new users of metformin are at low risk of incident cancer

7/30/2019 New Users of Metformin Are at Low Risk of Incident Cancer

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New Users of Metformin Are at Low Risk ofIncident Cancer

A cohort study among people with type 2 diabetes

GILLIAN LIBBY, MSC1LOUISE A. DONNELLY1

PETER T. DONNAN, PHD1

DARIO R. ALESSI, PHD2ANDREW D. MORRIS, FRCP3

JOSIE M.M. EVANS, PHD1

OBJECTIVE The antidiabetic properties of metformin are mediated through its ability toactivate the AMP-activated protein kinase (AMPK). Activation of AMPK can suppress tumorformation and inhibit cell growth in addition to lowering blood glucose levels. We tested thehypothesis that metformin reduces the risk of cancer in people with type 2 diabetes.

RESEARCH DESIGN AND METHODS In an observational cohort study usingrecord-linkage databases and based in Tayside, Scotland, U.K., we identified people with type 2diabetes who were new users of metformin in 19942003. We also identified a set of diabeticcomparators, individually matched to the metformin users by year of diabetes diagnosis, who

had never used metformin. In a survival analysis we calculated hazard ratios for diagnosis ofcancer, adjusted for baseline characteristics of the two groups using Cox regression.

RESULTS Cancer was diagnosed among 7.3% of 4,085 metformin users compared with11.6% of 4,085 comparators,with median times to cancer of 3.5and 2.6years,respectively (P0.001). The unadjusted hazard ratio (95% CI) for cancer was 0.46 (0.400.53). After adjustingfor sex, age, BMI, A1C, deprivation, smoking, and other drug use, there was still a significantlyreduced risk of cancer associated with metformin: 0.63 (0.530.75).

CONCLUSIONS These results suggest that metformin use may be associated with areduced risk of cancer. A randomized trial is needed to assess whether metforminis protective ina population at high risk for cancer.

Diabetes Care 32:16201625, 2009

Recent research suggests that the an-tidiabetic drug metformin, whichexerts its effects by activating the

AMP-activated protein kinase (AMPK),may have potential for the treatment ofcancer in humans(1). The hypothesis thatmetformin may have anticancer effects issupported by laboratory studies showingthat metformin is associated with reducedincidence of pancreatic cancer in ham-sters (2) and delays onset of mammary (3)and other tumors (4) in tumor-pronemice. Metformin also inhibits growth of

human breast cancer cells (5). Althoughthe potential for prevention of cancer in

humans using metforminhas not been ex-plored, we previously reported the resultsof a pilot case-controlstudythat identified areduced risk of cancer among patients withtype 2 diabetes who had used metformin(6). However, the outcome was limited tohospital admissions for cancer, and the dateof diagnosis was assumed to be date of firsthospital admission.

Other diabetic drugs may also havecancer-related effects. An independentepidemiological study found that users ofsulfonylureas were at higher risk of

cancer-related mortality than metforminusers (7). Sulfonylureas (and insulin)

increase circulating insulin levels, andhyperinsulinemia may promote carcino-genesis (8). Treatments such as met-formin and glitazones reduce insulinresistance, with insulin resistance possi-bly associated with increased risk of can-cer (9). The objective of this study was totest the hypothesis that metformin use isassociated with a reduced risk of cancer inpeople with type 2 diabetes using a nationalcancer registry to ensure valid diagnoses ofcancer with precise dates of diagnosis. Wealso adjusted results for the effects of expo-

sure to other diabetic drugs.

RESEARCH DESIGN AND

METHODS This observational his-torical cohort study was carried out usinganonymous patient data for the residentpopulation of Tayside Health Board inScotland, U.K. (400,000 people). Datawere provided by the Health InformaticsCentre (HIC), University of Dundee,which hasdeveloped therecord linkage ofmultiple routinely collected datasets forresearch. Scottish Care Information

Diabetes Collaboration (SCI-DC; for-merly known as the Diabetes Audit andResearch in Tayside Scotland [DARTS]) isa validated population-based diabetesregister with detailed clinical information(10). A pharmacoepidemiological data-base (formerly known as the TaysideMedicines Monitoring Unit [MEMO]drug safety database) holds computerizedrecords of every diabetic drug dispensedto residents of Tayside, Scotland, U.K.,since 1993 (11). Scottish MorbidityRecord 6 (SMR6) is a national database of

all diagnoses of cancer (12). Computer-ized death certification records from theRegistrar General with ICD9/ICD10-coded causes of death (13,14) were alsoavailable. All HIC data are anonymizedprior to analysis to maintain confidential-ity and conform to data protectionlegislation.

The DARTS database was used toidentify patients who were diagnosedwith type 2 diabetes in Tayside, Scotland,U.K., before 2004 (patients diagnosedover the age of 35 years and younger pa-tients with no insulin requirement are

From the1Division of Clinical and Population Sciences and Education, University of Dundee, Dundee, U.K.;the 2School of Life Sciences, University of Dundee, Dundee, U.K.; and the 3Diabetes Research Centre,University of Dundee, Dundee, U.K.

Corresponding author: Josie M.M. Evans, [email protected] 5 December 2008 and accepted 30 May 2009.Published ahead of print at http://care.diabetesjournals.org on 29 June 2009. DOI: 10.2337/dc08-2175. 2009 by the American Diabetes Association. Readers may use this article as long as the work is properly

cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be herebymarked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

See accompanying editorial, p. 1748.

E p i d e m i o l o g y / H e a l t h S e r v i c e s R e s e a r c hO R I G I N A L A R T I C L E

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classified as having type 2 diabetes). Weidentified patients who received a firstmetformin prescription any time between1 January 1994 and 31 December 2003(excluding patients who received met-formin in 1993 or before diabetes diagno-sis). We classified these patients asmetformin users anddefined theindex date

as date of first metformin prescription. Pa-tients who had a record of cancer in SMR6at any time between 1980 and the indexdate were excluded.

Comparator patients individuallymatched to the metformin users weregenerated at random from a pool of pa-tients with type 2 diabetes who had norecord of metformin use. We used a com-puter algorithm that identified compara-tors for each metformin user (listed inrandom order). For each metformin user,a potential comparator was identified

with the same year of diagnosis and as-signed the same index date. Year of diag-nosis was chosen as a matching variable tocontrol for effects of treatment patternsthat could vary over time but not be mea-sured directly. However, if there was arecord of cancer in SMR6 prior to the in-dex date, or if they had died, the compar-ator was discarded (but was potentiallyavailable for a different metformin user).This process was repeated until suitablecomparators were identified. The compara-tors who were identified for metformin us-ers were therefore diagnosed with diabetes

in the same year and survived until the in-dex date without cancer (the date that thecorresponding metformin user startedmetformin). Any potential survival bias(metformin users surviving to go on to met-formin) was thus eliminated.

Baseline data were collated for allmetformin users and comparators: age atindex date, age at diagnosis of diabetes,sex, smoking status, mean BMI and A1Cduring the study period, and use of sulfo-nylureas or insulin within 3 months or 1year of the index date, respectively. An

area-based measure of material depriva-tion (Carstairs score [15]) based on fourvariables from the national census (carownership, unemployment, overcrowd-ing, and head-of-household job classifica-tion) was also used.

Main outcome measuresWe followed-up all patients from the in-dex dates for predefined outcomes. Theprimary outcome was diagnosis of cancer(as recorded in SMR6). Time to outcomewas defined as the period from index dateto 1) date of diagnosis of cancer in SMR6,

2) date of death if no cancer diagnosis, or3) end of the study (31 December 2003) ifno cancer diagnosis.

Secondary outcomesWe evaluated the risks of the followingsecondary outcomes: diagnosis withbowel cancer (ICD9 153154, ICD10

C18C20), lung cancer (ICD9 162,ICD10 C33C34), or breast cancer inwomen (ICD9 174, ICD10 C50) as wellas all-cause mortality and mortalityfrom cancer (any mention on deathcertificate).

Statistical methodsTime from index date to outcome in thecohorts was shown using Kaplan-Meierplots. The proportional hazards assump-tion was examined using log (log) sur-vival plots, with parallel lines indicating

that the assumption was reasonable. Therelationship between metformin use anddiagnosis of cancer was assessed in an un-adjusted Cox regression analysis and thenin a multivariable model adjusted for ageat index date, sex, smoking status, depri-vation, mean BMI and A1C during thestudy period, and use of sulfonylureasand insulin. These were all treated as cat-egorical variables (as defined in Table 1)with the exception of A1C and BMI,which were treated as continuous vari-ables. The analyses were stratified by yearof diagnosis (the matching variable).

Dose-response analysesFor each metformin user, we identifiedthe maximum metformin dose prescribedduring follow-up. We then categorizedthese as low dose (50% of maximumprescribable dose), medium dose (5080% of maximum prescribable dose), andhigh dose (80%). The risks associatedwith each dose level were determined in astratified analysis with adjustments for allcovariates. However, in case of confound-ing by duration of follow-up, we further

stratified patients according to length oftime in the study.Ethical approval was obtained from

the multicenter research and ethics com-mittee for Scotland.

RESULTS There were 13,344 pa-tients alive in January 1993 who were di-agnosed with type 2 diabetes in Tayside,Scotland, U.K., before 2004, of which12,255 were eligible for the study. Weidentified 5,183 patients who received afirst prescription for metformin after1994 and selected 4,944 for whom there

was no cancer diagnosis prior to met-formin use. The remaining patients were5,883 patients who received no met-formin prescriptions between 1993 and2004 and 1,189 patients who received aprescription for metformin in 1993.These latter patients were excluded as thedate of starting metformin was unknown

(no prescribing data available prior to1993). Figure 1 shows how patients wereselected for the study.

Metformin users and comparatorsThe computer algorithm was used toidentify comparators for the 4,804 met-formin users who were aged35 years attheir index date. The comparators wereidentified from the 5,773 patients whowere aged 35 years and had no recordof metformin use. A comparator was suc-cessfully identified for 4,364 users (the

remaining 440metformin users for whomcomparators could not be found were ex-cluded). However, all further analyseswere restricted to the 4,085 metforminusers who had more than one prescrip-tion for metformin and their respectivecomparators.

The baseline characteristics of the twogroups are presented in Table 1. Met-formin users were younger than theircomparators and slightly more likely to becurrent smokers (although smoking sta-tus was unavailable for about one-quarterof study subjects). BMI and A1C values

were also unavailable for 3 and 9% ofstudy subjects, respectively, who weretherefore assigned the mean values. Met-formin users had higher mean values ofBMI and A1C. There was a much higherproportion of metformin users who weretreated with sulfonylureas within 3months but a lower proportion who usedinsulin within a year. These differenceswere all statistically significant.

Main outcome measuresCancer was diagnosed among 297 (7.3%)

of the metformin users during follow-up,compared with 474 (11.6%) of the com-parators. Median time to cancer was 3.5years (interquartile range [IQR] 2.15.8)for metformin users, compared with 2.6years (1.24.1) for comparators. Figure 2shows the Kaplan-Meier plot for diagno-sis of cancer (log-rank test P 0.001).The proportional hazards assumptionwas met for all study subjects.

The unadjusted Cox regression anal-ysis showed a statistically significant re-duction in the risk of cancer in the newmetformin users with a hazard ratio (HR)

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(95% CI) 0.46 (0.400.53) (Table 1). In-creased cancer risk was observed amongmen and with increasing age. It also ap-peared that higher BMI and A1C were as-sociated with a reduced risk of cancer.This is difficult to explain but may be a

diagnostic bias, with high BMI and A1Cindicative of less frequent health careseeking behavior.

In the multivariable analysis, theadjusted HR (95% CI) increased to 0.63(0.530.75) for metformin users. Never

and ex-smokers were at reduced risk ofcancer, but the reduced risks associatedwith increased BMI and A1C were lessmarked. No statistically significant ef-fects were observed for use of sulfonyl-ureas or insulin.

Figure 1Flowchart showing how metformin users and comparators were selected for the study.

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Secondary outcomesThe unadjusted and adjusted risks of thesecondary outcomes are presented in Ta-ble 2. Metformin users were at muchlower risk of overall mortality and cancer-related mortality than their comparators.Overall, 14.9% of metformin users died,compared with 34.8% of the comparators.The median survival times were 3.6 years

(IQR 2.25.9) and 2.8 years (1.44.3), re-spectively.Additionally,3.0% of metforminusers died from cancer, compared with6.1% of comparators. Reduced risks ofmagnitude similar to that for all cancerswere observed for bowel cancer, lung can-cer, and breast cancer, although the resultswere not all statistically significant.

Dose-response analysisThe stratified analysis formaximum dose isalso presented in Table 2. Although none ofthe risks for low, medium, and high dosesstratified by length of follow-up were signif-

icantly different from each other (as indi-cated by overlapping CIs), there was a cleartrend for metformin users to have a higherrisk of cancer in the first 2 years of follow-up.After this, amongpatients with the sameduration of follow-up, the risk appeared tobe lower with the highest metformin doses.

CONCLUSIONS This study sup-

ports the hypothesis that users of met-formin are at lower risk of cancercompared with people with type 2 diabeteson other treatments. Fewer than 8% of acohort of metformin users were diagnosedwith cancer during a maximum of 10 yearsof follow-up, compared with 11% of a com-parator cohort of nonusers. The mediantime to cancer was 3.6 years among met-formin users, compared with 2.5 yearsamong comparators, and they also had re-duced overall and cancer-related mortality.

This was an observational study;therefore, we could not control for all dif-

ferences between study groups. Met-formin users could have been at lowerbaseline risk of cancer than the compara-tors. Indeed, they were younger than theircomparators (but mean BMI and A1Cwere higher). Metformin users did seemto be a different group clinically fromnonusers, with a much lower rate of mor-tality (some of which could be explained

by lower risk of cardiovascular mortality[16]). Although this limitation is inherentin the observational nature of the study,we adjusted results for known potentialconfounders and there were sizablechanges to the risk estimates. There maystill have been residual confounding orunknown confounders, but it is unlikelythat this could account for the entire 37%reduced risk of cancer observed.

Adjusting for use of other diabeticdrugs was necessary because there was ahigher proportion of metformin userswho were treated with sulfonylureas com-

Table 1Baseline characteristics and results of Cox regression analysis for incidence of cancer among metformin users and comparators

Metformin users Comparators Diagnosed cancer Unadjusted Adjusted*

Comparators 4,085 474 1.00 1.00Metformin users 4,085 297 0.46 (0.400.53) 0.63 (0.530.75)

SexFemale 1,848 (45.9) 1,875 (45.2) 315 1.00 1.00

Male 2,237 (54.1) 2,210 (54.8) 456 1.26 (1.091.45) 1.37 (1.181.59)Age (years)

3555 1,001 (24.5) 533 (13.1) 51 1.00 1.005663 964 (23.6) 647 (15.8) 138 2.72 (1.973.75) 2.66 (1.923.68)

6469 865 (21.2) 691 (16.9) 160 3.40 (2.484.67) 3.13 (2.274.32)7076 781 (19.1) 939 (23.0) 205 4.61 (3.396.28) 4.09 (2.985.61)

77100 474 (11.6) 1,275 (31.2) 217 5.95 (4.378.12) 4.86 (3.516.73)Smoking status

Current 577 (14.1) 558 (13.7) 109 1.00 1.00Ex-smoker 1,015 (24.9) 866 (21.2) 177 0.99 (0.781.26) 0.77 (0.600.98)

Never 1,637 (40.1) 1,411 (34.5) 271 0.87 (0.691.09) 0.75 (0.600.94)Not known 856 (21.0) 1,250 (30.6) 214 1.19 (0.941.51) 0.91 (0.721.16)

Carstairs deprivation category1 (least deprived) 224 (5.5) 206 (5.0) 46 1.00 1.00

2 805 (19.7) 902 (22.1) 162 0.75 (0.561.01) 0.74 (0.550.99)3 1,129 (27.6) 1,171 (28.7) 223 0.80 (0.611.07) 0.82 (0.621.09)

4 458 (11.2) 488 (12.0) 99 0.78 (0.561.08) 0.81 (0.581.12)5 521 (12.8) 457 (11.2) 77 0.66 (0.470.92) 0.69 (0.490.97)

6 603 (14.8) 579 (14.2) 106 0.71 (0.520.98) 0.79 (0.581.09)7 (most deprived) 345 (8.5) 282 (6.9) 58 0.72 (0.501.04) 0.83 (0.581.19)

BMI 30.7 3.5 28.6 3.1 0.93 (0.910.95) 0.98 (0.961.00)A1C (%) 7.9 1.0 7.2 1.2 0.77 (0.720.82) 0.91 (0.840.98)

Insulin use

No use 3,833 (93.8) 3,512 (86.0) 696 1.00 1.00Use within 1 year 252 (6.2) 573 (14.0) 75 0.99 (0.851.15) 1.13 (0.971.33)

Sulphonylurea useNo use 2,196 (53.8) 1,996 (73.3) 483 1.00 1.00

Use within 3 months 1,889 (46.2) 1,089 (26.7) 288 1.00 (0.781.28) 1.12 (0.871.47)Data are n, n (%), means SD, or HR (95% CI). *Adjusted for all covariates.




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pared with the comparators but a lowerproportion treated with insulin. Thisprobably reflects the heterogeneity of thepool of potential comparators. Patients

not treated with metformin will encom-pass those who do not yet require oraltherapy as well as those who have pro-gressed to insulin after treatment with sul-

fonylureas only. However, we found nostatistically significant independent ef-fects of sulfonylureas and insulin on riskof cancer in the Cox regression analysis.In contrast, men and older people were atincreased risk of cancer, as might be ex-pected. The results were similar for spe-cific cancer types.

In a dose-response analysis, met-formin users appeared to have a higherrisk of cancer during the first 2 years offollow-up. This may be because patientswho begin treatment with metformin aremore likely to have cancer diagnosed be-cause they have increasing contact withhealth care professionals. In later years offollow-up, high maximum doses of met-formin were associated with the greatestreduction in risk of cancer. Metformindose usually increases with increasing du-ration of use; therefore, dose variables can

be confoundedby duration. This could pro-duce a survival bias, with higher doses spu-riously associated with reduced cancerbecause patients have survived to receive ahigher dose. This is the reason for stratifica-tion by length of follow-up (although resid-ual confounding may still be present).

Within the known limitations of ob-servational data, we are confident in ourstudy design and data sources. The datasources used were independent of eachother, and they provided objective mea-

Figure 2Kaplan-Meier plot with 95% CIs showing time to cancer among metformin users andcomparators.

Table 2Unadjusted and adjusted HRs for secondary outcomes with adjusted HRs for incidence of cancer stratified by maximum prescribeddose and duration of follow-up with comparators as the reference category

n (%) Unadjusted Adjusted*

Incidence of bowel cancer

Comparators 76 (1.9) 1.00 1.00Users 40 (1.0) 0.41 (0.280.61) 0.60 (0.380.94)

Incidence of lung cancerComparators 58 (1.4) 1.00 1.00

Users 35 (0.9) 0.49 (0.320.74) 0.70 (0.431.15)Incidence of breast cancer in women


Overall mortalityComparators 1,422 (34.8) 1.00 1.00

Users 609 (14.9) 0.32 (0.290.35) 0.42 (0.380.47)Mortality from cancer


Incidence of cancer 2 years follow-up* 24 years follow-up* 4 years follow-up*Maximum prescribed dose during

follow-up (n)

Low (1,017) 3.15 (1.925.18) 0.99 (0.442.25) 0.16 (0.060.44)Medium (2,090) 1.94 (1.203.13) 0.51 (0.310.82) 0.40 (0.270.60)

High (978) 2.76 (0.5613.45) 0.28 (0.120.70) 0.15 (0.090.25)

Data are HR (95% CI) unless otherwise indicated. *Adjusted for age, sex, smoking, deprivation, BMI, A1C, insulin use, and sulphonylurea use.

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sures of exposure and outcome. The dia-betic population of Tayside, Scotland,U.K., is well defined, and the MEMO da-tabase used to identify metformin usershas been widely used for drug safety re-search (11). The likelihood of misclassifi-cation of metformin exposure due to dataerror is low because we ensured that all

patients had multiple metformin pre-scriptions. We were otherwise unable to

judge whether patients actually took themetformin as prescribed, although weknow that the drug was collectedfrom thepharmacies (11). We are confident thatwe eliminated survival bias in our choiceof comparators. The national cancer reg-istry (SMR6) was used to identify cancerdiagnoses. Specificity is likely to be higherthan sensitivity in this register, but if anycancer diagnoses were missed, this wouldnot occur differentially with respect to

metformin status.This study has produced sufficientepidemiological evidence that metforminreduces the risk of cancer to make furtherinvestigation a high priority. A plausiblebiological mechanism hinges on the dis-covery that the upstream LKB1 regulatorof AMPK is a tumor suppressor and thatactivation of AMPK by LKB1 plays an im-portant role in inhibiting cell growthwhen cellular energy levels are low (17).Metformin activates AMPK by inhibitingmitochondrial respiration and increasing5-AMP, which enhances activation of

AMPK by LKB1 (1). The blood glucoselowering properties of metformin are me-diated through AMPK restoring cellularenergy levels by phosphorylating regula-tory proteins that lead to stimulation ofglucose uptake into muscle tissues as wellas inhibition of gluconeogenesis in theliver. The anticancer properties of met-formin are likely to be mediated by

AMPKs ability to preserve cellular energylevels by phosphorylating proteins suchas p27KIP and TSC2 that lead to inhibi-tion of cell growth and proliferation sig-

naling networks (18,19).Prior to the discovery that the LKB1 tu-mor suppressor activated AMPK, there waslittle interest in the role of AMPK in cancer.However, the ability of AMPK to gauge andcontrol cellular energy places it in an idealposition to ensure that cell growth and pro-liferation is coupled to the availability of asufficient supply of nutrients and energy.Recent laboratory evidence showing thatthree distinct drugs activate AMPK-delayedtumorigenesis in tumor-prone mice sug-gests that activators of AMPK could have

therapeutic benefit for the treatment of can-cer in humans (4). The protective effects ofmetformin on cancer development couldpotentially be rapid and may occur at quitea late stage of cancer development. Treat-ment of animal cells with metformin signif-icantly activates the AMPK pathway within30 min (2022). Metformin also inhibits

growth of cancer cells (5) or mouse embry-onic stem cells (4) within 12 days. We be-lieve that there is now a strong case toconduct a randomized trial to establishwhether metformin is protective in a popu-lation at high risk for cancer.

Acknowledgments We thank Tenovus,Scotland, U.K., for financial support. The re-searchers were independent. The fundingsource had no involvement in study design oranalysis.

No potential conflicts of interest relevant to

this article were reported.We thank the staff of HIC who provideddata and John Kernthaler who assisted withprogramming.

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new users of metformin are at low risk of incident cancer

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