Breast Cancer Research and Treatment, 5,171-176 (1985) © 1985, Martinus Nijhoff Publishers, Boston. Printed in the Netherlands

Report

Seasonal variation in breast cancer detection: correlation with tumour pro- gesterone receptor status

B.H. Mason, BSc, I.M. Holdaway, MD, FRACP, P.R. Mullins, MSc, R.G. Kay, FRCS, FRACS, S.J. Skinner, PhD Departments of Surgery, Endocrinology, and Community Health, University of Auckland, School of Medi- cine, Auckland, New Zealand.

Keywords: breast cancer detection, seasonal variation, steroid receptors.

Summary

A significant circannual variation of the month in which patients detect the first sign or symptom of tumour has been defined in 1413 patients with breast cancer. The months of highest detection were in the late spring- early summer, and lowest detection was in late autumn-early winter. Analysis of subgroups indicates that this cyclic trend was most significant in younger women with small or moderate-sized tumours containing steroid hormone receptors, particularly progesterone receptors. It seems likely that this variation is related to the effect of cyclic hormonal changes on tumour growth, possibly mediated through the pineal.

Introduction

A seasonal variation in the month when patients first detect breast cancer was initially described by Lee (1) and later confirmed by Cohen et al. (2). The time of maximum rate of detection Was late spring and early summer, and the phenomenon was more pronounced in premenopausal women. The cause of this seasonal variation has yet to be established, although a number of hormonal factors potentially involved in the maintenance of breast cancer are known to undergo seasonal change. First, in a pro- visional report, Hrushesky et al. (3) found that oestrogen receptor protein present in breast tu- mours fluctuated between highest levels in tumours biopsied in autumn and lowest in tumours sampled in spring. Second, the night-day cycle acts via the optic pathways to influence the secretions of the pineal. The principal pineal hormone, melatonin,

is suppressed by daylight. Melatonin inhibits the release of gonadotrophin releasing factor from the hypothalamus with suppression of production of gonadotrophins by the anterior pituitary. The pineal also produces a prolactin-inhibiting factor and/or prolactin-releasing factor which has a direct effect on the production of prolactin by the anterior pituitary (4). Melatonin has a seasonal subrhythm (5) and may affect pituitary (6), ovarian (7), and adrenal (8) secretion. Cohen et aI. have suggested that the hyposecretion of melatonin with resulting increases in production of gonadotrophins, oestrogen, and progesterone, will consequently stimulate breast tissue (9). The present study re-ex- amines the question of seasonal variation in detec- tion of breast cancer in a population from the southern hemisphere, and investigates some of the hormonal factors that may be relevant. It is impor- tant to recall that in the Southern Hemisphere

Address for offprints: Barbara Mason, Department of Surgery, University of Auckland, School of Medicine, Park Road, Grafton, Auckland, New Zealand.

172 B H Mason et al.

winter is from June to August, and summer from December to February.

Methods

Computerised records of all new breast cancer cases in Auckland, New Zealand (1982 population: 829,000) have been maintained since 1976. Data for this file is obtained from hospital notes, family physician records, and postal questionnaire to pa- tients. The data is stored on an IBM 4341 compu- ter. 1756 patients with breast cancer were recorded between September 1976 and September 1982. In- formation recorded includes date of first sign or symptom of breast cancer as discovered by the patient, the number of axillary nodes infiltrated with tumour as found by histological examination, a clinical measurement of the size of the tumour, patient age, the concentration of oestrogen and progesterone receptors in the primary tumour, and pre-operative measurements of serum prolactin and urine androgenic/glucocorticoid steroid ratios (urinary discriminant (10) ratio) performed on samples collected within ten days of surgery. Pa- tients who had receptor studies performed follow- ing administration of chemotherapy or radiation treatment were excluded from the receptor analy- sis.

The urinary discriminant ratio was determined by the measurement of the 11-deoxy-17-oxosteroids (ll-DOS) expressed as a ratio in comparison with the total 17-hydroxycorticosteroid metabolites in a 24 hour urine collection. The measurement of ll-DOS involves enzymic and solvolytic hydrolysis of the glucuronide and sulfate conjugates, solvent partition to remove the bulk of the ll-oxy-17-oxo- steroids, and colorimetric estimation of the re- maining ll-DOS by the Zimmerman reaction (10). Discriminant ratio measurements were considered 'positive' if > =0.14 (11). Oestrogen and pro- gesterone receptors were measured in tumour tissue by a dextran-charcoal method as detailed elsewhere (12). In brief, tumour samples were ob- tained at surgery, kept on ice, frozen within 60 minutes, and stored at -70 ° C. Frozen tissue was pulverized, the resulting powder homogenised with buffer, and cytosol extract obtained by ultra-

centrifugation. Oestrogen and progesterone recep- tors were determined by dextran-charcoal assay using a single saturating dose of labelled hormone, results with this system showing excellent correla- tion with assessment by Scatchard analysis (12). On the basis of clinical response data (13), oestrogen receptor levels were considered negative if <5 fmol/mg, and progesterone receptor levels were considered negative if <3 fmol/mg (14). Prolactin was measured by radioimmunoassay (15), and lev- els were classed as either detectable (> = 1 ng/ml) or non-detectable (<lng/ml).

Statistical Methods: Edwards' test for cyclic vari- ation was used to determine the significance of any seasonal variation (16). For samples with total numbers less than 100 the significance test of Roger (17) adapted from Edwards (16) was used. The statistic used determines a simple harmonic cyclic trend. A circle is divided into twelve equal sectors. The monthly frequencies are represented by co-or- dinates (xiYi) placed in the corresponding sectors in the circle. The co-ordinates are computed as fol- lows: x i = ~ / N i sin0i, y = N / N i COS0i, where 0 = the angle between an arbitary diameter to the bisector of the segment, Ni = monthly frequencies (i = 1 . . . 12) and N = ~N i. The mean of these points is the central reference point. The further from the cen- tre of the circle this point lies, the stronger the cyclic trend. The direction of the movement of the central reference point also indicates the season where the peak of the frequencies occurs. The test statistic is 1/2a2N where a = 4d, and d = %/(}~ %/N i sin0~ + ~ X/N~ cos0i)/~ N/Ni . This is approximately distributed as chi-squared with 2 degrees of free- dom.

Results

Breast cancer was diagnosed in 1756 patients dur- ing the six year period 1976-82. Of these, 1481 women had clearly stated the month when the first feature of breast cancer became apparent. In New Zealand summer is from December to February, autumn March to May, winter June to August and spring September to November. In 68 patients the initial sign or symptom had been present for more than 18 months prior to presentation, and these

patients were excluded from the study because of the possible inaccuracy of recall over such a long period. The mean time from discovery of the lump to surgery was 3 months.

The distribution of month of detection of the first sign or symptom of cancer by the patient is shown in Figure 1. There was a significant annual cyclic variation in month of detection with the month of highest detection being November and the month of lowest detection being May. Of the 1413 patients available for study, 1076 had histologically con- firmed axillary nodal status, tumour size was known in 1378 patients, and age was recorded in all cases. The influence of these variables on the an- nual variation in monthly detection rate is shown in Table 1. The cyclic trend was similar in patients above or below age 50, with the months of highest detection being November and December, respec- tively. However, there was no significant cyclic trend in month of detection in patients with tu- mours greater than 5 cm in diameter, or in patients with tumour in the axillary nodes. A significant cyclic variation in month of detection of cancer was still present in node-negative patients and in pa- tients with tumours <5 cm diameter.

Oestrogen receptor (ER) measurements were available in tumours from 711 patients and pro- gesterone receptor (PR) measurements were avail- able from 647 patients. Receptor-positive and re- ceptor-negative subgroups of women aged 50 years or over showed no significant annual cyclic varia- tion in month of detection of cancer (Table 2).

Seasonal variation in breast cancer 173

NUMBER OF CASES

160-

140-

120-

100-

80-

60-

40-

20-

0

-7-

i i

i i

i I i

, i

J F i M I A i M J J A S O N DI

MONTH WHEN FIRST SIGN OR SYMPTOM DETECTED

Fig. 1. Month of appearance of initial sign or symptom of breast cancer. Data expressed as 2 month moving average, n = 1413. Summer - December to February. Winter - June to August. There is a significant cyclic variation in monthly rate of first detection as assessed by Edward's test, p<0.001.

Table 1. Month and season with highest rate of first detection of breast cancer in selected subgroups by age, axillary node status, and tumour size.

Patient subgroup Number of %z p Month (and season) of highest patients detection

Age <50 yrs 400 11.5 <0.005 November (spring) Age >=50yrs 1013 10.8 <0.005 December (summer) Node positive* (tumour present) 435 3.1 ns Node negative (tumour absent) 641 12.5 <0.005 December (summer) Tumour size ---<5 cm 1151 22.9 <0.001 December (summer) Tumour size >5cm 227 0.5 ns

* histological examination of nodes in surgical specimen. X 2 = chi-squared. P = significance.

174 B H Mason et al.

However, women under age 50 with either PR-positive or ER-positive tumours continued to show a significant cyclic variation in month of de- tection of cancer (Table 2, Figure 2). This variation was not seen in receptor-negative patients less than age 50.

Hormonal measurements in the total patient group were examined for seasonal variation. There was a significantly higher frequency of undetecta- ble serum prolactin measurements in spring months, but there was no significant cyclic trend in urinary discriminant ratio measurements (Table 3).

Fig. 2. Month of appearance of initial sign or symptom of breast cancer; women <50 yrs, tumour progesterone receptors pres- ent. Data expressed as 2 month moving average, n = 113. Sum- m e r - December to February. W i n t e r - June to August. There is a significant cyclic variation in monthly rate of first detection as assessed by Edward 's test, p<0.05.

NUMBER OF CASES

3

11

10-

5-

J F 0

14

13

12

0 0

7

6 6 6

5

M A M J J A S 0 N D

MONTH WHEN FIRST SIGN OR SYMPTOM DETECTED

Table 2. Month and season with highest rate of first detection of breast cancer in selected subgroups by age and presence of tumour steroid receptors.

Patient subgroup Number of ;(2 p Month (and season) of highest patients detection

Age <50 yrs E R positive 113 6.09 <0.05 January (summer) PR positive 113 14.97 <0.05 December (summer)

Age =>50 yrs E R positive 167 2.12 ns PR positive 226 2.5 ns

;(2 = chi-squared.

P = significance.

Table 3. Month and season with highest rate of first detection of breast cancer in relation to serum prolactin levels and urinary discriminant ratio.

Patient subgroup Number of ;(2 p Month (and season) of highest patients detection

Serum prolactin undetectable Serum prolactin _->1 ng/ml Urinary discriminant ratio =>0.14 Urinary discriminant ratio <0.14

20 9.70 <0.01 October (spring) 86 3.99 ns - 63 2.93 ns - 49 2.08 ns -

;(2 = c h i - s q u a r e d .

P = s i g n i f i c a n c e .

Discussion

The present resutts confirm the reports of Lee (1) and Cohen (2) indicating a significant circannual variation in the month in which patients detect the first symptom or sign of breast cancer. As in the previous reports, the months of highest detection were in the summer. This is important since the present patients were studied in the southern hemi- sphere where summer occurs December to Febru- ary, in comparision with the northern patients of Lee and Cohen (1, 2). The variation was restricted to node-negative patients with small or moderate sized tumours 5 cm or less and was most marked in young women with progesterone receptor-positive tumours and, to a lesser extent, oestrogen recep- tor-positive tumours.

The presence of steroid receptors indicates an increased likelihood that a tumour may be hor- mone responsive (14, 18). The higher frequency of PR-positive and ER-positive turnouts in young women first detecting their breast cancer in sum- mer suggests that a hormonal factor may stimulate turnout growth in endocrine-responsive tumours at this time, leading to more ready detection of the tumour by the patient. Seasonal changes in gonadal activity in premenopausal women could result in cyclic stimulation of receptor-positive, hormone- sensitive tumours. Alternatively, hormones from non-gonadal sources such as the adrenal, pituitary, or vitamin D stores could directly influence tumour growth. Since the seasonal variation in detection is also seen, although to a less significant extent, in older women, hormonal mechanisms independent of the gonad may well be operating. The monthly cyclic change in gonadal steroid production in pre- menopausal women with breast cancer could also contribute to cyclic changes in tumour growth, al- though any such trend would have a shorter cycle than the seasonal variations shown above.

Cyclic changes in me!atonin could explain the results seen in this study. Production of this hor- mone has a pronounced diurnal rhythm on which is superimposed a seasonal variation (5). Melatonin acts at the hypothalamic and probably at the ovarian level to mediate the suppressive effect of short photoperiod on reproductive function (6).

Seasonal variation in breast cancer 175

Melatonin or other pineal factors may thus influ- ence gonadotrophins, ovarian secretion directly (7), ACTH-adrenal function (8), or prolactin se- cretion (4), all of which could contribute to seaso- nal changes in tumour growth rate in hormonally sensitive turnouts and lead to higher detection rates at times of growth stimulation. The cyclic trends in prolactin observed in the present study could affect tumour growth either directly or by influencing ovarian steroid synthesis (19). However, since a mean period of 3 months separated prolactin sam- pling from time of first detection, the patho- physiological significance of the trend in prolactin levels remains uncertain.

Breast cancer is usually found after showering or bathing, although in 10% of cases the presenting symptom is pain (20). There is therefore no reason to believe that the wearing of lighter clothing in summer has any relevance to seasonal changes in detection rate.

It remains uncertain whether the seasonal changes in patient detection of breast cancer seen in this study are related to hormonal or other bio- logic factors. However, since the changes were strikingly related to tumour hormone receptor con- tent, it seems likely that cyclic hormonal variation is at least one important contributing factor.

Acknowledgements

The authors thank P.L. Trindall, R. Rodgers, J. Winger, L.H. Yee, and H.J. Cook of the Auckland Breast Cancer Study Group for data collection.

Supported by the Medical Research Council of New Zealand and the Auckland Division of the Cancer Society of New Zealand.

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