the clustering of carriers within families. The assumption of proportional hazards was tested using Schoenfeld residuals and log-minus-log plots. Censoring was applied at the moment any of the following events occurred: breast cancer, RRM, RRSO, ovarian cancer or last date of information. To assess whether the effect of parental origin of the BRCA mutation was independent of referral bias due to a family history of cancer, Cox regression analyses of prevalent cases were adjusted as described previously (Box 1). Factors that altered the parental-origin-effect by 5% or more were considered to be relevant, and are reported in the result section. We also took the second-degree family history into account in order to evaluate the potential referral bias. Because this information was not available for the complete cohort, we used a sub cohort of 742 (94%) BRCA1 carriers and 488 (93%) BRCA2 carriers.

To assess whether the parental-origin-effect of the BRCA mutation was affected by referral bias due to a personal history of cancer, Cox regression analyses were performed on semi-incident and incident cases. For the semi-incident case analyses,

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follow-up time and cases were counted from the date of the family index carrier’s DNA test. For the incident case analyses, follow-up time and cases (≥3 mo. after DNA-test) were counted from the woman’s date of DNA test onwards. In these analyses only mutation carriers who did not have breast or ovarian cancer, RRM or RRSO before the start of the follow-up period were included as these were reasons for censoring.

Sensitivity analyses were performed for the unadjusted analyses by changing the outcome event to 1) prevalent registry-confirmed cases or 2) all self-reported and registry-confirmed prevalent cases. In addition, RRSO was included as a time-dependent covariate and no censoring was applied at this event. Other sensitivity analyses were performed only for the prevalent case analyses adjusted for family history of cancer. First, the analyses were additionally adjusted for the number of reported family members. Secondly, carriers with missing information for the family history factors were excluded. Thirdly, analyses were performed with the family history as documented at the time of personal genetic testing because this might be the more optimal scenario to assess referral bias.

All analyses were performed with stratification by the BRCA1/2 gene. The analyses were performed using R, and statistical significance was defined as p < 0.05.17

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Results

Population characteristics In total 1,314 BRCA mutation carriers were included in this study, of whom 788 (60%) harbored a mutation in the BRCA1 gene and 526 (40%) in the BRCA2 gene (Table 1). Of these, 236 (33%) of the BRCA1 carriers and 120 (23%) of the BRCA2 carriers developed breast cancer. For both BRCA1 and BRCA2 carriers, the percentage of ovarian cancer was relatively low, 2-4%, most likely due to the high rate of RRSO (about 65%). BRCA1 carriers had more FDRs affected with breast cancer before age 50 (38% vs 31%, p = 0.010) or ovarian cancer at any age (20% vs 11%, p < 0.001) compared to BRCA2 carriers, but had fewer male FDRs with breast cancer (0.9% vs. 3.6%, p < 0.001) which is in line with known differences in cancer penetrance between BRCA1 and BRCA2 families.18-21

The BRCA mutation was of paternal origin in 552 (42%) women: 330 (42%, p <0.001) BRCA1 and 222 (42%, p < 0.001) BRCA2 carriers (Table 2). For both BRCA1 and BRCA2 carriers, women with a paternal origin of the BRCA mutation differed significantly from the women with a maternal origin in the following ways: they were more likely to have breast cancer themselves (BRCA1pat 42% vs. BRCA1mat 26%; BRCA2pat 28% vs. BRCA2mat 19%); less likely to have FDRs affected with breast or ovarian cancer (BRCA1pat 37% vs. BRCA1mat 82%; BRCA2pat 37% vs. BRCA2mat 74%); less likely to have a mother affected with any cancer (BRCA1pat 17% vs. BRCA1mat 83%; BRCA2pat 17% vs. BRCA2mat 73%); and were more likely to have a father with any cancer (BRCA1pat 34% vs. BRCA1mat 20%; BRCA2pat 44% vs. BRCA2mat 30%). While breast cancer was the most common cancer among mothers of mutation carriers, only a small fraction of the fathers were affected with breast cancer (Table 2).

BRCA1/2 mutation carriers with a paternal origin of the mutation were more often affected with cancer at the time of the index carrier’s DNA test, and this difference increased up to the time of their personal DNA test (BRCA1pat 20% vs. 25%; BRCA1mat 7% vs. 13%; BRCA2pat 10% vs. 13%; BRCA2mat 7% vs. 13%), which also affected the difference in percentages between carriers with a paternal or maternal mutation. BRCA1/2 mutation carriers with a paternal mutation who were unaffected at the time of DNA testing were more likely to have affected siblings, children or SDRs at this time compared to unaffected mutation carriers with a maternal origin of the mutation (Supplementary Table 1).

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Table 1. Study population characteristics BRCA1N = 788

BRCA2N = 526 p-value

Clinical characteristicsAge at follow-up, median (IQR)Year of ascertainment family <2005, N (%)Age at DNA-testing

Missing, N (%)median (IQR)

46 (37-55)200 (35.9%)

236 (30.0%)39.1 (30.5-47.4)

48 (39-58)156 (37.3%)

110 (20.9%)41.9 (33.4-51.1)

0.0050.650

<0.001Breast cancer

Number (%)Age at diagnosis, median (IQR)

258 (32.7%)41.9 (35.4-49.6)

120 (22.8%)45.7 (39.9-51.6)

<0.001<0.001

Ovarian cancerNumber (%)Age at diagnosis, median (IQR)

32 (4.1%)51.0 (47.7-58.0)

10 (1.9%)54.7 (52.9-57.8)

0.0290.224

Incident breast cancerBC after DNA-testing, N (% of BC patients with DNA date)Age at diagnosis, median (IQR)

47 (32.9%)43.6 (35.4-48.0)

35 (39.1%)47.2 (39.7-52.5)

0.2580.039

Incident ovarian cancerOC after DNA-testing, N (% of OC patients with DNA date)Ages at diagnosis

2 (15.4%)38; 50

4 (50%)50; 54; 56; 58

0.1460.133

RRMNumber (%)Age at surgery, median (IQR)

197 (25.0%)36 (31-43)

113 (21.5%)40 (34-46)

0.1410.004

RRSONumber (%)Age at surgery, median (IQR)

511 (64.8%)44 (39-50)

338 (64.3%)47 (41-54)

0.827<0.001

Family factors

Paternal origin of BRCA mutation, N (%) 330 (41.9%) 222 (42.2%) 0.906Mothers with early-onset BC

BC≤40, N(%)BC≤50, N(%)

73 (9.3%)153 (19.4%)

31 (5.9%)79 (15.0%)

0.0270.041

Parents with cancer other than BC/OC and no BC/OCFather, N(%)Mother, N(%)

196 (24.9%)68 (8.6%)

178 (33.8%)58 (11.0%)

<0.0010.148

FDRs with BC or OC≥1 FDRs with BC (%)≥1 FDRs with BC<50 (%)1 male FDR with BC(%)≥1 FDR with OC (%)

397 (50.5%)300 (38.1%)7 (0.9%)160 (20.3%)

268 (51.0%)164 (31.2%)19 (3.6%)60 (11.4%)

0.8750.010

<0.001<0.001

Abbreviations: BC, breast cancer; FDR, first-degree relatives; IQR, interquartile range (i.e. 25th percentile – 75th percentile); OC, ovarian cancer; RRM, bilateral risk-reducing mastectomy; RRSO, bilateral risk-reducing salpingo-oophorectomy

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)2

(0.4

%)

<0.0

01<0

.001

<0.0

01<0

.001

0.65

5

12 (5

.4%

)1

(0.5

%)

2 (0

.9%

)1

(0.5

%)

6 (2

.7%

)

152

(50.

0%)

30 (9

.9%

)77

(25.

3%)

42 (1

3.8%

)5

(1.6

%)

<0.0

01<0

.001

<0.0

01<0

.001

0.54

0Pa

rent

s w

ith c

ance

r oth

er th

an B

C/O

CM

othe

r Ca

(%)

Fath

er w

ith C

a (%

)36

(10.

9%)

108

(32.

7%)

32 (7

.0%

)88

(19.

2%)

0.05

5<0

.001

24 (1

0.8%

)93

(41.

4%)

34 (1

1.2%

)86

(28.

3%)

0.89

30.

002

Affe

cted

FD

Rs w

ith B

C o

r OC

≥1 F

DRs

with

BC

(%)

≥1 F

DRs

with

BC

≤50

(%)

≥1 F

DRs

with

OC

(%)

113

(34.

2%)

88 (2

6.7%

)22

(6.7

%)

286

(62.

4%)

212

(46.

3%)

138

(30.

3%)

<0.0

01<0

.001

<0.0

01

80 (3

6.0%

)56

(25.

2%)

9 (4

.1%

)

188

(61.

8%)

108

(35.

5%)

51 (1

6.8%

<0.0

010.

012

<0.0

01SD

R fa

mily

his

tory

N =

313

N =

429

N =

208

N =

280

Affe

cted

SD

Rs w

ith B

C o

r OC

≥1 S

DRs

with

BC

(%)

≥1 S

DRs

with

OC

(%)

190

(60.

7%)

83 (2

6.5%

)24

1 (5

6.0%

)14

6 (3

4.0%

)0.

204

0.03

012

6 (6

0.6%

)33

(15.

9%)

173

(61.

8%)

48 (1

7.1%

)0.

786

0.70

8A

bbre

viat

ions

: BC

, bre

ast c

ance

r; FD

R, fi

rst-d

egre

e re

lativ

es; I

QR,

inte

rqua

rtile

ran

ge (i

.e. 2

5th p

erce

ntile

– 7

5th p

erce

ntile

); O

C, o

vari

an c

ance

r; RR

M,

bila

tera

l ris

k-re

duci

ng m

aste

ctom

y; R

RSO

, bila

tera

l ris

k-re

duci

ng s

alpi

ngo-

ooph

orec

tom

y; S

DR,

sec

ond-

degr

ee re

lativ

es

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The parent-of-origin effect and referral bias operationalized by family history of cancerA woman’s breast cancer risk was significantly increased when the BRCA1 mutation was of paternal origin (HR = 1.54, 95%CI 1.19-2.00). For BRCA2 carriers this increase was of the same order of magnitude, but not statistically significant (HR = 1.40, 95%CI 0.95-2.06; Fig. 1; Table 3).

When taking into account the referral criteria and other family history factors separately, the risk increase associated with the paternal origin of the BRCA mutation varied from 1.41 to 1.83 in BRCA1 carriers and 1.27 to 1.62 in BRCA2 carriers (Figure 1). When taking into account the factors with the most impact (i.e. maternal breast cancer by age 60 and ovarian cancer in FDRs) together in one model, this resulted in a HR of 1.63 (95%CI 1.19-2.24) for BRCA1 carriers and 1.46 (95%CI 0.92-2.32) for BRCA2 carriers.

For BRCA1 carriers, the effect of the paternal origin remained significantly increased irrespective of the adjustment. For BRCA2 carriers, the effect of the paternal origin was only significantly increased when adjusted for maternal breast cancer up to age 60, or for having a sibling with breast cancer. For both BRCA1 and BRCA2 carriers, adjustment for having FDRs with ovarian cancer mitigated the effect of paternal origin, whereas having FDRs with breast cancer increased the effect. Overall, adjustment for the second-degree family history had a similar but weaker impact on the effect on the paternal origin of the BRCA mutation.

The combination of the parent-of-origin effect and the effect of having a positive family history is presented in Figure 2. Among women with a paternally inherited BRCA mutation, having a mother with breast cancer might increase their risk for breast cancer even further.

The parent-of-origin effect and referral bias operationalized by personal history of cancerThe semi-incident case analyses included 46 BRCA1-related and 36 BRCA2-related breast cancers. The effect of the paternal origin was 1.02 (95%CI 0.56-1.88) for BRCA1 carriers and 0.94 (95%CI 0.48-1.85) for BRCA2 carriers (Table 3). The incident case analyses included 16 BRCA1-related and 15 BRCA2-related breast cancers. The effect of the paternal origin was 0.77 (95%CI 0.25-1.71) for BRCA1 carriers and 1.14 (95%CI 0.24-3.15) for BRCA2 carriers.

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The parent-of-origin eff ect on breast cancer risk in BRCA1/2 mutation carriers

0 1 2 3

A. BRCA1 mutation carriers

Unadjusted

Adjusted for:

BC in mother

BC≤40 in mother

BC≤50 in mother

BC≤60 in mother

OC in mother

OC in FDRs: ≥1 vs 0

0 1 2 3

B. BRCA2 mutation carriers

Unadjusted

Adjusted for:

BC in mother

BC≤40 in mother

BC≤50 in mother

BC≤60 in mother

BC in siblings: ≥1 vs 0

OC in mother

OC≤60 in mother

OC in FDRs: ≥1 vs 0 *

B. Breast cancer risk ratio for paternal versus maternal origin of the BRCA2 mutation

A. Breast cancer risk ratio for paternal versus maternal origin of the BRCA1 mutation

*

#

Figure 1. The eff ect of the parent-of-origin on the breast cancer risk: comparing the BRCA1/2 mutation of paternal origin to maternal origin (HR, 95%CI), without and with taking into account the indicated factors of family history. A) BRCA1 carriers and B) BRCA2 carriers* Ca in FDRs: any cancer other than BC and OC, or cancers of unknown site in male and female FDRs# BC in siblings: breast cancer in male and female siblings

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Figure 2. The combined impact of the parent-of-origin eff ect and the eff ect of family history (as indicated on the left) on the breast cancer risk (HR, 95%CI). A) BRCA1 mutation carriers and B) BRCA2 mutation carriers* Signifi cant predictor (p < 0.05)Note: the light blue bars present the same data as presented in fi gure 1, i.e. representing the eff ect of the paternal origin adjusted for the indicated family history.

0 1 2 3 4 5 6 7 8

BC in mother *

BC≤40 in mother *

BC≤50 in mother *

BC≤60 in mother *

OC in mother

OC in FDRs: ≥ 1 vs 0 *

HR with 95%CI

A. BRCA1 mutation carriers

Maternal origin BRCA1 and not havingthe indicated family history (reference)

Maternal origin BRCA1 and havingthe indicated family history

Paternal origin BRCA1 and not havingthe indicated family history

Paternal origin BRCA1 and having theindicated family history

0 1 2 3 4 5 6 7 8

BC in mother

BC≤40 in mother

BC≤50 in mother

BC≤60 in mother

BC in siblings: ≥ 1 vs 0

OC in mother

OC60 in mother

OC in FDRs: ≥ 1 vs 0 *

HR with 95%CI

B. BRCA2 mutation carriers

Maternal origin BRCA2 and not havingthe indicated family history (reference)

Maternal origin BRCA2 and having theindicated family history

Paternal origin BRCA2 and not havingthe indicated family history

Paternal origin BRCA2 and having theindicated family history

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Sensitivity analysesIn the sensitivity analyses restricted to only registry-confirmed prevalent cases, as compared to the prevalent case analyses, the unadjusted effect of the paternal origin was 1.52 (-3%) in BRCA1 carriers and 1.44 (+2%) BRCA2 carriers (table 3). For the analyses including both registry-confirmed and self-reported prevalent cases, these numbers were 1.56 (-1%) in BRCA1 carriers and 1.28 (-8%) in BRCA2 carriers.

When the analyses adjusted for family history also included the reported number of FDRs and SDRs in addition to our already reported factors, adjustment for having any FDRs with breast cancer or having any (male) FDRs with any other cancer (not breast or ovarian) increased the effect of paternal origin of BRCA1 by 5% or more. Adjustment for having any female FDRs with any other cancer by age 60 increased the effect of paternal origin of BRCA2 by 5% or more.

When women with missing data were excluded, the impact of family factors on the paternal origin effect was slightly stronger than in the main analyses. For BRCA2 carriers, in addition to the already reported factors, adjustment for having any male FDRs with any cancer other than breast cancer reduced the paternal origin effect by 5%.

In our analyses we used family history at time of the questionnaire. We wondered if the family history at time of genetic testing would be more optimal for assessing referral bias, because this is the very family history that lead to the family’s ascertainment. Therefore these analyses were performed on a sub cohort of 550 (70%) BRCA1 carriers and 416 (79%) BRCA2 carriers for whom this data was available, but no differences with the other prevalent case analyses were observed (data not shown).

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Tabl

e 3.

The

una

djus

ted

effec

t of t

he p

aren

tal o

rigi

n of

the

BRCA

mut

atio

n (p

ater

nal v

s. m

ater

nal)

Brea

st c

ance

r eve

nts

Tim

e-de

pend

ent

effec

t

Prev

alen

t cas

e an

alys

esSe

mi-i

ncid

ent c

ase

anal

yses

aIn

cide

nt c

ase

anal

yses

b

Reg

istr

yco

nfirm

ed

Self

-rep

orte

dN

(e

vent

s)H

R (9

5%C

I)N

(e

vent

s)H

R (9

5%C

I)N

(eve

nts)

HR

(95%

CI)

Sele

cted

*A

ll

BRC

A1

pare

nt-o

f-or

igin

effe

ct: p

ater

nal v

s. m

ater

nal

xx

-78

8 (2

28)

1.54

(1.1

9-2.

00)

387

(46)

1.02

(0.5

6-1.

88)

272

(19)

0.66

(0.2

5-1.

71)

xx

RRSO

78

8 (2

55)

1.53

(1.2

1-1.

95)

387

(57)

1.23

(0.7

5-2.

03)

272

(27)

1.10

(0.5

9-2.

08)

x-

788

(216

)1.

53 (1

.18-

1.99

)38

7 (4

3)1.

17 (0

.63-

2.16

)27

2 (1

6)0.

77 (0

.29-

2.05

)

xx

-78

8 (2

37)

1.53

(1.1

9-1.

98)

386

(47)

0.98

(0.5

4-1.

79)

271

(19)

0.65

(0.2

5-1.

70)

BRC

A2

pare

nt-o

f-or

igin

effe

ct: p

ater

nal v

s. m

ater

nal

xx

-52

6 (1

10)

1.40

(0.9

6-2.

06)

321

(36)

0.94

(0.4

8-1.

85)

229

(15)

1.14

(0.4

2-3.

15)

xx

RRSO

52

6 (1

20)

1.41

(0.9

6-2.

04)

321

(41)

0.87

(0.4

5-1.

66)

229

(17)

0.90

(0.3

6-2.

23)

x-

526

(107

)1.

44 (0

.97-

2.14

)32

1 (3

5)0.

98 (0

.50-

1.94

)22

9 (1

5)1.

14 (0

.42-

3.15

)

xx

-52

6 (1

16)

1.28

(0.8

9-1.

86)

320

(38)

0.97

(0.5

2-1.

82)

229

(15)

1.14

(0.4

2-3.

15)

BC: b

reas

t can

cer

* Sel

ecte

d ca

ncer

s: s

elf-r

epor

ted

canc

er in

the

year

s ou

tsid

e th

e co

vera

ge o

f the

nat

iona

l can

cer r

egis

try

a In

cide

nt c

ases

: cas

es a

nd fo

llow

-up

time

afte

r per

sona

l DN

A te

st

b Se

mi i

ncid

ent c

ases

: cas

es a

nd fo

llow

-up

time

afte

r the

fam

ily’s

Inde

x ca

rrie

rs D

NA

test

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Discussion

The results of the prevalent case analyses show that paternal inheritance of a BRCA mutation increases the breast cancer risk for both BRCA1 carriers (HR = 1.54, 95%CI 1.19-2.00) and BRCA2 carriers (HR = 1.40, 95%CI 0.95-2.06). This risk increase was present irrespective of the referral criteria and family history of cancer since the fully adjusted HR for family history was 1.63 (95%CI 1.19-2.24) for BRCA1 carriers and 1.46 (95%CI 0.92-2.32) for BRCA2 carriers. However, no parent-of-origin effect was observed when referral bias by personal history of cancer was taken into account. These HRs were 0.66 (95%CI 0.25-1.71) and 1.14 (95%CI 0.42-3.15), respectively. An increase in breast cancer risk in case of a paternal origin of the mutation has been reported for BRCA1, but for BRCA2 mutations both non-significant risk-increasing and risk-decreasing trends have been published.7-9 For both genes we observed a risk increase due to paternal transmission of the mutation even when the effect was adjusted for possible referral bias by family history. We adjusted the risk ratios only for referral-bias-related factors (i.e. year of referral and family history of cancer in both FDRs and SDRs), while previous studies adjusted for the combination of date of birth and year of referral, and oral contraceptive use,7 or for the number of FDRs with breast cancer, breast cancer in the mother, breast feeding, age at menarche and country of residence.8 For BRCA1 carriers, these previously reported unadjusted risk ratios were 1.46 (p = 0.06) and 1.50 (p = 0.02), respectively, and, when adjusted, 1.36 (p = 0.19) and 1.53 (p = 0.02), respectively.7, 8 For BRCA2 carriers these risk ratios were 0.81 (p = 0.65) and 1.23 (p = 0.37), respectively, and, when adjusted, 0.88 (p = 0.82) and 1.21 (p = 0.41), respectively.7, 8 In our study we saw a risk-increasing effect of paternal BRCA2 transmission, but it was only statistically significant when adjusted for maternal breast cancer (HR = 1.62, p = 0.04) or breast cancer in siblings (HR = 1.49, p = 0.04).

Our study is the first to adjust the analyses for referral bias by incorporating a family history of cancer in both male and female FDRs and SDRs, including a history of cancer other than breast cancer. We show that having a family history of ovarian cancer in any FDRs and/or SDRs mitigates the paternal origin effect, while a family history of breast cancer increases this effect. Although data on the mutation position and mutation cluster regions was not available for our cohort, it is likely that the effect of the type of family history (ovarian cancer vs. breast cancer) is associated with the ovarian cancer cluster regions and breast cancer cluster regions.22-24 Mutations in these regions are associated with a relatively higher ratio of ovarian cancer to breast cancers and vice versa. The combination of the parent-of-origin effect and family history shows that information on maternal breast cancer status may be relevant even when the mutation is of paternal origin, as there might be an additive effect. This additive trend was not seen for maternal ovarian cancer, but this result should be interpreted with caution as only about 1% of the mutation-negative mothers were affected with ovarian cancer and an interaction effect might still be present. Sensitivity analyses showed similar results for the unadjusted analyses using only registry-confirmed cases

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and/or all self-reported breast cancer cases. Moreover, in the adjusted analyses similar results were found when missing family history was considered as missing instead of a negative family history.

In our study we also addressed the impact of referral bias by a personal history of cancer. More mutation carriers with a paternal mutation origin were affected by the time of ascertainment of the family and by the time of their personal DNA test as compared to mutation carriers with a maternal origin of the mutation, especially for BRCA1, which might suggest referral bias and genetic testing bias. When this was taken into account in the semi-incident and incident case analyses, no parent-of-origin effect could be observed anymore, although numbers were small and results uncertain.

For this study we used a well-structured national cohort, and breast cancers were confirmed by linkage with the national cancer registry when possible. Only the impact of the parent-of-origin on breast cancer was assessed because the number of ovarian cancer cases was too small for risk assessment. A minor limitation is that the family history and risk-reducing surgeries were self-reported, but studies have shown that individuals report their family history of breast cancer quite accurately for FDRs and fairly accurately for SDRs.25-27 The self-reported family history of ovarian cancer is less accurate, especially in SDRs. However, results adjusted for SDR history were in line with what was expected based on the results of the FDR history. As mutation carriers can opt for risk reducing surgeries, family history might become, over time, a less valid expression of the underlying carcinogenic environmental and genetic factors. This is not yet expected for the current cohort, and the results adjusted for family history at the time of genetic testing or at the time of the follow-up questionnaire were similar. Information on the parental origin of the BRCA mutation and on second-degree family history was not available for the complete cohort. However, comparison of the selected study population with the complete cohort showed that our study population was a representative sample including a somewhat younger cohort with more risk-reducing surgeries and fewer cancers.

Both retrospective and prospective cohort studies can be used to assess risk factors, but biases should be addressed carefully in both study designs, as there will always be some form of selection of the study population. In this study, the referral bias by family history was assessed by excluding the index cases and accounting for possible confounding by family history. However, our risk factor of interest, parent-of-origin, seems to be related to referral bias due to personal history of cancer, and this could not be disentangled with retrospective analyses alone. Therefore, the impact of referral bias due to family history of cancer on the parent-of-origin effect was assessed in a retrospective cohort, while the referral bias due to a personal history of cancer could only be addressed prospectively without any further adjustment for family history due to small numbers. Although the results from our epidemiologic study make the parent-of-origin effect seem less likely, research on the possible biological mechanisms underlying this effect may help to resolve the issue.

In conclusion, the existence of a parent-of-origin effect depends on how researchers correct for referral bias. Correction of referral bias as defined by family history did not substantially impact this effect, while bias correction for the personal cancer history made the parent-of-origin effect disappear. This bias, when uncorrected, may

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have produced the positive association seen between paternal origin of the BRCA1/2 mutation and risk of breast cancer in earlier studies. In a larger prospective cohort, the impact of referral bias by a combined assessment of family and personal history should be addressed.

AcknowledgmentsHEBON thanks the registration teams of IKNL and PALGA for part of the data collection. The authors thank Kate Mc Intyre for editorial help.

CollaboratorsThe Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) consists of the following Collaborating Centers: Coordinating center: Netherlands Cancer Institute, Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, F.E. van Leeuwen, S. Verhoef, M.K. Schmidt, N.S. Russell, J.L. de Lange, R. Wijnands; Erasmus Medical Center, Rotterdam, NL: J.M. Collée, A.M.W. van den Ouweland, M.J. Hooning, C. Seynaeve, C.H.M. van Deurzen, I.M. Obdeijn; Leiden University Medical Center, NL: C.J. van Asperen, J.T. Wijnen, R.A.E.M. Tollenaar, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Center, NL: C.M. Kets, A.R. Mensenkamp; University Medical Center Utrecht, NL: M.G.E.M. Ausems, R.B. van der Luijt, C.C. van der Pol; Amsterdam Medical Center, NL: C.M. Aalfs, T.A.M. van Os; VU University Medical Center, Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital Maastricht, NL: E.B. Gómez-Garcia, M.J. Blok; University Medical Center Groningen, NL: J.C. Oosterwijk, A.H. van der Hout, M.J. Mourits, G.H. de Bock; The Netherlands Foundation for the detection of hereditary tumours, Leiden, NL: H.F. Vasen; The Netherlands Comprehensive Cancer Organization (IKNL): S. Siesling, J.Verloop; The nationwide network and registry of histo- and cytopathology in The Netherlands (PALGA): L.I.H. Overbeek.

FundingThe HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI2007-3756, the Netherlands Organization of Scientific Research grant NWO 91109024, the Pink Ribbon grants 110005 and 2014-187.WO76, the BBMRI grant NWO 184.021.007/CP46 and the Transcan grant JTC 2012 Cancer 12-054.

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Supp

lem

enta

ry T

able

1. P

erso

nal a

nd fa

mily

his

tory

at i

nitia

l ref

erra

l of t

he fa

mily

and

per

sona

l DN

A te

st.

Pers

onal

bre

ast o

r ova

rian

can

cer

and

fam

ily h

isto

ry o

f any

ca

ncer

..

..at t

ime

of D

NA

test

inde

x ca

se..a

t tim

e of

per

sona

l DN

A te

stBR

CA

1 (N

=507

)BR

CA

2 (N

=378

)BR

CA

1 (N

=507

)BR

CA

2 (N

=378

)Pa

tern

alN

=208

Mat

erna

lN

=299

Pate

rnal

N=1

73M

ater

nal

N=2

05Pa

tern

alN

=208

Mat

erna

lN

=299

Pate

rnal

N=1

73M

ater

nal

N=2

05

Car

rier

Pare

nt(s

)kid(

s)/

sib(

s)SD

R(s

)N

(Col

%)

N (C

ol %

)N

(Col

%)

N(C

ol %

)N

(Col

%)

N(C

ol %

)N

(Col

%

)N

(Col

%)

No

BC/O

C

No

No

No

189%

103%

1810

%12

6%16

8%8

3%14

8%8

4%Ye

s81

39%

6823

%66

38%

4321

%75

36%

4916

%58

34%

3517

%

Yes

No

31%

21%

63%

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References

1 de Bock G. H., Jacobi C.E., Seynaeve C., Krol-Warmerdam E.M., Blom J., van Asperen C.J., Cornelisse C.J., Klijn J.G., Devilee P., Tollenaar R.A., et al. (2008). A family history of breast cancer will not predict female early onset breast cancer in a population-based setting. BMC Cancer 8, 203.

2 Lee A. J., Cunningham A.P., Kuchenbaecker K.B., Mavaddat N., Easton D.F., Antoniou A.C., Consortium of Investigators of Modifiers of BRCA1/2 and Breast Cancer Association Consortium (2014). BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br. J. Cancer 110, 535-545.

3 Amir E., Freedman O.C., Seruga B. and Evans D.G. (2010). Assessing women at high risk of breast cancer: a review of risk assessment models. J. Natl. Cancer Inst. 102, 680-691.

4 Evans D. G., Lalloo F., Wallace A. and Rahman N. (2005). Update on the Manchester Scoring System for BRCA1 and BRCA2 testing. J. Med. Genet. 42, e39.

5 Metcalfe K., Lynch H.T., Ghadirian P., Tung N., Kim-Sing C., Olopade O.I., Domchek S., Eisen A., Foulkes W.D., Rosen B., et al. (2011). Risk of ipsilateral breast cancer in BRCA1 and BRCA2 mutation carriers. Breast Cancer Res. Treat. 127, 287-296.

6 Panchal S., Bordeleau L., Poll A., Llacuachaqui M., Shachar O., Ainsworth P., Armel S., Eisen A., Sun P. and Narod S.A. (2010). Does family history predict the age at onset of new breast cancers in BRCA1 and BRCA2 mutation-positive families? Clin. Genet. 77, 273-279.

7 Ellberg C., Jernstrom H., Broberg P., Borg A. and Olsson H. (2015). Impact of a paternal origin of germline BRCA1/2 mutations on the age at breast and ovarian cancer diagnosis in a Southern Swedish cohort. Genes Chromosomes Cancer 54, 39-50.

8 Senst N., Llacuachaqui M., Lubinski J., Lynch H., Armel S., Neuhausen S., Ghadirian P., Sun P., Narod S.A. and Hereditary Breast Cancer Study Group (2013). Parental origin of mutation and the risk of breast cancer in a prospective study of women with a BRCA1 or BRCA2 mutation. Clin. Genet. 84, 43-46.

9 Bernholtz S., Laitman Y., Kaufman B., Paluch Shimon S. and Friedman E. (2011). Cancer risk in Jewish BRCA1 and BRCA2 mutation carriers:

effects of oral contraceptive use and parental origin of mutation. Breast Cancer Res. Treat. 129, 557-563.

10 Fostira F., Tsoukalas N., Konstantopoulou I., Georgoulias V., Christophyllakis C. and Yannoukakos D. (2014). A Paternally Inherited BRCA1 Mutation Associated with an Unusual Aggressive Clinical Phenotype. Case Rep. Genet. 2014, 875029.

11 Oosterwijk J. C., de Vries J., Mourits M.J. and de Bock G.H. (2014). Genetic testing and familial implications in breast-ovarian cancer families. Maturitas 78, 252-257.

12 Weinberg C. R., Shi M., DeRoo L.A., Taylor J.A., Sandler D.P. and Umbach D.M. (2014). Asymmetry in family history implicates nonstandard genetic mechanisms: application to the genetics of breast cancer. PLoS Genet. 10, e1004174.

13 Cheung E. L., Olson A.D., Yu T.M., Han P.Z. and Beattie M.S. (2010). Communication of BRCA results and family testing in 1,103 high-risk women. Cancer Epidemiol. Biomarkers Prev. 19, 2211-2219.

14 Koehly L. M., Peters J.A., Kenen R., Hoskins L.M., Ersig A.L., Kuhn N.R., Loud J.T. and Greene M.H. (2009). Characteristics of health information gatherers, disseminators, and blockers within families at risk of hereditary cancer: implications for family health communication interventions. Am. J. Public Health 99, 2203-2209.

15 Couto E. and Hemminki K. (2007). Estimates of heritable and environmental components of familial breast cancer using family history information. Br. J. Cancer 96, 1740-1742.

16 Patenaude A. F., Dorval M., DiGianni L.S., Schneider K.A., Chittenden A. and Garber J.E. (2006). Sharing BRCA1/2 test results with first-degree relatives: factors predicting who women tell. J. Clin. Oncol. 24, 700-706.

17 R Core Team. R Foundation for Statistical Computing (2013) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.

18 Rebbeck T. R., Mitra N., Wan F., Sinilnikova O.M., Healey S., McGuffog L., Mazoyer S., Chenevix-Trench G., Easton D.F., Antoniou A.C., et al. (2015). Association of type and location of BRCA1 and BRCA2 mutations with

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risk of breast and ovarian cancer. JAMA 313, 1347-1361.

19 Thompson D. and Easton D. (2001). Variation in cancer risks, by mutation position, in BRCA2 mutation carriers. Am. J. Hum. Genet. 68, 410-419.

20 Thompson D., Easton D. and Breast Cancer Linkage Consortium (2002). Variation in BRCA1 cancer risks by mutation position. Cancer Epidemiol. Biomarkers Prev. 11, 329-336.

21 Murff H. J., Spigel D.R. and Syngal S. (2004). Does this patient have a family history of cancer? An evidence-based analysis of the accuracy of family cancer history. JAMA 292, 1480-1489.

22 Sijmons R. H., Boonstra A.E., Reefhuis J., Hordijk-Hos J.M., de Walle H.E., Oosterwijk J.C. and Cornel M.C. (2000). Accuracy of family history of cancer: clinical genetic implications. Eur. J. Hum. Genet. 8, 181-186.

23 Tehranifar P., Wu H.C., Shriver T., Cloud A.J. and Terry M.B. (2015). Validation of family cancer history data in high-risk families: the influence of cancer site, ethnicity, kinship degree, and multiple family reporters. Am. J. Epidemiol. 181, 204-212.

24 Michailidou K., Hall P., Gonzalez-Neira A., Ghoussaini M., Dennis J., Milne R.L., Schmidt M.K., Chang-Claude J., Bojesen S.E., Bolla M.K., et al. (2013). Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat. Genet. 45, 353-61, 361e1-2.

25 Kong A., Steinthorsdottir V., Masson G., Thorleifsson G., Sulem P., Besenbacher S., Jonasdottir A., Sigurdsson A., Kristinsson K.T., Jonasdottir A., et al. (2009). Parental origin of sequence variants associated with complex diseases. Nature 462, 868-874.

26 Antoniou A. C., Beesley J., McGuffog L., Sinilnikova O.M., Healey S., Neuhausen S.L., Ding Y.C., Rebbeck T.R., Weitzel J.N., Lynch H.T., et al. (2010). Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction. Cancer Res. 70, 9742-9754.

27 Perry J. R., Day F., Elks C.E., Sulem P., Thompson D.J., Ferreira T., He C., Chasman D.I., Esko T., Thorleifsson G., et al. (2014). Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92-97.

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Chapter 7Relevance and effi cacy of breast cancer screening in

BRCA1 and BRCA2 mutation carriers above 60 years: A national cohort study

Sepideh Saadatmand Janet R. Vos

Maartje J. Hooning Jan C. Oosterwijk

Linett a B. Koppert Geertruida H. de Bock

Margreet G. Ausems Christi J. van Asperen

Cora M. Aalfs Encarna B. Gómez Garcia

Hanne Meijers-Heijboer Nicoline Hoogerbrugge

Marianne Piek Caroline Seynaeve

Cornelis Verhoef Matt i Rookus

Madeleine M. Tilanus-Linthorst Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON)

International Journal of Cancer 2014; 135(12): 2940-9

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Abstract

BackgroundAnnual MRI and mammography is recommended for BRCA1/2 mutation carriers to reduce breast cancer mortality. Less intensive screening is advised ≥60 years, although effectiveness is unknown.

MethodsWe identified BRCA1/2 mutation carriers without bilateral mastectomy before age 60 to determine for whom screening ≥60 is relevant, in the Rotterdam Family Cancer Clinic and HEBON: a nationwide prospective cohort study. Furthermore, we compared tumour stage at breast cancer diagnosis between different screening strategies in BRCA1/2 mutation carriers ≥60. Tumours >2 cm, positive lymph nodes, or distant metastases at detection were defined as “unfavourable.”

ResultsOf 548 BRCA1/2 mutation carriers ≥60 years in 2012, 395 (72%) did not have bilateral mastectomy before the age of 60. Of these 395, 224 (57%) had a history of breast or other invasive carcinoma. In 136 BRCA1/2 mutation carriers, we compared 148 breast cancers (including interval cancers) detected ≥60, of which 84 (57%) were first breast cancers. With biennial mammography 53% (30/57) of carcinomas were detected in unfavourable stage, compared to 21% (12/56) with annual mammography (adjusted odds ratio: 4.07, 95% confidence interval [1.79-9.28], p = 0.001). With biennial screening 40% of breast cancers were interval cancers, compared to 20% with annual screening (p = 0.016). Results remained significant for BRCA1 and BRCA2 mutation carriers, and first breast cancers separately.

ConclusionOver 70% of 60-year old BRCA1/2 mutation carriers remain at risk for breast cancer, of which half has prior cancers. When life expectancy is good, continuation of annual breast cancer screening of BRCA1/2 mutation carriers ≥60 is worthwhile.

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Breast cancer screening in BRCA1 and BRCA2 mutation carriers above 60 years

Introduction

The cloning of the BRCA1 1 and BRCA2 2 genes in 1994 made it possible to identify women with a germ-line mutation in these genes, who have a cumulative risk for breast cancer of 43 to 75% by age 70.3-5

Without preventive intervention, survival probability by age 80 for BRCA1 and BRCA2 mutation carriers is estimated 33 to 52%, in comparison to 66% in the United States (U.S.) general female population.6 The two main strategies to reduce breast cancer mortality are prevention of breast cancer through risk-reducing mastectomy or optimizing survival chances by early detection through breast screening with annual magnetic resonance imaging (MRI) and mammography.7-9 Both strategies offer comparable improved survival in modelling studies,6 and in most countries the majority of mutation carriers opt for screening.10,11

In most international guidelines screening with annual clinical breast examination, MRI, and mammography is advised for BRCA1/2 mutation carriers until the age of 50.7-9,12,13 Above the age of 50 guidelines differ. The recently updated British NICE guideline recommends extending the period of annual mammography screening until 69 years, and considering continuing MRI screening for women older than 50 with dense breasts.12 From the age of 60 (≥60) Dutch guidelines advise screening with only biennial mammography.13,14 American guidelines advice annual screening with MRI and mammography without an upper age limit.7,9

There are several reasons why a less intensive screening protocol may not be adequate for BRCA1/2 mutation carriers ≥60 years. First of all, breast cancer incidence remains high in mutation carriers ≥60.4,5,15 Secondly, there is no evidence that screening with mammography alone is effective for BRCA1/2 mutation carriers ≥60.16 In the Dutch prospective MRISC cohort screening study BRCA1/2 mutation carriers and women with familial risk for breast cancer aged 25 to 70 years were screened with annual mammography and MRI. Sensitivity of mammography was just 25% for BRCA1 mutation carriers and 62% for BRCA2 mutation carriers, whilst MRI sensitivity was approximately 68%.17 Since only few BRCA1/2 mutation carriers ≥60 have participated in the large prospective screening trials17-19 no sensitivity analyses have been performed for this subgroup specifically. Finally, it is questionable if reducing screening frequency is optimal for BRCA1/2 mutation carriers ≥60 as their tumours grow twice as fast as tumours of age-matched non-carriers.20 The growth rate of a carcinoma of a 60-year-old BRCA1/2 mutation carrier is comparable to that of a 37-year-old non-carrier.20

To address the clinical relevance and extent of this issue, we first assess the proportion of BRCA1/2 mutation carriers with remaining breast tissue at risk at age 60, in an on-going nationwide cohort study and a family cancer clinic cohort. Secondly, to determine the optimal breast cancer screening strategy for BRCA1/2 mutation carriers ≥60, we compared tumour stage at detection per screening strategy.

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Methods

BRCA1/2 mutation carriers with breast tissue at risk at age 60We assessed the proportion of BRCA1/2 mutation carriers who were at risk of breast cancer at age 60, i.e. did not have bilateral therapeutic or risk-reducing mastectomy performed before age 60. In addition, in the women with remaining breast tissue present at age 60, we evaluated the proportion of women with a history of invasive carcinoma, other than non-melanoma skin cancer, since relevance of screening also depends on a woman’s life expectancy. We selected all female BRCA1/2 mutation carriers aged 60 years or older in 2012,i.e. born before January 1, 1953, from the prospective cohorts with follow-up of the Family Cancer Clinic of the Erasmus University Medical Centre, Cancer Institute, Rotterdam (“Rotterdam”) and the Netherlands Collaborative Group on Hereditary Breast Cancer (HEBON)21 a nationwide cohort study of women tested for BRCA1/2 mutations in the Netherlands. Patients included in both cohorts were identified, and registered in the “Rotterdam” cohort only. Informed consent was obtained from all patients, prior to inclusion in these databases. Women were selected irrespective of their prior cancer status. Women who died before reaching the age of 60 were excluded.

Ethics committeeThe research protocol of the “Rotterdam” cohort was approved by the institutional board of the Erasmus Medical Centre, Rotterdam and the HEBON study was approved by the Institutional Review Board of all participating centres. All participants of “Rotterdam” and HEBON provided written informed consent.

Assessment of the optimal screening strategyTo evaluate the optimal screening strategy for BRCA1/2 mutation carriers ≥60, we conducted a case-case study, comparing tumour stage at breast cancer detection (including ductal carcinoma in situ; DCIS) in women ≥60 between screening strategies (biennial mammography, annual mammography). Breast cancer cases were selected from the “Rotterdam” and HEBON cohorts and from the department of Clinical Genetics of the University Medical Centre Groningen (“Groningen”), updated until September 20115 and entered into an anonymised database (Supporting Information Fig. 1). All first breast cancers, contralateral breast cancers and second primary ipsilateral breast cancers detected above 60 years were included. Second primary ipsilateral breast cancer was distinguished from breast cancer recurrence by the multidisciplinary team of the treating hospital based on differences in tumour characteristics and/or localization between the first and second breast cancer. Tumours >2 cm, with positive lymph nodes, or with distant metastases at detection were defined as ‘unfavourable’. Women with missing data on screening method or tumour stage were excluded from analysis.

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Data collectionTo answer the two research questions breast cancer characteristics were extracted from the three databases or from additional medical files in case of missing data. Medical files from the hospitals and the National Breast Cancer Screening Program were searched. The following data were collected: age at diagnosis, mode of detection, lateralization, tumour size, nodal status, histological type and grade, oestrogen receptor status, progesterone receptor status and Her2Neu status. Furthermore, data on prior cancer status, therapeutic or prophylactic breast surgery, and of method and frequency of breast cancer screening were gathered.

Statistical analysisContinuous data were presented as median (range). To evaluate the optimal screening strategy for BRCA1/2 mutation carriers ≥60 differences between different screening strategies were analysed. Differences in discrete outcomes were analysed using Pearson χ2 tests or Fisher’s exact tests, as appropriate, differences in median age at diagnosis of breast cancer were assessed with the Mann-Whitney Utest. Data analyses were stratified for BRCA1 mutation carriers and BRCA2 mutation carriers, and for first breast cancer (yes or no). The association of frequency of mammography screening with tumour stage (favourable/unfavourable) was estimated by multivariable backwards logistic regression models with adjustment for all possible clinical relevant factors known in our dataset: period of diagnosis (<2005 or >2005; after 2005 generally digital mammography was used in the Netherlands), mutation status (BRCA1 or BRCA2), first breast cancer (yes or no), and age at detection of breast cancer. Odds ratios (OR) for unfavourable tumour stage were computed and presented with 95% confidence intervals (CI). We started with the most extensive logistic regression model, including all possible confounders, using a backward stepwise approach to remove all variables that were shown to have a non-significant contribution to the model by the likelihood-ratio test. A two-sided p-value of 0.05 or less was considered statistically significant. Missing values were excluded from analyses. Statistical analyses were performed using SPSS Statistics for Windows, version 20.0 (IBM Corp, Armonk, NY).

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Results

BRCA1/2 ≥60 with breast tissue at riskWe identified 588 BRCA1/2 mutation carriers born before 1953. Forty (7%) patients died before reaching the age of 60 and were excluded from analyses. Of the remaining 548 BRCA1/2 mutation carriers, 264 patients were from “Rotterdam,” and an additional 284 patients from HEBON.

There were 413 patients with a BRCA1 mutation, 133 with a BRCA2 mutation, and two with both a BRCA1 and a BRCA2 mutation. Table 1 gives the distribution of BRCA1 and BRCA2 mutation carriers and information on breast tissue present in the “Rotterdam” and HEBON cohorts. In our total dataset 395/548 (72%) had one or both breasts present at age 60. Among these 395 women with breast tissue present, 171 (43%) women had no history of breast cancer or other invasive carcinoma (non-melanoma skin cancer excluded), 144 (37%) had a history of breast cancer (including DCIS), 47 (12%) had a history of another type of cancer, and 33 (8%) women had a history of breast cancer as well as another type of cancer (Fig. 1).

Table 1. BRCA1 and BRCA2 gene mutation carriers; information on breast tissue present at age 60 and history of cancer

Breast tissue present (%) “Rotterdam” HEBON only TotalBRCA1 Bilateral 100 (52%) 120 (55%) 220 (53%)

Unilateral 39 (20%) 36 (16%) 75 (18%) None 54 (28%) 64 (29%) 118 (29%) Total 193 (100%) 220 (100%) 413 (100%)

BRCA2 Bilateral 44 (62%) 31 (50%) 75 (56%) Unilateral 12 (17%) 12 (19%) 24 (18%) None 15 (21%) 19 (31%) 34 (26%) Total 71 (100%) 62 (100%) 133(100%)

Total1 Bilateral 144 (55%) 151 (53%) 295 (54%) Unilateral 51 (19%) 49 (17%) 100 (18%) None 69 (26%) 84 (30%) 153 (28%) Total 264 (100%) 284 (100%) 548 (100%)

1Two HEBON patients included with gene mutations in both BRCA1 and BRCA2. Abbreviations: BRCA1 = BRCA1 gene mutation carrier, BRCA2 = BRCA2 gene mutation carrier, HEBON = prospective cohort of the Netherlands Collaborative Group on Hereditary Breast Cancer, “Rotterdam”= prospective cohort of Erasmus University Medical Centre, Rotterdam, % = per cent.

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Figure 1. BRCA1 and BRCA2 gene mutation carriers; proportion with breast tissue present at age 60 and history of cancer.

Supplementary Figure 1. Relevance and effi cacy of breast cancer screening in BRCA1/2 ≥60; aims, methods and datasets usedAbbreviations: BRCA1/2= BRCA1 and BRCA2 gene mutation carriers, HEBON= the Netherlands Collaborative Group on Hereditary Breast Cancer, “Rott erdam”=Erasmus University Medical Centre, Cancer Institute, Rott erdam, the Netherlands, “Groningen”=the department of Clinical Genetics of the University Medical Centre Groningen, the Netherlands.

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Differences in tumour stage per screening modalityThe HEBON, “Rotterdam” and “Groningen” series of BRCA1/2 mutation carriers included 154 breast cancers detected in patients aged 60 years or older. Six were excluded due to missing screening data. The 148 remaining breast cancers were detected in 86 BRCA1 mutation carriers, 50 BRCA2 mutation carriers and one BRCA1 & BRCA2 mutation carrier. Of these tumours 15 (10%) were second primary ipsilateral carcinomas, 49 (33%) were primary contralateral breast cancers, and 84 (57%) were first breast cancers. Further tumour characteristics and method of screening per mutation type (BRCA1 or BRCA2) are depicted in Table 2.

In Table 3 the characteristics of BRCA1/2-associated breast cancers diagnosed ≥60 with either biennial or annual mammography screening are compared. Of the 113 breast cancers detected ≥60 while being screened with mammography, 64 (57%) were first breast cancers. For BRCA1/2 mutation carriers screening with biennial mammography detected 53% (30/57) of tumours in an unfavourable stageversus 21% (12/56) with annual mammography (OR: 4.07, 95% CI [1.79–9.3], p = 0.001). Also when analysing first breast cancers separately this percentage was 53% (24/45) versus 21% (4/19) respectively (OR: 4.29, 95% CI [1.23–14.94], p = 0.017). This statistically significant difference was also seen for BRCA1 mutation carriers separately; biennial screening detected 57% of all breast cancers in unfavourable stage versus 24% with annual mammography (OR: 4.19, 95% CI [1.5–11.5], p = 0.005), and for BRCA2 mutation carriers separately; biennial screening detected 50% of tumours in an unfavourable stage compared to annual screening 14% (OR: 6.00, 95% CI [1.11–32.3], p = 0.026). In the overall biennial mammography group 40% (23/57) of tumours detected were interval cancers, compared to 20% (11/56) in the annual mammography group (p = 0.016). In the overall biennial mammography group 74% (17/23) of interval cancers was detected in unfavourable stage, versus 36% (4/11) in the annual mammography group (p = 0.060).

In univariable logistic regression models mammographic screening frequency (annual or biennial) was the only significant variable influencing tumour stage at detection (favourable/unfavourable) (Table 4). In multivariable backwards logistic regression, after adjustment for period of diagnosis (before 2005 or after 2005), mutation status (BRCA1 or BRCA2), first breast cancer (yes or no), and age at detection of breast cancer, mammography screening frequency remained the only significant variable (OR: 4.07, 95% CI [1.79–9.3], p = 0.001) influencing tumour stage at detection. Therefore, results of univariable and multivariable logistic regression with backward stepwise approach were equal for mammography screening frequency.

Screening with annual MRI and mammography detected 2 of 11 (18%) breast cancers in an unfavourable stage. Fourteen of 22 (64%) breast cancers were detected in an unfavourable stage, when women were not screened at all. Since so few BRCA1/2 mutation carriers ≥60 were screened with annual MRI and mammography, or not screened at all, no comparative analyses were performed for these groups.

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Table 2. Tumour characteristics and mode of screening of BRCA1/2-associated breast cancers diagnosed ≥60

BRCA1 BRCA2 Overall1 pNo. patients 86 50 136No. diagnosed breast cancers 92 55 147 0.985First breast cancer 52 (57%) 31 (56%) 83 (57%)Second breast cancer (ipsilateral and contralateral) 40 (44%) 24 (44%) 64 (44%)Median age at diagnosis in years (range) 64 (60–81) 65 (60–79) 64 (60–81) 0.487Year of diagnosis 0.055

Detected < 2005 47 (51%) 37 (67%) 84 (57%)Detected ≥ 2005 45 (49%) 18 (33%) 63 (43%)

Screening at time of detection2 0.008No screening 9 (10%) 13 (24%) 22 (15%)Biennial mammography 30 (33%) 26 (47%) 56 (39%)Annual mammography 42 (47%) 14 (25%) 56 (39%)Annual mammography and MRI 9 (10%) 2 (4%) 11 (7%)

Detection 0.069Interval carcinoma 21 (23%) 12 (22%) 33 (22%)Screen-detected 62 (67%) 30 (54%) 92 (63%)No screening 9 (10%) 13 (24%) 22 (15%)

Stage 0.423Favourable (T1 & N-& M-) 58 (63%) 31 (56%) 89 (60%)Unfavourable 34 (37%) 24 (44%) 58 (40%)

Tumour size3 0.225Tis/T1a/T1b (tumour ≤ 10 mm)4 32 (36%) 12 (22%) 44 (31%)T1c (tumour 11–20 mm) 33 (37%) 24 (44%) 57 (40%)T2+ (tumour >20 mm) 24 (27%) 18 (33%) 42 (29%)

Tumour characteristics of invasive cancers5

Nodal status 0.359N-/isolated cells 68 (77%) 38 (70%) 106 (75%)N+/micro metastasis (0.2–2.0 mm) 20 (23%) 16 (30%) 36 (25%)

Histological subtype 0.234Ductal cancer 78 (89%) 44 (82%) 122 (86%)Other 10 (11%) 10 (18%) 20 (14%)

Bloom and Richardson Grade 0.092Grade 1/2 22 (29%) 20 (44%) 42 (34%)Grade 3 55 (71%) 26 (57%) 81 (66%)

Oestrogen status <0.001Positive 28 (36%) 35 (76%) 63 (51%)Negative 50 (64%) 11 (24%) 61 (49%)

Progesterone status 0.052Positive 20 (27%) 19 (44%) 39 (33%)Negative 55 (73%) 24 (56%) 79 (67%)

Her 2 Neu status 0.978Overexpression 4 (9%) 2 (9%) 6 (9%)No overexpression 41 (91%) 20 (91%) 61 (91%)

1 Data of the one breast cancer in a patient with both BRCA1 and BRCA2 gene mutation are not shown 2 Two patients were screened according to a different protocol, not included in analyses.3 Size of four breast cancers unknown (three axillary cancers, primary breast cancer undetected).4 Five Tis, four in the BRCA1 gene mutation group, one in the BRCA2 gene mutation group.5 Missing data not shown.Two-sided p-value for difference between two risk groups; all differences were obtained from χ2 test or Fisher’s exact tests, as appropriate, except for differences in median age which were computed using the Mann-Whitney U test. All statistical tests were two-sided.Abbreviations: BRCA1 = BRCA1 gene mutation carrier, BRCA2 = BRCA2 gene mutation carrier, Her2 = human epidermal growth factor 2, N− = node negative, N+ = Node positive, % = per cent.

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Table 3. Characteristics of BRCA1/2–associated breast cancers diagnosed ≥60 per screening strategy1

Biennial Mx Annual Mx Overall p No. patients 56 49 105 Number of diagnosed breast cancers 57 56 113 <0.001 First breast cancer 45 (79%) 19 (34%) 64 (57%) Second breast cancer 12 (21%) 37 (66%) 49 (43%) Median age at diagnosis in years (range) 63 (60–75) 64 (60–77) 64 (60–77) 0.428 Year of diagnosis 0.220

Detected < 2005 37 (65%) 30 (54%) 67 (60%) Detected ≥ 2005 20 (35%) 26 (46%) 46 (40%)

Detection 0.016 Interval 23 (40%) 11 (20%) 34 (30%) Screen-detected 34 (60%) 45 (80%) 79 (70%)

BRCA1/BRCA21

Stage 0.001 Favourable (≤T1 & N-& M-) 27 (47%) 44 (79%) 71 (63%) Unfavourable 30 (53%) 12 (21%) 42 (37%)

Tumour size2 0.001 Tis/T1a/T1b (tumour ≤ 10 mm)3 9 (16%) 21 (39%) 30 (27%) T1c (tumour 11–20 mm) 24 (43%) 26 (48%) 50 (46%) T2+ (tumour >20 mm) 23 (41%) 7 (13%) 30 (27%)

Nodal status4 0.005 N-/isolated cells 36 (64%) 48 (87%) 84 (76%) N+/micro metastasis (0.2–2.0 mm) 20 (36%) 7 (13%) 27 (24%)

BRCA1 Detection 0.087

Interval 12 (40%) 9 (21%) 21 (29%) Screen-detected 18 (60%) 33 (79%) 51 (71%)

Stage 0.005 Favourable (T1 & N-& M-) 13 (43%) 32 (76%) 45 (63%) Unfavourable 17 (57%) 10 (24%) 27 (38%)

Tumour size2 0.004 Tis/T1a/T1b (tumour ≤ 10 mm) 6 (20%) 16 (40%) 22 (32%) T1c (tumour 11–20 mm) 9 (31%) 19 (48%) 28 (40%) T2+ (tumour >20 mm) 14 (48%) 5 (13%) 19 (28%)

Nodal status3 0.045 N-/isolated cells 19 (66%) 36 (86%) 55 (76%) N+/micro metastasis (0.2–2.0 mm) 10 (35%) 6 (14%) 16 (23%)

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Biennial Mx Annual Mx Overall p BRCA2 Detection 0.157

Interval 10 (39%) 2 (14%) 12 (30%) Screen-detected 16 (62%) 12 (86%) 28 (70%)

Stage 0.026 Favourable (T1 & N-& M-) 13 (50%) 12 (86%) 25 (63%) Unfavourable 13 (50%) 2 (14%) 15 (38%)

Tumour size5 Tis/T1a/T1b (tumour ≤ 10 mm) 3 (12%) 5 (36%) 8 (20%) T1c (tumour 11–20 mm) 14 (54%) 7 (50%) 21 (53%) T2+ (tumour >20 mm) 9 (35%) 2 (14%) 11 (28%)

Nodal status 0.063N-/isolated cells 16 (62%) 12 (92%) 28 (72%) N+/micro metastasis (0.2–2.0 mm) 10 (39%) 1 (8%) 11 (28%)

First breast cancers Stage 0.017

Favourable (T1 & N-& M-) 21 (47%) 15 (79%) 36 (56%) Unfavourable 24 (53%) 4 (21%) 28 (44%)

Second breast cancers Stage 0.059

Favourable (T1 & N-& M-) 6 (50%) 29 (78%) 35 (71%) Unfavourable 6 (50%) 8 (22%) 14 (29%)

1 Including one breast cancer found in a patient with a BRCA1 and BRCA2 gene mutation.2 Size unknown for three breast cancers (two axillary cancers, primary breast cancer undetected).3 Only one Tis per screening group.4 Only invasive cancers included in analysis (one DCIS excluded).5 Numbers too small for χ2 test, more than 20% of expected frequencies less than 5.Two-sided p value for difference between two risk groups; all differences were obtained from χ2 test or Fisher’s exact tests, as appropriate, except for differences in median age which were computed using the Mann-Whitney U test. All statistical tests were two-sided.Abbreviations: BRCA1 = BRCA1 gene mutation carrier, BRCA2 = BRCA2 gene mutation carrier, Her2 = human epidermal growth factor 2, N− = node negative, N+ = Node positive, % = per cent

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Table 4. Odds ratios for unfavourable tumour stage with factors in BRCA1/2-associated breast cancers diagnosed above 60 years1

Variable investigated Univariable OR (95% CI) p Multivariable

OR (95% CI)2p 2

Screening frequency 0.001 0.001Annual 1.00 1.00Biennial 4.07 (1.79–9.28) 4.07 (1.79–9.28)

First breast cancer 0.100Yes 1.00No 0.51 (0.23–1.14)

Period of diagnosis 0.407After 2005 1.00Before 2005 1.40 (0.64–3.06)

Type of mutation 1 1.000BRCA2 1.00BRCA1 1.00 (0.45–2.22)

Age at diagnosis 0.98 (0.90–1.07) 0.6141Excluding one breast cancer found in a patient with a BRCA1 and BRCA2 gene mutation. 2Multivariable OR only shown for factors with a significant contribution to the model. Univariable regression analysis and multivariable logistic regression analyses with backward stepwise approach for unfavourable tumour stage. The most extensive logistic regression model including all possible confounders was the starting model. Using a backward stepwise approach all variables that were shown to have a non-significant contribution to the model by the likelihood-ratio test were removed.

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Discussion

This is the first study assessing relevance and optimal strategy of breast cancer screening in BRCA1/2 mutation carriers ≥60. Our results, based on data derived from a prospective nationwide cohort study and a large family cancer clinic suggest that more than 70% of BRCA1/2 mutation carriers still have breast tissue (one or both breasts) present at age 60 and are therefore at risk for breast cancer. An unacceptably high percentage of breast cancers (53%) were detected in unfavourable stage with biennial vs. 21% with annual mammography. Continuing screening annually is therefore advisable.

Some explanations for the large proportion of BRCA1/2 mutation carriers at risk for breast at age 60 in our study are: approximately 60% of BRCA1/2 mutation carriers opt for screening over risk-reducing bilateral mastectomy in The Netherlands,22 and in case of malignancy, breast conserving therapy is considered equally safe as mastectomy.23,24 Furthermore, most BRCA1/2 mutation carriers with breast tissue present at age 60 in our study did not have a history of breast cancer. Older age at onset, also in BRCA1/2 mutation carriers, can be a family trait.25 Because in BRCA1/2 mutation carriers ≥60, breast cancer incidence remains high,4,5,15 screening effectiveness in this group is a highly relevant question. Also for BRCA1/2 mutation carriers ≥60 with a history of breast cancer, screening is important, since contralateral breast cancer risk is high; up to 56% after 25 years,26 and survival with timely diagnosis is good.27

While screening biennially is beneficial in the general population,28,29 our results suggest that continuation of annual screening is the advisable strategy for BRCA1/2 mutation carriers ≥60. Biennial screening compared to annual screening resulted in twice as many BRCA1/2-associated cancers detected as interval cancers (40%) and twice as many breast cancers detected in an unfavourable stage (53%). Differences in tumour stage remained significant when breast cancers of BRCA1 and BRCA2 mutation carriers were analysed separately.

Since no prior studies have been published that assess the most effective screening frequency in BRCA1/2 mutation carriers ≥60 specifically, it is not possible to compare our results with those of others. However, our results are supported by knowledge of the biology of BRCA1/2 tumours. BRCA1/2 breast cancers grow twice as fast as sporadic breast cancers20,30 and are more often detected as interval cancers.17 There is no evidence for a sudden change in tumour biology of BRCA1/2 mutation carriers at age 60. This is supported by our findings and those of others, that like BRCA1/2 breast cancers at younger age, BRCA1 breast cancers ≥60 are significantly more often oestrogen-negative than BRCA2 tumours ≥60.27,31 Compared with the results of the Dutch population-based National Breast Cancer Screening Program, in which women in the ages of 50 to 75 are screened with biennial mammography, the results of biennial screening in BRCA1/2 mutation carriers are disappointing. In the general population less than 30% of tumours (DCIS included) are diagnosed in an unfavourable stage; this percentage is almost doubled with biennial screening of BRCA1/2 mutation carriers.32 Annual screening is therefore more appropriate.

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Although carefully designed and executed, our study does have limitations. We have reported extensive information on mastectomies and prior cancers in BRCA1/2 mutation carriers from a prospectively collected national hereditary breast cancer cohort and a large family cancer clinic cohort to describe our population at risk. However, there is a considerable variability between countries in the uptake of risk reducing strategies by BRCA1/2 mutation carriers.10 In the Netherlands and the United States of America relatively many women opt for bilateral risk-reducing mastectomy.11 Therefore our results may be an underestimation of the proportion of women at risk for breast cancer aged ≥60 in countries, like France and Italy, where more carriers opt for screening.11 In these countries there might be an even larger proportion of BRCA1/2 mutation carriers for whom continuation of annual screening is relevant.

Secondly, our study does not have a randomized design, and there was a significant difference in the screening of BRCA1 mutation carriers and BRCA2 mutation carriers ≥60. BRCA2 mutation carriers were less intensively screened and more often not screened at all. Moreover, patients with a second breast cancer were more often screened with annual screening as opposed to patients with a first breast cancer, introducing selection bias. An explanation might be that, although Dutch guidelines do not advise annual screening for BRCA1 and BRCA2 mutation carriers above the age of 60,13 doctors often do not feel safe, sending these mutation carriers with a history of breast cancer, to the National Breast Cancer Screening Program where they are screened biennially. Furthermore, Dutch guidelines advise screening with annual mammography for the first 5 years after breast cancer detection, irrespective of age.13 However, in stratified analyses the percentage breast cancers found in unfavourable tumour stage with biennial mammography was comparable for first and second breast cancers. Furthermore, adjusting for first breast cancer (yes or no) in multivariable analysis did not influence the significant difference in tumour stage at detection found between annual and biennial screening in BRCA1 and BRCA2 breast cancers.

Furthermore, we have chosen not to analyse survival data, as interpretation will be extremely difficult, due to a large number of patients with a history of a previous breast cancer (39%) and/or other invasive cancer (additional 18%). In general, and also in BRCA1/2-associated breast cancers, the risk of metastases is related to both tumour size and the number of axillary lymph nodes involved.27,33 Consequently, “unfavourable tumour stage,” provides a good alternative outcome for prognosis.

Also, our study does not report on the number of false-positives, the number of additional examinations, or the extra costs of a more frequent screening scheme with mammography. However, the differences in tumour stage between annual and biennial mammography screening were so large, that it is likely that the advantages of annual screening outweigh the disadvantages. Finally, since so few BRCA1/2 mutation carriers were screened with MRI, no comparative analyses were performed for this group to guarantee statistical accurateness. Screening with additional MRI in younger BRCA1 and BRCA2 mutation carriers is generally considered both effective, sensitivity of at least 70%,17,34 as well as cost-effective.35 The preferred method of breast cancer screening for BRCA1/2 mutation carriers ≥60; MRI and/or mammography, remains to be assessed. The results of this comparison might also be influenced by breast density, which is associated with increased breast cancer incidence, also in BRCA1/2 mutation

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carriers,36 and decreased sensitivity of mammography.37 In conclusion, the majority of BRCA1/2 mutation carriers are still at risk for breast

cancer after the age of 60. If life expectancy is good, annual mammography screening of BRCA1/2 mutation carriers ≥60 should be considered over biennial screening.

AcknowledgementsThe authors thank Thea Mooij (Department of Epidemiology, the Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands) and Ellen Crepin (Department of Medical Oncology, Erasmus Medical Centre-Cancer Institute, Rotterdam, The Netherlands) for data management.

The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) consists of the following Collaborating Centres: Coordinating centre: Netherlands Cancer Institute, Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, F.E. van Leeuwen, S. Verhoef, M.K. Schmidt, J.L. de Lange; Erasmus Medical Centre, Rotterdam, NL: J.M. Collée, A.M.W. van den Ouweland, M.J. Hooning, C. Seynaeve, C.H.M. van Deurzen, I.M. Obdeijn, M.M.A. Tilanus-Linthorst; Leiden University Medical Centre, NL: C.J. van Asperen, J.T. Wijnen, R.A.E.M. Tollenaar, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Centre, NL: C.M. Kets, A.R. Mensenkamp; University Medical Centre Utrecht, NL: M.G.E.M. Ausems, R.B. van der Luijt; Amsterdam Medical Centre, NL: C.M. Aalfs, T.A.M. van Os; VU University Medical Centre, Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital Maastricht, NL: E.B. Gómez-Garcia, M.J. Blok; University Medical Centre Groningen, NL: J.C. Oosterwijk, A.H. van der Hout, M.J. Mourits, G.H. de Bock. The Netherlands Foundation for the detection of hereditary tumours, Leiden, NL: H.F. Vasen.

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References

1. Miki Y, Swensen J, Shattuck-Eidens D, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science 1994;266:66-71.

2. Wooster R, Neuhausen SL, Mangion J, et al. Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13. Science 1994;265:2088-90.

3. Mavaddat N, Peock S, Frost D, et al. Cancer Risks for BRCA1 and BRCA2 Mutation Carriers: Results From Prospective Analysis of EMBRACE. J Natl Cancer Inst 2013;105:812-22.

4. Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet 2003;72:1117-30.

5. Van der Kolk DM, de Bock GH, Leegte BK, et al. Penetrance of breast cancer, ovarian cancer and contralateral breast cancer in BRCA1 and BRCA2 families: high cancer incidence at older age. Breast Cancer Res Treat 2010;124:643-51.

6. Kurian AW, Sigal BM, Plevritis SK. Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers. J Clin Oncol 2010;28:222-31.

7. Saslow D, Boetes C, Burke W, et al. American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J Clin 2007;57:75-89.

8. Balmana J, Diez O, Rubio IT, Cardoso F. BRCA in breast cancer: ESMO Clinical Practice Guidelines. Ann Oncol 2011;22(Suppl 6):vi31-vi34.

9. National Comprehensive Cander Network (NCCN). NCCN clinical practice guidelines in oncology (NCCN Guidelines): genetic/familial high-risk assessment: breast and ovarian [Guideline]. Version1.2012. 2012. Available at http://www.nccn.org/professionals/physician_gls/pdf/genetics_screening.pdf.

10. Wainberg S, Husted J. Utilization of screening and preventive surgery among unaffected carriers of a BRCA1 or BRCA2 gene mutation. Cancer Epidemiol Biomarkers Prev 2004;13:1989-95.

11. Metcalfe KA, Birenbaum-Carmeli D, Lubinski J, et al. International variation in rates of uptake of preventive options in BRCA1 and BRCA2 mutation carriers. Int J Cancer 2008;122:2017-22.

12. National Institute for Health and Clinical Excellence guidelines (NICE). NICE clinical guideline 164: Familial breast cancer: classification and care of people at risk of familial breast cancer and management of breast cancer and related risks in people with a family history of breast cancer. 2013. Available at: http://www.nice.org.uk/nicemedia/live/14188/64202/64202.pdf.)

13. Nationaal Borstkanker Overleg Nederland (NABON). Richtlijn mammacarcinoom (breast cancer national guideline). 2012. Available at: http://oncoline.nl/richtlijn/doc/index.php?type=pda&richtlijn_id=828.

14. Stichting Opsporing Erfelijke Tumoren (STOET), Vereniging Klinische Genetica Nederlands (VKGN). Erfelijke Tumoren: richtlijnen voor diagnostiek en preventie (hereditary cancer: guidelines for diagnosis and prevention). Available at: http://www.vkgn.org/images/Vakinformatie/Richtlijnen_en_protocollen/StOET_VKGN_richtlijn_erfelijke_tumoren.pdf.

15. Chen S, Parmigiani G. Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 2007;25:1329-33.

16. Moller P, Evans DG, Reis MM, et al. Surveillance for familial breast cancer: differences in outcome according to BRCA mutation status. Int J Cancer 2007;121:1017-20.

17. Rijnsburger AJ, Obdeijn IM, Kaas R, et al. BRCA1-associated breast cancers present differently from BRCA2-associated and familial cases: long-term follow-up of the Dutch MRISC Screening Study. J Clin Oncol 2010;28:5265-73.

18. Leach MO, Boggis CR, Dixon AK, et al. Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS). Lancet 2005;365:1769-78.

19. Warner E, Plewes DB, Hill KA, et al. Surveillance of BRCA1 and BRCA2 mutation carriers with magnetic resonance imaging,

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ultrasound, mammography, and clinical breast examination. JAMA 2004;292:1317-25.

20. Tilanus-Linthorst MM, Obdeijn IM, Hop WC, et al. BRCA1 mutation and young age predict fast breast cancer growth in the Dutch, United Kingdom, and Canadian magnetic resonance imaging screening trials. Clin Cancer Res 2007;13:7357-62.

21. Pijpe A, Manders P, Brohet RM, et al. Physical activity and the risk of breast cancer in BRCA1/2 mutation carriers. Breast Cancer Res Treat 2010;120:235-44.

22. Heemskerk-Gerritsen BA, Menke-Pluijmers MB, Jager A, et al. Substantial breast cancer risk reduction and potential survival benefit after bilateral mastectomy when compared with surveillance in healthy BRCA1 and BRCA2 mutation carriers: a prospective analysis. Ann Oncol 2013;24:2029-35.

23. Kirova YM, Savignoni A, Sigal-Zafrani B, et al. Is the breast-conserving treatment with radiotherapy appropriate in BRCA1/2 mutation carriers? Long-term results and review of the literature. Breast Cancer Res Treat 2010;120:119-26.

24. Pierce LJ, Phillips KA, Griffith KA, et al. Local therapy in BRCA1 and BRCA2 mutation carriers with operable breast cancer: comparison of breast conservation and mastectomy. Breast Cancer Res Treat 2010;121:389-98.

25. Tilanus-Linthorst MM, Lingsma HF, Evans DG, et al. Optimal age to start preventive measures in women with BRCA1/2 mutations or high familial breast cancer risk. Int J Cancer 2013;133:156-63.

26. Graeser MK, Engel C, Rhiem K, et al. Contralateral breast cancer risk in BRCA1 and BRCA2 mutation carriers. J Clin Oncol 2009;27:5887-92.

27. Brekelmans CT, Tilanus-Linthorst MM, Seynaeve C, et al. Tumour characteristics, survival and prognostic factors of hereditary breast cancer from BRCA2-, BRCA1- and non-BRCA1/2 families as compared to sporadic breast cancer cases. Eur J Cancer 2007;43:867-76.

28. Berry DA, Cronin KA, Plevritis SK, et al. Effect of screening and adjuvant therapy on mortality from breast cancer. N Engl J Med 2005;353:1784-92.

29. Independent UKPoBCS. The benefits and harms of breast cancer screening: an independent review. Lancet 2012;380:1778-86.

30. Heijnsdijk EA, Warner E, Gilbert FJ, et al. Differences in natural history between breast cancers in BRCA1 and BRCA2 mutation carriers and effects of MRI screening-MRISC, MARIBS, and Canadian studies combined. Cancer Epidemiol Biomarkers Prev 2012;21:1458-68.

31. Lakhani SR, Jacquemier J, Sloane JP, et al. Multifactorial analysis of differences between sporadic breast cancers and cancers involving BRCA1 and BRCA2 mutations. J Natl Cancer Inst 1998;90:1138-45.

32. National Evaluation Team for Breast Cancer in the Netherlands (NETB). NETB report 2012: main results 2010 breast cancer screening programme in the Netherlands. 2012. Available at: http://www.erasmusmc.nl/mgz/publicationsx/reports/evaluatie-borstkanker/.

33. Sant M, Allemani C, Capocaccia R, et al. Stage at diagnosis is a key explanation of differences in breast cancer survival across Europe. Int J Cancer 2003;106:416-22.

34. Obdeijn IM, Winter-Warnars GA, Mann RM, et al. Should we screen BRCA1 mutation carriers only with MRI? A multicenter study. Breast Cancer Res Treat 2014;144:577–82.

35. Griebsch I, Brown J, Boggis C, et al. Cost-effectiveness of screening with contrast enhanced magnetic resonance imaging vs X-ray mammography of women at a high familial risk of breast cancer. Br J Cancer 2006;95:801–10.

36. Gierach GL, Loud JT, Chow CK, et al. Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer. Breast Cancer Res Treat 2010;123:245–55.

37. Kerlikowske K, Zhu W, Hubbard RA; Breast Cancer Surveillance C. Outcomes of screening mammography by frequency, breast density, and postmenopausal hormone therapy. JAMA Int Med 2013;173:807–16.

Chapter 8General discussion

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Summary

The (lifetime) risk of cancer in BRCA1/2 mutation families has been studied extensively, although results show a wide variation, which is confusing for clinical practice. The aim of this thesis was to improve the accuracy of the breast and ovarian cancer risk estimates in BRCA1/2 mutation families by understanding the reasons for risk variation and assessing the effect of suggested risk factors, especially familial factors, more closely. Both absolute and relative breast and ovarian cancer risks were assessed in mutation negative and mutation positive women in BRCA1/2 mutation families. Moreover, the implications of the CLTRs for breast cancer screening above age 60 in BRCA1/2 mutation carriers were evaluated.

Cancer in proven non-carriersFor proven non-carriers in BRCA1/2 mutation families, study results are contradicting on whether or not these non-carrier relatives are at increased risk for breast cancer as compared to women in the general population, whereas for ovarian cancer no risk estimates for non-carriers were available at all. Both breast and ovarian cancer risks of proven non-carriers in BRCA1/2 mutation families were assessed in a consecutive cohort counseled at the Family Cancer Clinic in the Northern region of the Netherlands (chapter 2). The results showed that the lifetime risk of breast cancer was slightly increased (SIR 1.5, 95%CI 0.9-2.3) as compared to the general population, whereas for ovarian cancer no risk increase was detected, though these numbers were small. The breast cancer risk increase was more pronounced in non-carriers from BRCA1 mutation families (SIR 2.0, 95%CI 1.1-3.3), especially in age-group 40-49 (SIR 4.5, 95%CI 1.8-9.2). At first sight the stronger risk increase in the 5th decade might be considered as a sign of ascertainment and genetic testing bias, however, the effect remained when bias correction was performed through inclusion of a proportion of untested FDRs. Only among BRCA1 mutation families a difference in familial load (i.e. a more suspected family history) was observed between families with affected non-carriers before age 50 and the rest of the families.

Breast cancer risk variation in the NetherlandsPreviously relatively high breast cancer risks, especially at older age, were observed for mutation carriers in the Northern-Netherlands (up to 88% for BRCA2) as compared to carriers in the rest of the Netherlands (Geo-Hebon cohort). In order to assess whether mutation carriers in the Northern-Netherlands are indeed at higher risk as compared to the rest of the Netherlands and to disentangle this effect from the impact of differences in study methodology and bias, we examined and quantified the existence of regional risk differences in the Netherlands by using these two Dutch clinic-based cohorts and analyzing them identically (chapter 3). BRCA1 mutation carriers in the rest of the Netherlands were at a somewhat increased risk (HR = 1.52, 95%CI 1.23-1.85) as compared to the Northern-Netherlands as were the BRCA2 mutation carriers up to age 60 (HR = 1.56, 95%CI 1.04-2.17). From age 60 onwards BRCA2 mutation carriers in the Northern-Netherlands were at increased risk when compared to BRCA2 carriers

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in the rest of the Netherlands (HR = 3.99, 95%CI 1.11-14.4). Regional differences in the mutation spectrum exist, especially for BRCA2 due to several Northern founder mutations, but these only partly explained the observed regional risk differences.

Breast cancer risk variation explained by methodologyFor BRCA1/2 mutation carriers, the breast cancer lifetime risk estimations vary from 27% to 88%. The regional risk differences in the Netherlands appeared smaller than what could have been expected as based on the CLTRs for the separate cohorts (chapter 3). This was suggestive of a possible impact of differences in study methodology. The impact of risk assessment methodology and bias correction was explicitly assessed by applying all applicable methods -in total 19- to one well-defined clinic-based cohort (chapter 4). These different methods consisted of Kaplan-Meier analyses with and without bootstrapping, of frailty model analyses and of modified segregation analyses for risk estimation, in combination with different forms of bias correction, such as excluding indexes, including untested FDRs or conditioning the likelihood function on phenotype and genotype. The estimates of all methods resulted in a variation of the CLTRs of 35% to 83% for BRCA1 and 41% to 86% in BRCA2 mutation carriers. Much of the variation seen in the CLTRs could be explained by the different bias correction methods, and not so much by population differences. Results of our simulation study showed that the Kaplan-Meier estimation with bias correction through inclusion of a proportion of untested FDRs was the most suitable method for risk estimation in BRCA1/2 mutation carriers counseled in the Family Cancer Clinic. The modified segregation analyses with conditioning of the likelihood function on index cases’ genotype and all phenotypes provided risk estimates more suitable for population-based cohort of BRCA1/2 carriers.

Inverse trends in ovarian cancer riskFor breast cancer the CLTR increases in more recent birth cohorts both in the general and in the BRCA1/2 carrier population. This is most likely due to a combination of changes in lifestyle, hormonal and reproductive factors. The results of previous studies on the effect of the birth cohort on the ovarian cancer risk in BRCA1/2 mutation carriers also indicated an increase but were inconsistent. However, this possible risk increase is in contrast with the decreasing ovarian cancer incidence by birth cohort observed in the general population. In a regional clinic-based cohort of mutation carriers and their background general population it was assessed whether a birth cohort effect existed for ovarian cancer as this effect is known to be present for breast cancer (chapter 5). Our results show that the ovarian cancer in BRCA1/2 mutation carriers is increased in more recent birth cohorts, even though the risk is decreasing in their background general population in more recent cohorts. BRCA1/2 mutation carriers born more recently, particularly those with a BRCA1 mutation, have a higher additional ovarian cancer risk. The reason for this is not yet clear.

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The parent-of-origin effect for breast cancer risksIt has been suggested that the effect of the parent-of-origin of the BRCA1/2 mutation is associated with the risk of breast cancer. The presences of the parent-of-origin effect, and whether this effect is independent from referral bias due to differences in the family or personal history of cancer was assessed using the national clinic-based Hebon cohort (chapter 6). The results showed that the presence of a parent-of-origin effect depends on the way one corrects for referral bias. Correction of referral bias as defined by family history did not substantially impact this effect, while bias correction for the personal cancer history made the parent-of-origin effect disappear. This bias when uncorrected, may have caused the positive association between paternal origin of the BRCA1/2 mutation and risk of breast cancer in earlier studies. In a larger prospective cohort the impact of referral bias by a combined assessment of family and personal history should be addressed.

Breast cancer screening from age 60 onwardsIn the Netherlands, BRCA1/2 mutation carriers are offered intensive breast cancer screening from age 25 to age 60. Above age 60, they are offered less intensive screening till age 75 consisting of either annual mammography or the national screening program with biennial mammography. The relevancy and efficacy of screening mutation carriers aged 60 year and over was assessed using the cohorts of the Family Cancer Clinic in Rotterdam and Groningen and the national Hebon cohort (chapter 7). More than 70% of the mutation carriers over age 60 still has one or two breasts, and therefore remains at risk for breast cancer. More than half of the tumors detected by biennial mammography were of unfavorable stage, which was more than two times higher as by annual mammography. Above age 60, BRCA1/2 mutation carriers are still at risk for breast cancer and annual mammography might be beneficial.

Methodological considerations

In research, study designs and biases are often a topic of debate, and assumptions regarding the impact or existence of these methodological issues are made on a regular basis. As these methodological issues can influence the outcome of the study, it is important to stress the following methodological considerations.

For accurate risk estimations several methodological issues regarding statistics, bias correction as well as population and familial factors are important to consider. Which risks are we estimating, and for whom are we estimating them? Is the study cohort the proper cohort for the analyses? How are the subjects ascertained and are there causes for bias? When does the follow-up time start, and when was the DNA test performed? Which events are being counted and at which events should censoring be applied? And, when comparing groups or estimating relative risks, are there demographic differences between the groups or confounding factors that should be taken into account?

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Target population: is the study population suitable to answer your research question?When estimating CLTRs it is important to keep the target population in mind: for which population will the calculated cancer risks be applicable? For BRCA1/2 carriers that are referred to the familial cancer clinics, or for unselected carriers from the general population? For the estimation of breast cancer risk for BRCA1/2 mutation carriers both clinic-based and population-based study cohorts have been used. However, it is for the women seen in the Family Cancer Clinic, i.e. those women who receive the actual counseling, that we need adequate risk figures the most. Of all BRCA1/2 families, only the high-risk BRCA1/2 families will enter the clinic since their personal and/or family history meets the national referral criteria. Even when the risk estimates are based on a clinic-based population, just using every female mutation carrier for risk estimation would result in incorrect risk estimates as this population is enriched with cancer cases (e.g. early onset and/or bilateral breast cancer, or ovarian cancer), because they were the ones referred as index cases. So when assessing absolute or relative risks, the ascertainment bias (also called selection bias or referral bias) and genetic testing bias -meaning that affected women are more likely to undergo DNA testing- should be addressed. Prospective versus retrospective cohortsMost studies on cancer risks in BRCA1/2 mutation families -including the ones in this thesis- are based on retrospective or consecutive cohorts. However, it is generally assumed that prospective studies are preferable, because reported information is more accurate and the design can already take the above described biases into account. Inclusion of all cancer cases, including those cases that led to the ascertainment of the family because of referral to the Family Cancer Clinic, might be troublesome when assessing the effect of family history factors, since there is overlap between the selection criteria (familial cancer as reason for referral), the risk predictors (familial cancer load as separate risk factor) and possibly the outcome event (cancer as event and/or reason for censoring). However, in a prospective analysis -including only incident cases that occurred after a person’s date of genetic testing- the follow-up time, especially at older age, and the number of incident cases are still rather limited, because 1) genetic testing for BRCA1/2 mutations started small scale (only) 20 years ago, and 2) the percentage of women opting for risk-reducing surgery is increasing, which markedly reduces the collection of follow-up data. An alternative approach could be to only include follow-up time and events that occurred after the first BRCA1/2 mutation has been found in the family (i.e. the index), but here genetic-testing bias is still in play. However, the follow-up time at older age remains an important factor with respect to the certainty and applicability of the risk estimates.

Familial clusteringThere are two reasons for incorporating the family structure or familial clustering in the analyses: dependent sampling and unobserved heterogeneity. First, in BRCA1/2 mutation families the sampling of the family members does not occur independently as it occurs via a cascade screening approach within the family. This implies that mutation carriers are not independent from each other but correlated, while independent or

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random sampling is the statistical assumption. When clustering is presented but not incorporated in the model the standard errors will be smaller than they should be. Second, BRCA1/2 mutation families seen in the Familial Cancer Clinic setting all meet the referral criteria, but this referred BRCA1/2 population is not homogeneous. Some families have a stronger family history than others, and in some families a history of breast cancer predominates while in others a history of ovarian cancer is most outspoken. This familial heterogeneity can be a chance phenomenon, but it can also be due to differences in the underlying risk profile consisting of the BRCA1/2 mutation type and other genetic and non-genetic factors that family members share and that lead to different phenotypic expression. For example, two sisters (i.e. 1st degree relatives) share more (non-) genetic factors than two women from two different families, but they share also more than two cousins (i.e. 3rd degree relatives) in one family. Because not all factors contributing to the cancer risks are known or measured, there is so called unobserved heterogeneity. For either of the two reasons to take the familial clustering into account, the familial clustering should be considered also when one is interested in marginal (i.e. population-averaged) estimates and the familial clustering is considered to be a nuisance.

For the study results in this thesis, the estimated clustering or heterogeneity between families was small and incorporating the familial clustering had only a small impact on the standard errors (i.e. larger standard errors) of the marginal estimates. However, this could have been because the definition of a family was rather broad and included besides close relatives also more remote relatives. Other studies have shown a larger impact of familial clustering when only first- or second-degree relatives were grouped in a family cluster.1

Confounding factorsIn (epidemiological) research it is important to consider any type of bias, including bias by confounding factors, i.e. factors related to both the outcome and predictor. When assessing relative risks of cancer in observational, non-matched cohorts, confounding factors might distort part of the effect seen. For example, in the assessment of the regional risk difference in the Netherlands (this thesis), the two regional cohorts had a different distribution of the BRCA mutation spectrum. The mutation spectrum was related to the region but is also known to be related to the breast cancer risk, and was therefore included a confounding factor. Sometimes the relevance of a confounding factor is assessed by how much the outcome of interest changes when the confounder is taken into account. When this change is more than a pre-defined percentage (e.g. 5%) the factor is considered relevant and remains included in the analysis.

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Implications for practice and research

Understanding the variation in calculated cancer risks is important for comparing risk estimates in the literature, for re-evaluation of guidelines for counseling of population-averaged risk estimates, as well as for the development of more patient-tailored risk estimates. BRCA1/2 mutation carriers face complicated choices based on a fixed range of breast and ovarian cancer lifetime risks. Although a patient’s decision-making regarding preventive options is influenced by a complex network of factors, tailored cancer risk estimation could be beneficial as it could reduce part of uncertainty and might help to choose the right thing to do, at the right time.2, 3

The research in this thesis has detected several risk associations and trends that could contribute to the development of more personalized risk estimates or that are relevant for other aspects of clinical practice. For some of the observed effects the underlying cause is still unexplained and this should be addressed in follow-up research. The implications for clinical practice and follow-up research will be discussed here: starting with breast and ovarian cancer risks in mutation carriers, followed by breast cancer screening in mutation carriers, and ending with cancer risks in non-carriers in mutation families.

Breast cancer risk counselling in mutation carriersReferral criteria have changed over time and have become slightly less stringent. Since less than 2 years, ovarian cancer patients can be referred to the Family Cancer Clinic irrespective of their family history, because family history was not a good predictor for mutation carriership.4 Also for breast cancer patients such a trend may develop, the age cut-off for referral of breast cancer patients with triple negative cancer (50 years) is already a topic of discussion. These changes in referral criteria mean that in the (near) future the clinic-based population of mutation carriers will no longer consist of only the selected high-risk population. The currently counselled breast and ovarian risk estimates might not be applicable to all mutation carriers, as (in this thesis) it is shown that different breast cancer risk estimates apply to selected mutation carriers (clinic-based cohorts) and unselected mutation carriers (population-based cohorts). More tailored risk counselling is one way to deal with this expected growing heterogeneity among BRCA1/2 mutation families. In this thesis it is shown that risk estimates probably can be refined using birth cohort, mutation spectrum and family history. Risk tailoring based on these confirmed and rather easy to measure risk factors would be a good step in the direction of more personalized risk counselling. In the meantime continuing research should focus on the elucidation of this heterogeneity by assessing SNPs, environmental factors and the interaction between the genetic and non-genetic factors. As for such studies enormous sample sizes are needed, continuation of (inter-)national registration of mutation families and cancer cases is crucial.

Irrespective of the discussion on tailoring of cancer risks, improvements can be made to current counselling of population-averaged risks by incorporating residual risks or 10-year risks, and expanding lifetime risks data till age 80 or over. Counselling of only lifetime risks might not always be appropriate, and residual cancer risks

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might be more informative. For example, for a 55-year old mutation carrier, what is her risk as she already survived so many years cancer-free? As the residual cancer risks are based on the curve of the lifetime risk, these estimates can be determined using suitable lifetime risk curves. However, most studies provide risk curves and risk estimations up to age 70, while the average life expectancy for women is more than 10 years higher and still increasing.5 Some risk assessment tools, e.g. Boadicea, do provide risk estimates up to age 80, but these estimates are not yet based on the Dutch population.6 Breast cancer screening from age 60 onwards.The breast cancer risk in mutation carriers is still increasing after age 60. BRCA2 mutation carriers in the Northern-Netherlands over age 60 had a more increased breast cancer risk as compared to those in the rest of the Netherland. It should be assessed whether, besides the BRCA1/2 mutation, other genetic and non-genetic factors can explain this lasting risk increase. Understanding this risk difference might give indications regarding which women might benefit most from breast cancer screening above the age of 60. Offering annual mammography to BRCA1/2 mutation carriers may be beneficial to detect tumors in a more favorable stage. Over time, guidelines have changed on this topic and mutation carriers over age 60 with dense breasts are already offered annual mammography outside the national screening program. It could be considered to offer this to all mutation carriers over age 60 with a good life expectancy.

Ovarian cancer risk in mutation carriersFor ovarian cancer, a similar discussion on risk tailoring and improvement of population-averaged applies. Even more so, because for ovarian cancer no screening is available and risk-reducing surgery is the only way for cancer prevention. This surgery –when performed in the appropriate time window- leads to immediate and early menopause, which may lead to short-term and long-term morbidity. Therefore, more personal or age-related cancer risk estimates are necessary for counselling on the optimal timing of RRSO.7-10

For ovarian cancer also varying population-averaged risk estimates are published. An assessment of the effect of different methods of risk estimation and bias correction might be insightful, especially as for ovarian cancer the general population risk and population selection might show more variation among studies and countries.6, 11 For example, in the general population of the Netherlands the incidence of ovarian cancer is declining over time, while this is not the case for all countries. The decreasing trends in the Netherlands is most probably due to the wide spread use of oral contraceptives.12

For risk tailoring it is important to understand the birth cohort effect and the conflicting trends in the ovarian cancer risk in BRCA1/2 mutation carriers and general population. A starting point for this understanding might be to explore possible differences in oral contraceptive use between the two populations.

Proven non-carriersFor proven non-carriers in BRCA1/2 mutation families an increased risk was observed in the 5th decade. Annual mammography from age 40 to 49 may be considered, if the

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results are confirmed in a upcoming national study. However, it could be that only a subgroup of non-carriers is at increased risk, due to underlying (non-) genetic risk factors. In this thesis the increased risk was mainly observed in non-carriers in BRCA1 mutation families, while in a recent study from the UK an increased risk was observed among non-carriers in BRCA1/2 mutation families,13 whereas in their prospective analyses the risk increase was mainly present in non-carriers in BRCA2 mutation families.

To improve the age-related risk counselling of proven non-carriers, follow-up research on the genetic load using OncoPanels, and the effect of SNPs and environmental factors (e.g. BMI, use of oral contraceptives, reproductive history and breast density) should be conducted to unravel the factors driving the increased cancer risk in non-carriers. Depending on the outcomes, personalized breast cancer screening might be explored for proven non-carriers.14-16

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References

1. Hsu L and Gorfine M. Multivariate survival analysis for case-control family data. Biostatistics 2006; 7: 387-398.

2. van Driel CM, de Bock GH, Arts HJ, Sie AS, Hollema H, Oosterwijk JC, et al. Stopping ovarian cancer screening in BRCA1/2 mutation carriers: effects on risk management decisions & outcome of risk-reducing salpingo-oophorectomy specimens. Maturitas 2015; 80: 318-322.

3. van der Aa JE, Hoogendam JP, Butter ES, Ausems MG, Verheijen RH and Zweemer RP. The effect of personal medical history and family history of cancer on the uptake of risk-reducing salpingo-oophorectomy. Fam Cancer 2015; doi: 10.1007/s10689-015-9827-7.

4. Commissie Richtlijnen Gynaecologische Oncologie (CRGO) en Integraal Kankercentrum Nederland ( INKL). Richtlijn erfelijk en familiair ovariumcarcinoom (National guideline hereditary and familiar ovarian cancer). 2015. Available at: http://www.oncoline.nl/erfelijk-en-familiair-ovariumcarcinoom. Accessed 5 Oct 2015.

5. Organisation for Economic Co-operation and Development (OECD). Health at a Glance: Europe 2012. Available at: http://dx.doi.org/10.1787/9789264183896-en. Accessed 5 Oct 2015.

6. Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC, et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 2014; 110: 535-545.

7. Berek JS, Chalas E, Edelson M, Moore DH, Burke WM, Cliby WA, et al. Prophylactic and risk-reducing bilateral salpingo-oophorectomy: recommendations based on risk of ovarian cancer. Obstet Gynecol 2010; 116: 733-743.

8. Arts-de Jong M, Maas AH, Massuger LF, Hoogerbrugge N and de Hullu JA. BRCA1/2 mutation carriers are potentially at higher cardiovascular risk. Crit Rev Oncol Hematol 2014; 91: 159-171.

9. Fakkert IE, Abma EM, Westrik IG, Lefrandt JD, Wolffenbuttel BH, Oosterwijk JC, et al. Bone mineral density and fractures after risk-reducing salpingo-oophorectomy in women at increased risk for breast and ovarian cancer. Eur J Cancer 2015; 51: 400-408.

10. Harmsen MG, Hermens RP, Prins JB, Hoogerbrugge N and de Hullu JA. How medical choices influence quality of life of women carrying a BRCA mutation. Crit Rev Oncol Hematol 2015; doi: 10.1016/j.critrevonc.2015.07.010.

11. Jervis S, Song H, Lee A, Dicks E, Harrington P, Baynes C, et al. A risk prediction algorithm for ovarian cancer incorporating BRCA1, BRCA2, common alleles and other familial effects. J Med Genet 2015; 52: 465-475.

12. Braem MG, Onland-Moret NC, van den Brandt PA, Goldbohm RA, Peeters PH, Kruitwagen RF, et al. Reproductive and hormonal factors in association with ovarian cancer in the Netherlands cohort study. Am J Epidemiol 2010; 172: 1181-1189.

13. Evans DG, Ingham SL, Buchan I, Woodward ER, Byers H, Howell A, et al. Increased rate of phenocopies in all age groups in BRCA1/BRCA2 mutation kindred, but increased prospective breast cancer risk is confined to BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev 2013; 22: 2269-2276.

14. Evans DG and Howell A. Can the breast screening appointment be used to provide risk assessment and prevention advice? Breast Cancer Res 2015; 17: 84.

15. Price ER, Keedy AW, Gidwaney R, Sickles EA and Joe BN. The Potential Impact of Risk-Based Screening Mammography in Women 40-49 Years Old. AJR Am J Roentgenol 2015; doi: 10.2214/AJR.15.14668.

16. Feig SA. Personalized Screening for Breast Cancer: A Wolf in Sheep’s Clothing? AJR Am J Roentgenol 2015; doi: 10.2214/AJR.15.15293.

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AppendicesNederlandse samenvatt ing

DankwoordCurriculum Vitae

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IntroductieBorstkanker is wereldwijd de meest voorkomende kanker onder vrouwen. De kans dat een vrouw in haar leven borstkanker ontwikkelt (het zogenoemde lifetime-risico) is in Nederland circa 12%. Het lifetime-risico op eierstokkanker is veel lager en bedraagt circa 1,2%. In Nederland worden jaarlijks ongeveer 14.000 vrouwen gediagnosticeerd met borstkanker en 1.300 vrouwen met eierstokkanker. Ongeveer 5-10% van deze tumoren wordt veroorzaakt door een mutatie in de borstkankergenen BRCA1 en BRCA2. BRCA1/2-mutatiedraagsters hebben een sterk verhoogd borsten eierstokkankerrisico en ontwikkelen kanker veelal op jongere leeftijd in vergelijking met vrouwen in de algemene bevolking. Omdat bewezen mutatiedraagsters een sterk verhoogd borstkankerrisico hebben, kunnen ze kiezen voor intensieve borstcontroles om de ziekte zo vroeg mogelijk op te sporen, of voor preventieve borstamputatie (mastectomie) om de kanker te voorkomen. Voor eierstokkanker bestaat geen effectieve screening om de ziekte vroegtijdig op te sporen, en de ziekte is vaak al in een gevorderd stadium op het moment dat deze wordt ontdekt. Daarom wordt BRCA1/2-mutatiedraagster geadviseerd om tijdig een preventieve verwijdering van de eierstokken en eileiders (bilaterale salpingo-ovariëctomie) te laten verrichten, op een leeftijd vóórdat het risico begint te stijgen.

Op basis van een belaste persoonlijke voorgeschiedenis en familiegeschiedenis van met name borsten eierstokkanker kunnen mensen verwezen worden naar een polikliniek Familiaire Tumoren voor genetische counseling en mogelijk DNA-onderzoek. Momenteel worden bij de counseling van BRCA1/2-mutatiedraagsters populatie-gemiddelde risicoschattingen voor borsten eierstokkanker gebruikt, waarbij deze vrouwen voor ingrijpende keuzes staan ten aanzien van periodieke controles en preventieve operaties. Daarnaast variëren de (leeftijdsspecifieke) schattingen van deze risico’s in de literatuur behoorlijk, wat verwarrend is voor de klinische praktijk. Een preciezere voorspelling van het kankerrisico op een bepaalde leeftijd kan daarom bijdragen aan een betere counseling en persoonlijkere afstemming van het advies over keuze en timing van de ingrijpende preventieve operaties.

Het doel van dit proefschrift was de nauwkeurigheid van de risicoschattingen op borstkanker en eierstokkanker in BRCA1/2-mutatiefamilies te verbeteren. Om dit doel te bereiken is onderzoek uitgevoerd om de redenen van de risicovariatie te begrijpen en bekende risicofactoren, met name familiespecifieke factoren, nader te onderzoeken. Populatie-gemiddelde risico’s en relatieve risico’s op borsten eierstokkanker werden onderzocht in vrouwen met en vrouwen zonder een BRCA1/2 mutatie, afkomstig uit bekende BRCA1/2-mutatiefamilies. Daarnaast is het belang van borstkankerscreening in BRCA1/2-mutatiedraagsters ouder dan 60 jaar geëvalueerd.

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Borst- en eierstokkankerrisico’s in niet-draagsters afkomstig uit BRCA1/2-mutatiefamiliesOver het algemeen wordt ervan uitgegaan dat vrouwen die geen draagster zijn van de BRCA1/2 mutatie die in hun familie is vastgesteld, de zogenaamde bewezen niet-draagsters, geen verhoogd risico hebben op borsten eierstokkanker in vergelijking met vrouwen in de algemene bevolking. Dit staat momenteel ter discussie, want enkele onderzoeken laten zien dat er mogelijk toch nog een licht verhoogd borstkankerrisico overblijft voor deze bewezen niet-draagsters. Voor het risico op eierstokkanker in niet-draagsters uit deze families bleken helemaal geen schattingen bekend.

Het borsten eierstokkankerrisico van bewezen niet-dragers in BRCA1/2-mutatiefamilies is onderzocht in een cohort dat bekend is bij de polikliniek Familiare Tumoren in het UMCG (hoofdstuk 2). De resultaten toonden aan dat het lifetime-risico op borstkanker anderhalf maal verhoogd is in niet-draagsters in vergelijking met de algemene populatie (SIR 1.5, 95% BI 0.9-2.3). Voor eierstokkanker kon er geen risicoverhoging worden aangetoond, maar het aantal tumoren was klein en de schattingen dus niet heel betrouwbaar. De verhoging van het borstkankerrisico was meer uitgesproken in niet-dragers uit BRCA1 mutatie families (SIR 2.0, 95% BI 1.1-3.3), vooral bij vrouwen tussen 40-49 jaar (SIR 4.5, 95% BI 1.8-9.2). Op het eerste gezicht kan de sterkere toename van het risico in deze leeftijdsgroep worden beschouwd als een vertekening in deze risicoschatting omdat families naar de polikliniek Familiare Tumoren verwezen worden op basis van een belaste familiegeschiedenis met kanker op jongere leeftijd en omdat vrouwen die kanker hebben zich misschien eerder laten testen dan hun verwanten die zelf geen kanker hebben. Maar de risicoverhoging was ook aanwezig wanneer er voor deze vertekening of bias werd gecorrigeerd door middel van inclusie van een deel van de niet-geteste eerstegraads vrouwelijke verwanten.

Dit onderzoek liet zien dat bewezen niet-draagsters in BRCA1/2-mutatiefamilies toch een licht verhoogd risico op borstkanker hebben ten opzicht van de algemene bevolking. Wanneer andere onderzoeken dit bevestigen, zou het screeningsbeleid voor deze groep mogelijk aangepast kunnen worden. Er zou overwogen kunnen worden om niet-draagsters in BRCA1/2-mutatiefamilies extra controles te bieden, bijv. een jaarlijks mammogram in de leeftijd van 40 tot 49 jaar, voorafgaand aan het landelijke bevolkingsonderzoek op borstkanker.

Regionale verschillen in het borstkankerrisico van BRCA1/2-mutatiedraagsters in NederlandIn een vorige studie die ook in het UMCG is uitgevoerd, werden relatief hoge borstkankerrisico’s waargenomen voor BRCA1/2-mutatiedraagsters die bekend zijn bij de polikliniek Familiaire Tumoren in Noord-Nederland, in vergelijking met risicoschattingen op basis van een cohort van mutatiedraagsters in de rest van Nederland (Geo-Hebon cohort). Vooral het risico op borstkanker in BRCA2-mutatiedraagsters was hoog: een lifetime-risico tot leeftijd 70 van 88%, vergeleken met 27% in het Geo-Hebon cohort. Omdat beide onderzoeken niet identiek zijn uitgevoerd, is het echter moeilijk om een directe vergelijking van deze risico’s te maken.

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Om te onderzoeken of BRCA1/2-mutatiedraagsters in Noord-Nederland werkelijk een hoger borstkankerrisico hebben in vergelijking met mutatiedraagsters uit de rest van Nederland en om vertekening door verschillen in de gebruikte methodologie uit te sluiten, zijn beide Nederlandse cohorten op een identieke manier geanalyseerd en vervolgens vergeleken (hoofdstuk 3). BRCA1-mutatiedraagsters uit de rest van Nederland hadden een licht verhoogd borstkankerrisico tot de leeftijd van 75 (HR = 1.52, 95% BI 1.23-1.85) in vergelijking met die uit Noord-Nederland. Dit gold ook voor de BRCA2-mutatiedraagsters tot de leeftijd van 60 (HR = 1.56, 95 % BI 1.04-2.17). BRCA2-mutatiedraagsters in Noord-Nederland hadden vanaf de leeftijd van 60 jaar een sterker verhoogd risico in vergelijking met draagsters in de rest van Nederland (HR = 3.99, 95% BI 1.11-14.4). Toen we zochten naar een verklaring werden duidelijke verschillen gevonden in het mutatiespectrum van mutatiedraagster tussen beide gebieden, met name voor BRCA2 mutaties, maar deze bleken slechts een klein deel van de waargenomen regionale verschillen in het borstkankerrisico te kunnen verklaren.

Er bestaan verschillen in het borstkankerrisico van mutatiedraagsters in Nederland, maar deze verschillen zijn minder groot dan verwacht. Nader onderzoek naar de achtergrond van de risicoverschillen in mutatiedraagsters boven de 60 jaar is nodig om te bepalen welke van deze vrouwen misschien meer baat hebben bij extra borstcontroles buiten het bevolkingsonderzoek. Het is ook belangrijk om te onderzoeken wat de oorzaak is van het risicoverschil door bijvoorbeeld te kijken naar leefstijl, BMI en reproductieve factoren, omdat dit kan mogelijk handvaten bieden voor de counseling en advisering ten aanzien van primaire preventie.

Verschillen in toegepaste methodologie verklaren veel van de variatie in de risicoschattingen van borstkanker De schattingen van het lifetime-risico op borstkanker in BRCA1/2-mutatiedraagsters variëren wereldwijd van 27% tot 88%. Het vergelijkend onderzoek van het borstkankerrisico van BRCA1/2-mutatiedraagsters in Noord-Nederland en de rest van Nederland liet minder grote verschillen zien dan wat kan worden verwacht op basis van de afzonderlijke risicoschatting in beide studie cohorten (hoofdstuk 3). Deze observatie maakte duidelijk dat verschillen in toegepaste methodologie tussen de studies de geschatte borstkankerrisico’s beïnvloeden.

Om deze reden werden de effecten van de toegepaste methodologie voor risicoschatting en van de methode voor bias-correctie op de uiteindelijk geschatte borstkankerrisico’s bij leeftijd 70 expliciet bepaald. Dit werd gedaan door alle bruikbare methoden achtereenvolgens toe te passen op één groot cohort BRCA1/2-mutatiedraagsters dat bekend is in het UMCG. (hoofdstuk 4). De verschillende methodieken bestonden uit Kaplan-Meier analyses met en zonder ‘bootstrapping’ op familieniveau, frailty modelling en modified segregation analyses. Deze analyses werden gecombineerd met verschillende vormen van bias-correctie, zoals exclusie van index cases, inclusie van een deel van de niet-geteste eerstegraads vrouwelijke verwanten of conditionering van de likelihood functie op fenotype en genotype. In totaal werden negentien verschillende methodes toegepast en de variatie van de geschatte borstkankerrisico met deze methodieken liep uiteen van 35% tot 83% voor BRCA1 en 41% tot 86% voor BRCA2-mutatiedraagsters. Dit betekent dat een groot deel

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van de variatie in de gepubliceerde risicoschattingen kan worden verklaard door de verschillen in toegepaste methodiek en niet zozeer – zoals vaak wordt beargumenteerd – door verschillen in studiepopulaties.

Alle methodieken werden ook toegepast op 50 datasets die gesimuleerd waren op basis van de klinische data. Uit de resultaten bleek dat de Kaplan-Meier analyse met bias-correctie door inclusie van een deel van de niet-geteste eerstegraads vrouwelijke verwanten de meest geschikte en toegankelijke methode was voor risicoschatting in BRCA1/2-mutatiedraagsters die verwezen worden naar een polikliniek Familiare Tumoren. De modified segregation analyse met conditionering van de likelihood functie op het genotype van de index case en alle fenotypes in de familie resulteerde in risicoschattingen die meer geschikt zijn voor een niet geselecteerd cohort van BRCA1/2 dragers in de algemene bevolking.

Tegenstrijdig trends in eierstokkankerrisico’s Zowel in de algemene bevolking als in BRCA1/2-mutatiedraagsters komt borstkanker vaker voor in recentere geboortecohorten. Dit geboortecohorteffect hangt waarschijnlijk samen met veranderingen in levensstijl en gedrag, onder andere wat betreft hormonale en reproductieve factoren die ook in de algemene populatie van invloed zijn op het borstkankerrisico. Of voor het risico op eierstokkanker een geboortecohorteffect bestaat is niet duidelijk. Resultaten van eerdere studies naar een effect van geboortecohort op het eierstokkankerrisico bij BRCA1/2-mutatiedraagsters duidden op een toename, maar de resultaten zijn inconsistent. Een mogelijke risicotoename bij mutatiedraagsters is tegenstrijdig met de dalende trend van het risico op eierstokkanker bij vrouwen in de algemene bevolking.

In een cohort van BRCA1/2-mutatiedraagsters en in de algemene bevolking onderzochten we of er een geboortecohorteffect bestaat voor eierstokkanker (hoofdstuk 5). Onze resultaten toonden aan dat het eierstokkankerrisico in BRCA1/2-mutatiedraagsters sterker verhoogd is in recentere geboortecohorten, ook wanneer er voor bias wordt gecorrigeerd door middel van inclusie van een deel van de niet-geteste eerstegraads vrouwelijke verwanten. In de algemene bevolking bleek juist dat het risico op eierstokkanker afneemt in recentere cohorten. De gestandaardiseerde incidentieratio (SIR) voor eierstokkanker voor BRCA1-mutatiedraagsters van 20 tot 55 jaar was 1.7 maal hoger voor vrouwen die geboren waren tussen 1935-1953, en 2.7 maal hoger voor wie geboren waren na 1953, ten opzichte van mutatiedraagsters geboren voor 1935. Voor BRCA2-mutatiedraagsters was dit respectievelijk 1.6 maal en 2.4 maal hoger.

BRCA1/2-mutatiedraagsters die meer recent zijn geboren, met name vrouwen met een BRCA1 mutatie, hebben dus een extra verhoogd eierstokkankerrisico, terwijl in de algemene populatie vrouwen die meer recent zijn geboren juist een lager risico op eierstokkanker hebben dan vrouwen die eerder zijn geboren. De reden hiervoor is nog niet duidelijk. Om een meer persoonsgebonden risicoschatting te kunnen ontwikkelen is het van belang de onderliggende oorzaak van deze tegenstrijdige trends in het eierstokkankerrisico te onderzoeken. Een mogelijk verklaring die in dit kader onderzocht kan worden is een eventueel verschil in het gebruik van orale anticonceptie. Mutatiedraagsters zijn immers vaker terughoudend in het gebruik van

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hormonen en orale anticonceptiva, in verband met het gerapporteerde verhoogde borstkankerrisico. Of dat in dit cohort van BRCA1/2-mutatiedraagsters het geval was kon niet worden onderzocht.

Het effect van de overervingslijn van de BRCA1/2 mutatie op het borstkankerrisicoDraagsters van een BRCA1/2 mutatie hebben een sterk verhoogd risico op borsten eierstokkanker. Zoals bekend is het kankerrisico nog hoger als deze vormen van kanker voorkomen in de familieanamnese. Op basis van eerdere onderzoeksresultaten is daarnaast gesuggereerd dat het risico op borstkanker samenhangt met de overervingslijn van de BRCA1/2 mutatie (afkomstig van vader of van moeder). Maar dit geschatte effect kan ook vertekend zijn door bias die samenhangt met de verwijscriteria op basis waarvan vrouwen en hun familieleden worden verwezen naar de polikliniek Familiare Tumoren.

In het landelijke Hebon cohort van BRCA1/2-mutatiedraagsters is onderzocht of het borstkankerrisico van mutatiedraagsters samenhangt met de overervingslijn van de BRCA1/2 mutatie en of een dergelijk effect onafhankelijk is van de persoonlijke voorgeschiedenis en familiaire belasting van kanker (hoofdstuk 6). Uit de resultaten bleek dat de aantoonbaarheid van een effect van de overervingslijn afhangt van de manier waarop men corrigeert voor mogelijke verwijzingsbias van families en familieleden naar de kliniek. Wanneer er niet gecorrigeerd werd voor een dergelijke bias dan was de overerving van de mutatie van vader geassocieerd met een verhoging van het borstkankerrisico (BRCA1 HR = 1.54, 95%BI 1.19-2.00 en BRCA2 HR=1.40, 95%BI 0.96-2.06). Of er wel of niet gecorrigeerd werd voor de verschillende mate van familiaire belasting had geen invloed op dit risicoverhogend effect. Maar wanneer rekening werd gehouden met de persoonlijke voorgeschiedenis van kanker voordat de vrouwen verwezen werd naar de genetica en voor ze DNA-onderzoek onderging, dan was er geen effect meer van de overervingslijn (BRCA1 0.66 [95%BI 0.25-1.71] en BRCA2 1.14 [95%BI 0.42-3.15]). Mogelijk heeft deze laatste bron van genetische testing bias – eigen kanker in de voorgeschiedenis – ook de verhoging van het borstkankerrisico veroorzaakt die in eerdere onderzoeken was waargenomen bij overerving van de mutatie van vader.

Op dit moment is er geen bewijs dat overerving van de mutatie van vader het borstkankerrisico verder verhoogt. Het is belangrijk dat in vervolgonderzoek met een groter, prospectief cohort de impact van de verschillende redenen voor verwijzing naar de kliniek, dat wil zeggen de persoonlijke voorgeschiedenis én familiegeschiedenis, in één analyse wordt onderzocht.

Borstkanker screening in BRCA1/2-mutatiedraagsters ouder dan 60 jaarIn Nederland krijgen vrouwen met een BRCA1/2-mutatiedraagsters intensieve borstcontroles aangeboden van 25- tot 60-jarige leeftijd. Mutatiedraagsters boven de 60 jaar wordt geadviseerd om tot hun 75e deel te nemen aan het tweejaarlijkse landelijke bevolkingsonderzoek op borstkanker. In een beperkt aantal gevallen wordt tussen leeftijd 60 en 75 jaar jaarlijks een mammogram gemaakt in het ziekenhuis.

Het belang en de effectiviteit van borstkankerscreening in BRCA1/2-mutatiedraagsters van 60 jaar en ouder werd onderzocht in een cohort van

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mutatiedraagsters die gecounseld waren op de polikliniek Familiaire Tumoren in Rotterdam of Groningen en in het landelijke Hebon cohort (hoofdstuk 7). Meer dan 70% van de mutatiedraagters heeft op 60-jarige leeftijd nog één of beide borsten, en heeft daarom nog steeds een kans om (opnieuw) borstkanker te ontwikkelen. Meer dan de helft van de tumoren die gedetecteerd werden bij vrouwen die elke 2 jaar een mammogram kregen, hadden een ongunstige stadiëring (dat wil zeggen een tumor van meer dan 2 cm., positieve lymfeklieren of metastasen op afstand). Het percentage van tumoren met een ongunstige stadiëring was twee maal zo hoog onder tumoren die middels een tweejaarlijkse mammogram werden gedetecteerd vergeleken met tumoren die middels een jaarlijks mammogram werden gedetecteerd. Jaarlijkse mammografie na het 60e jaar kan van belang zijn voor BRCA1/2 mutatiedraagster om de kanker eerder te ontdekken.

ToekomstperspectievenVariatie in risicoschattingen wordt veroorzaakt door een combinatie van verschillen in de toegepaste methodiek en verschillen in populatiefactoren. Onderzoek in dit proefschrift laat zien dat het begrijpen van deze variatie belangrijk is voor zowel de vergelijking en interpretatie van gepubliceerde risicoschattingen als voor de ontwikkeling van meer specifieke risicoschattingen van borsten eierstokkanker voor subgroepen.

In dit proefschrift zijn verscheidene populatiefactoren onderzocht die reeds beschikbaar zijn in de kliniek: BRCA1/2-mutatiespectrum, familiegeschiedenis van borsten eierstokkanker en geboortecohort. Deze kunnen bijdragen aan het uiteindelijk vervangen van de populatie-gemiddelde risicoschattingen voor BRCA1/2 mutatie draagsters naar meer persoonsgebonden of subgroep-specifieke risicoschattingen van borsten eierstokkanker. Deze verfijnde risicoschattingen kunnen de onzekerheid omtrent risico’s verkleinen en bijdragen aan meer individuele en leeftijdsspecifieke risicocounseling en advisering over de timing van en de passende strategie voor kankerpreventie. Daarnaast kan deze verfijning van de risicoschattingen bijdragen aan de aanpak van de waarschijnlijk groeiende heterogeniteit tussen de BRCA1/2-families door veranderende verwijscriteria en de introductie van DNA-diagnostiek van tumoren. In de afgelopen jaren zijn de verwijscriteria voor genetische counseling en DNA-diagnostiek uitgebreid (diagnoseleeftijd, mate van familiaire belasting, triple negatieve borstkanker). Het meest ingrijpend in dat kader is de meest recente verandering dat alle vrouwen met eierstokkanker nu een indicatie hebben om doorverwezen te worden voor klinisch genetische counseling en DNA-diagnostiek. Door al deze veranderingen zal de mate van de familiaire belasting van de families die verwezen worden en waar een BRCA1/2 mutatie wordt aangetoond meer uiteenlopen. Daardoor zal het kankerrisico van de (onaangedane) familieleden waarschijnlijk meer variëren, en zijn verfijnde risicoschattingen nodig voor passende en persoonlijkere risicocounseling.

Een goede registratie van de families en hun mutaties, de gegevens betreffende screening en preventie en het vóórkomen van kanker is noodzakelijk om de verdere ontwikkeling van risicoschattingen op maat mogelijk te maken. Er zijn namelijk grote studiepopulaties nodig voor onderzoek naar het effect van minder penetrante

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genen (zoals CHEK2 en PALB2) en risico-modifiers (SNPs), omgevingsfactoren en de interactie tussen genetische en niet-genetische factoren. Daarnaast is een langdurige registratie en follow-up belangrijk voor een nauwkeurige risicoschatting, bij voorkeur ook voor vrouwen ouder dan 70 jaar.

Tot slot, voor de risicocounseling is het belangrijk dat naast nauwkeurige populatie-gemiddelde of subgroep-specifieke lifetime-risico’s voor de counseling ook risicoschattingen beschikbaar komen van het risico op kanker in de komende 10 jaar en het rest-risico specifiek voor BRCA1/2-mutatiedraagsters in Nederland.

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Dankwoord

Dankwoord

Daar ligt die dan. Voor een willekeurige voorbijganger gewoon een boekje, een boekje zonder enige emotionele lading. Maar voor mij, mijn proefschrift. Een bundeling van ruim 3 jaar werk, en het resultaat van vele mooie tijden en fijne samenwerkingen, maar - in alle realiteit - zo nu dan ook lastigere fases. Met veel plezier kijk ik terug op mijn promotietijd en al terugdenkend kan ik de glimlach niet van mij gezicht krijgen. Veel mensen hebben bijgedragen aan deze geslaagde tijd en de totstandkoming van dit proefschrift, waarvoor veel dank! Een aantal mensen wil ik graag in het bijzonder bedanken.

Allereerst mijn promotoren en co-promotor: prof. dr. G.H. de Bock, prof. dr. M.J.E. Mourits en dr. J.C. Oosterwijk. Het is alweer bijna vijf jaar geleden dat onze samenwerking begon. Eerst is het kader van mijn masterproject dat later uitmondde in een promotietraject en dit proefschrift. Bedankt voor alle supervisie en de fijne samenwerking deze jaren. Jullie hebben me uitgedaagd een stap verder zetten - soms verder dan ik in eerste instantie comfortabel achtte -, maar mede hierdoor heb ik vele mooie kansen gehad en veel geleerd. Het was een plezier om jullie als mijn promotieteam te hebben, met ieder een eigen specialisme, invalshoek en persoonlijkheid.

Beste Truuske, bedankt voor de enorm fijne samenwerking. Van jouw analytische denken en gestructureerde en daadkrachtige manier van werken heb ik veel geleerd. Je enthousiasme voor het onderzoek en het ‘willen weten’ werkt aanstekelijk.

Beste Marian, bedankt voor je positieve en directe insteek en je enthousiasme. Je kritische en klinische blik waren erg waardevol en maakten de stukken en de gepresenteerde data vaak toegankelijker.

Beste Jan, bedankt voor je onmisbare betrokkenheid en enthousiasme, en alle kritische vragen die het werk naar een hoger niveau tilden. Ook van de presentatie besprekingen heb ik veel geleerd. Mijn dank gaat uit naar de leden van de beoordelingscommissie, prof. dr. N. Hoogerbrugge, prof. dr. K.G.M. Moons en prof. dr. R.H. Sijmons. Hartelijk dank voor jullie bereidheid om plaats te nemen in de beoordelingscommissie, en het manuscript van dit proefschrift te lezen en te beoordelen.

Alle co-auteurs wil ik graag hartelijk bedanken voor de fijne samenwerking en hun bijdrage aan één of meerdere hoofdstukken in dit proefschrift. Tevens wil ik Jackie Senior en Kate Mc Intyre bedanken voor het werk dat zij als editoren aan de manuscripten hebben verricht. Thea Mooij, Judith de Lange en Rosemarie Wijnands, bedankt voor al jullie werk binnen Hebon en de hulp omtrent de datalevering voor een aantal artikelen/manuscripten in dit proefschrift. Ook de collega’s van de afdeling Epidemiologie wil ik graag bedanken. Roelian en Aukje, bedankt voor alle onmisbare ondersteuning en de antwoorden op vele praktische

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vragen. Van vele anderen heb ik tijdens mijn Bachelor, Master of PhD fase onderwijs gehad. In het bijzonder wil ik dr. Karin Vermeulen bedanken. Onder jouw supervisie maakte ik tijdens een leeronderzoek en later tijdens de wetenschappelijke stage kennis met epidemiologisch onderzoek. Mede hierdoor heb ik de overstap gemaakt naar de onderzoekmaster CPE, wat een zeer goede keuze is gebleken.

Dear colleagues of ‘the 4th floor’, thank you for the good times, nice conversations and chats at the department or during diners, BBQ and drinks.

Nienke, Leo, Maryam, Renske and Ingrid, at some point we shared the office. Nienke, it is a while ago. At that time I was a master student; thank you for showing me the ropes. Maryam, we knew each other from the master but got to know each other better during our PhD years. Thank you for the chats, advice, and discussions. I really appreciate it! Leo, Ingrid and Renkse, we were shared the office only for a limited amount of time. It was great to discuss ‘koetjes en kalfjes’ but also the whole PhD process.

Dear members of the unit cancer epidemiology, I really enjoyed and appreciated our meetings and discussions. It was great to have this environment and to learn from each other. Whether this was statistics, issues on breast cancer screenings, healthcare, Portuguese, making Vietnamese springrolls or something else. Many thanks!

Rositsa and Anh, I enjoyed our regular lunch breaks which was a moment to relax and to take my mind of work. Thanks!

Een hele grote dank gaat ook uit naar mijn familie en vrienden. Op de cursus- en congresbezoeken na, zal voor velen mijn werk en wat ik nu doe op een werkdag vaak weinig concreet zijn geweest. Desondanks kon ik bij jullie altijd mijn verhaal kwijt, en deelden jullie de vreugde van wanneer bijvoorbeeld een artikel geaccepteerd was voor publicatie. Daarom vind ik het ook ontzettend leuk dat hier nu iets tastbaars voor jullie ligt. Het resultaat van al dat werk waar jullie op afstand iets van meekregen en aan bijdroegen.

Pap en mam, het is alweer even geleden dat ik de studie Geneeskunde achter me liet en volledig koos voor het onderzoek. Op dat moment was het een beetje een verrassing, maar jullie hebben me altijd gesteund en daar ben ik enorm blij mee. Jullie wijze raad van tijd tot tijd is onmisbaar. Mijn grote zus en broers, wat ben ik trots op jullie. En wat ‘kijk ik graag af’ van jullie ervaring en wijsheid.

Mijn paranimfen, Esther en Marieke. Wat ben ik blij dat jullie mijn paranimfen zijn!Esther, we kennen elkaar sinds de onderzoekmaster en al snel kwamen we tot de

conclusie dat wij goed samen konden werken. Deze samenwerking is uitgegroeid tot een vriendschap. Je nuchtere raad op mijn geratel en de gezellige lunches en uitstapjes, dat waardeer ik zeer.

Marieke, ook zo heerlijk nuchter, en een doorzetter. We kennen elkaar sinds de studententijd en jij hebt van de zijlijn dus ook veel van mijn studie- en promotietraject

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Dankwoord

meegekregen. Onze vele bakjes koffie en etentjes waren altijd een moment om te ontspannen en weer op te laden.

Anje en Carla, wat ben ik blij met onze vriendschap. De ontbijtjes, bakjes koffie, de relax-avondjes, etentjes en uitstapjes waren absolute ontspanmomentjes. Alles kunnen bespreken, maar ook gewoon niets hoeven en lekker chillen.

Annet, jij begon één jaar eerder met je promotieonderzoek. Erg fijn om zo’n ervaringsexpert te hebben, en wat heb je het ook goed gedaan! Ik kijk met veel plezier terug op onze koffie/thee-momentjes aan het eind van de dag. Bedankt voor het lezen en corrigeren van mijn samenvatting.

Er is maar één passend slotwoord, gericht aan iedereen die wel of niet met naam is genoemd: bedankt!

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Curriculum Vitae

About the author

Janet Vos was born on July 27th 1987 in Emmeloord (Noordoostpolder), the Netherlands. She graduated from secondary school at the Emelwerda College in Emmeloord in 2005. In September 2005 she started her study Technical Business Administration at the University of Twente and obtained the Propaedeutic degree. After that she continued her education at the University of Groningen where she started her study Medical Education in September 2006 and obtained her Bachelor’s degree in 2009. Subsequently she conducted the Master’s program research project on the topic of ‘Social participation after lung transplantation’ at the department of Epidemiology supervised by Dr. K.M. Vermeulen.

In September 2010 she started her Research Master studies Clinical and Psychosocial Epidemiology at the University of Groningen, and in 2012 she obtained her Master’s degree cum laude. Her Master research project entitled ‘Breast cancer in BRCA1/2 mutation carriers: explaining differences in risk and age at diagnosis.’ was supervised by Prof. Dr. G.H. de Bock (epidemiologist), Prof. Dr. M.J.E. Mourits (gynaecologist) and Dr. J.C. Oosterwijk (clinical geneticist) and was conducted at the department of Epidemiology, University Medical Center Groningen. She continued her research on risk estimations of breast and ovarian cancer in BRCA1/2 families, since her PhD project proposal on this topic was awarded with funding from the Graduate School of Medical Sciences. Her PhD project started in September 2012 and was again supervised by Prof. Dr. G.H. de Bock, Prof. Dr. M.J.E. Mourits and Dr. J.C. Oosterwijk. The manuscript of this thesis was submitted to the reading committee in October 2015 and will be defended at March 14th, 2016

During her PhD project she finished her training to obtain the registration as Epidemiologist B by the Netherlands Epidemiological Society. In April 2015 she will start her post-doc research.

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Appendices

Publications

2015 Vos JR, Mourits MJE, Teixeira N, Jansen L, Oosterwijk JC, de Bock GH. Inversebirth cohort effects in ovarian cancer: increasing risk in BRCA1/2 mutation carriers and decreasing risk in the general population. Gynecologic Oncology 2015, doi: 10.1016/j.ygyno.2015.11.029

Vos JR, Hsu L, Brohet RM, Mourits MJE, de Vries J, Malone KM, Oosterwijk JC, de Bock GH. Bias correction methods explain much of the variation in the breast cancer risks of BRCA1/2 mutation carriers. Journal of Clinical Oncology 2015; 33:2553-2562.

Teixeira N, Mourits MJE, Vos JR, van der Kolk DM, Jansen L, Oosterwijk JC, de Bock GH. The impact of a family history of cancer on the ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Maturitas 2015;82:197-202.

2014 Vos JR, Teixeira N, van der Kolk DM, Mourits MJE, Rookus MA, van Leeuwen FE, Collée M, van Asperen CJ, Mensenkamp AR, Ausems M, van Os TAM, Meijers-Heijboer HEJ, Gómez-Garcia EB, Vasen HF, Brohet RM,HEBON, van der Hout AH, Jansen L, Oosterwijk JC, de Bock GH. Variation in mutation spectrum partly explains regional differences in the breast cancer risk of BRCA mutation carriers in the Netherlands. Cancer Epidemiology Biomarkers and Prevention 2014; 23:2482-2491.

Saadatmand S, Vos JR, Hooning MJ, Oosterwijk JC, Koppert LB, de Bock GH, Ausems MG, van Asperen CJ, Aalfs CM, Gómez Garcia EB, Meijers-Heijboer H, Hoogerbrugge N, Piek M, Seynaeve C, Verhoef C, Rookus M, Tilanus-Linthorst MM, HEBON. Relevance and efficacy of breast cancer screening in BRCA1 and BRCA2 mutation carriers above 60 years: a national cohort study. International Journal of Cancer 2014;135:2490-2499.

2013 Vos JR, de Bock GH, Teixeira N, van der Kolk DM, Jansen L, Mourits MJE, Oosterwijk JC. Proven non-carriers in BRCA families have an earlier age of onset of breast cancer. European Journal of Cancer 2013;49:2101-2106.

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Curriculum Vitae

Selected presentations

2015 ‘Breast cancer risks of BRCA1/2 carriers: the combined effect of family history and the line of inheritance’. Oral presentation at a pre-conference symposium, and a poster presentation, Translating Cancer Epidemiology, Salt Lake City, Utah, USA, October 2015.

2014 ‘Breast Cancer Risk Estimation Methods in a Clinic-based Cohort of BRCA1/2 Mutation Carriers’. Oral presentation plenary session, BRCA symposium, Montreal, Canada, April 2014.

2013 ‘Regional differences in the breast cancer risk of BRCA1/2 mutation carriers in the Netherlands’. Presentation plenary session, Genetic Retreat, Kerkrade, The Netherlands, March 2013.

‘Proven non-carriers in BRCA families have an earlier age of onset of breast cancer’. Oral presentation plenary session, International Student Congress of (bio)Medical Sciences, Groningen, The Netherlands, June 2013.

2012 ‘Regional influences partially explain the high breast cancer risk of BRCA1/2 mutation carriers in the Northern Netherlands’. Oral presentation plenary session Brazilian International Congress of Medical Students, São Paulo, July 2012.

‘Regional influences partially explain the high breast cancer risk of BRCA1/2 mutation carriers in the Northern Netherlands’. Oral presentation parallel session, International Student Congress of (bio)Medical Sciences, Groningen, The Netherlands, June 2012.

2011 ‘Social participation after lung transplantation’. Oral presentation parallel session, Health Insurance days, Almere, The Netherlands, November 2011.

Grants

2015 Travel grant Conference Translating Cancer Epidemiology, Salt lake City,Utah, USA.Travel grant. Stichting Simondsfonds.

2014 Travel grant for academics. Dutch Cancer Society

2013 Course grant. Stichting Het Scholten-Cordes fonds

2012 PhD research grant. Graduate School of Medical Sciences, University Medical Center Groningen.

Travel grant Brazilian International Congress of Medical Students. Graduate School of Medical Sciences, Groningen.

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