Metformin and Cancer Risk and Mortality: A Systematic ...Research Article Metformin and Cancer Risk and Mortality: A Systematic Review and Meta-analysis Taking into Account Biases

Research Article

Metformin and Cancer Risk and Mortality: A SystematicReview and Meta-analysis Taking into Account Biases andConfounders

Sara Gandini1, Matteo Puntoni2, Brandy M. Heckman-Stoddard3, Barbara K. Dunn4, Leslie Ford5,Andrea DeCensi6, and Eva Szabo7

AbstractPrevious meta-analyses have shown that the antidiabetic agent metformin is associated with reduced

cancer incidence and mortality. However, this effect has not been consistently demonstrated in animal

models and recent epidemiologic studies. We performed a meta-analysis with a focus on confounders

and biases, including body mass index (BMI), study type, and time-related biases. We identified 71

articles published between January 1, 1966, and May 31, 2013, through Pubmed, ISI Web of Science

(Science Citation Index Expanded), Embase, and the Cochrane library that were related to metformin

and cancer incidence or mortality. Study characteristics and outcomes were abstracted for each study

that met inclusion criteria. We included estimates from 47 independent studies and 65,540 cancer cases

in patients with diabetes. Overall cancer incidence was reduced by 31% [summary relative risk (SRR),

0.69; 95% confidence interval (CI), 0.52–0.90], although between-study heterogeneity was considerable

(I2 ¼ 88%). Cancer mortality was reduced by 34% (SRR, 0.66; 95% CI, 0.54–0.81; I2 ¼ 21%). BMI-

adjusted studies and studies without time-related biases also showed significant reduction in cancer

incidence (SRR, 0.82; 95% CI, 0.70–0.96 with I2 ¼ 76% and SRR, 0.90; 95% CI, 0.89–0.91 with I2 ¼56%, respectively), albeit with lesser magnitude (18% and 10% reduction, respectively). However,

studies of cancer mortality and individual organ sites did not consistently show significant reductions

across all types of analyses. Although these associations may not be causal, our results show that

metformin may reduce cancer incidence and mortality in patients with diabetes However, the reduction

seems to be of modest magnitude and not affecting all populations equally. Clinical trials are needed to

determine if these observations apply to nondiabetic populations and to specific organ sites. Cancer Prev

Res; 7(9); 867–85. �2014 AACR.

IntroductionThe recognition that hyper-insulinemic states such as

metabolic syndrome or type II diabetes mellitus are associ-ated with increased cancer risk has led to intensified interestin the potential of various antidiabetic drugs to preventcancer (1). Metformin, an oral, well-tolerated biguanide thatis used for first-line treatment of diabetes, has been shown todecrease the progression from prediabetes to overt diabetes(2–4). Its multiple actions at both cellular and organismallevels that contribute to anticancer effects include decreasedinsulin/insulin-like growth factor-1 (IGF-1) signaling, inhi-bition of the mammalian target of rapamycin (mTOR),inhibition of mitochondrial complex I in the electron trans-port chain, activation of AMP-activated kinase (AMPK), andreduction of endogenous production of reactive oxygenspecies (ROS), and associated DNA damage (5).

The evidence for a cancer preventive effect formetformin,however, has not been consistently demonstrated in animalor human studies. Multiple studies examining the effect ofmetformin on tumor formation in rodent carcinogenesis

1Division of Epidemiology and Biostatistics, European Institute ofOncology, Milan, Italy. 2Clinical Trials Office, Office of the ScientificDirector, E.O. Ospedali Galliera, Genoa, Italy. 3Breast and GynecologicCancer Research Group, Division of Cancer Prevention, National CancerInstitute, Bethesda, Maryland. 4Chemopreventive Agent DevelopmentResearch Group, Division of Cancer Prevention, National Cancer Insti-tute, Bethesda, Maryland. 5Division of Cancer Prevention, NationalCancer Institute, Bethesda, Maryland. 6Division of Medical Oncology,E.O. Ospedali Galliera, Genoa, Italy. 7Lung and Upper AerodigestiveCancer Research Group, Division of Cancer Prevention, National CancerInstitute, Bethesda, Maryland.

Note:Supplementary data for this article are available atCancer PreventionResearch Online (http://cancerprevres.aacrjournals.org/).

S. Gandini, M. Puntoni, andB.M. Heckman-Stoddard share first authorshipof this article.

A. DeCensi and E. Szabo share senior authorship of this article.

Corresponding Author: Eva Szabo, Lung and Upper Aerodigestive Can-cer Research Group, Division of Cancer Prevention, National CancerInstitute, National Institutes of Health, 9609 Medical Center Drive, Room5E-102, Bethesda, MD 20892. Phone: 240-276-7011; Fax: 240-276-7848;E-mail: [email protected]

doi: 10.1158/1940-6207.CAPR-13-0424

�2014 American Association for Cancer Research.

CancerPreventionResearch

www.aacrjournals.org 867

Research. on May 2, 2018. © 2014 American Association for Cancercancerpreventionresearch.aacrjournals.org Downloaded from

Published OnlineFirst July 1, 2014; DOI: 10.1158/1940-6207.CAPR-13-0424

http://cancerpreventionresearch.aacrjournals.org/

models have shown results ranging from no effect to stronginhibition, albeit using doses that are not always achievablein humans (6–10). Epidemiologic studies comparing theincidence of cancer in diabetics usingmetforminwith thoseusing insulin or other antidiabetic agents have shownsomewhat variable results (11–15). Several authors per-formed meta-analyses to determine if a consistent effect onoverall cancer incidence, cancer mortality, or cancer inci-dence at specific target organs was evident (11–15). Ashortcoming of these previousmeta-analyseswas the inabil-ity to identify subgroups that might benefit most (or sufferharm) from metformin. For instance, a recent clinical trialshowed that metformin affected breast cancer proliferationdifferentially according to insulin resistance status andbodymass index (BMI), with a trend toward inhibiting prolifer-ation only in women with insulin resistance or high BMI(16). Furthermore, a number of the published studiessuffered from time-related biases resulting in inappropriatecomparison between metformin users versus nonusers andpotentially exaggerated metformin’s protective effects (17).Time-related bias in observational studies can produceillusory results in favor of metformin. They are most oftena form of differential misclassification bias that can gener-ally be avoidedby appropriate accounting of follow-up timeand exposure status in the design and analysis of suchstudies. There are different types of time-related biases.Immortal time bias refers to a period of cohort follow-uptime during which a cancer event (that determines end offollow-up) cannot occur. Immortal time bias, for example,can arise when the period between cohort entry and date offirst exposure to metformin, during which cancer has notoccurred, is either misclassified or simply excluded and notaccounted for in the analysis. This is frequently found instudies that compare "users" against "nonusers." The use ofa time-dependent approach takes into account this sourceof bias. In cohort studies where a first-line therapy withmetformin is compared with second- or third-line thera-pies, patients are unlikely to be at the same stage of diabetes,which can induce confounding of the association with anoutcome (e.g., cancer incidence) by disease duration. Anoutcome related to the first-line therapy may also be attrib-uted to the second-line therapy if it occurs after a longperiodof exposure. Such a situation requires matching on diseaseduration and consideration of latency time windows in theanalysis (17).

Therefore, we performed a systematic review and meta-analysis with emphasis on studies controlling for BMI,prospective studies, and studieswithout time-related biases.

Materials and MethodsLiterature search

The aim of the study was to evaluate the associationbetweenmetformin use and cancer incidence andmortalityin patients with diabetes. The meta-analysis was conductedin accordance with the guidelines for the Meta-analysis OfObservational Studies in Epidemiology (MOOSE) and thePRISMA statement (18, 19). The search was carried out on

observational studies and trials, without language restric-tions. The literature from January 1, 1966, to May 31, 2013,was searched using the following databases: Pubmed, ISIWebof Science (ScienceCitation Index Expanded), Embase,and the Cochrane library. The following main keywords orcorresponding MeSH terms were used: "Metformin,""Biguanides," or "Diabetes Mellitus, Type 2/therapy," and"cancer" or "neoplasms." The search string used forPubmed is the following: (Metformin and cancer) or ["Met-formin"(Mesh) and "Neoplasms"(Mesh) and "epidemio-logic studies"(Mesh)] not ["polycystic ovary syndrome" or"Polycystic Ovary Syndrome"(Mesh)]. A manual searchwas performed for references cited in the selected articles,and in selected reviews or books. This literature search wasindependently carried out by 2 academic investigators.Group discussion resolved any disagreement with articleselection.

Methods of data extractionCriteria for article inclusion in the analysis were: (i)

independence from other studies in order to avoid givingdouble weight to estimates derived from the same study;when 2 or more studies were not independent, only thestudy with larger sample size was included; (ii) sufficientinformation to allow adequate estimation of the hazardratio (HR)/relative risk (RR)/odds ratios (OR), and 95%confidence intervals (CI; i.e., crude data or adjusted esti-mates and standard errors, CIs, or P values); (iii) compar-ison of cancer incidence or mortality in patients withdiabetes (comparisons with nondiabetic populations wereexcluded).

We extracted fully adjusted risk estimates for ever use ofmetformin, alone or in combinationwithother antidiabetictreatments, compared with antidiabetic treatments otherthan metformin or no treatment, and we calculated thecorresponding variance using the formula proposed byGreenland (20). Association between metformin and can-cer incidence/mortality across selected studies was comput-ed as a summary relative risk (SRR) with 95% CIs.

Statistical analysisHeterogeneity was evaluated using the I2 parameter,

which represents the percentage of total variation acrossstudies that is attributable to heterogeneity rather than tochance. A threshold below 50% is generally consideredacceptable (21). To account for possible sources of bias,we considered the STROBE checklist proposed for obser-vational epidemiologic studies (22). Several sensitivityanalyses were considered in this work, taking into accountfactors presented in the STROBE checklist that could intro-duce bias. Subgroup and sensitivity analyses and meta-regressions were carried out to investigate between-studyheterogeneity and the influence of confounding factors,study design, interaction with other treatments, definitionsof disease and population features on the risk estimates. Akey factor considered was the adjustment for BMI, given itsmodifying effect on metformin activity on diabetes inci-dence (3) and breast cancer proliferation (16).

Gandini et al.

Cancer Prev Res; 7(9) September 2014 Cancer Prevention Research868




We also investigated heterogeneity because of studydesign because retrospective cohort studies could haveimportant sources of bias. Sensitivity analyses were carriedout to verify the effect of single studies and inclusion andexclusion criteria on the stability of the summary estimates,such as the use of insulin as treatment comparator. The SRRwas estimated by pooling the study-specific estimates byrandom effects models fitted using SAS (Proc Mixed) withmaximum likelihood estimates and CIs based on t distri-bution (23), to be conservative.To take into account time-related biases that can occur in

observational studies (17), we carried out subgroup anal-yses including only studies that were designed or analyzedto avoid immortal time bias, time-window bias, and time-lagging issues. The summary estimates were based only onstudies that specifically used time-dependent techniquesneeded to avoid immortal time bias and to treat exposuresto the different antidiabetic agents as time-dependentvariables.To verify whether publication bias might affect the valid-

ity of the estimates, funnel plots were investigated consid-ering regression of Ln(RR) on the sample size, weighted bythe inverse of the pooled variance (24). All analyses wereperformed with SAS software version 8.02 and STATAsoftware version 11.

ResultsMeta-analysisThe flow diagram for study inclusion in themeta-analysis

is shown in Figure 1. A total of 71 articles were retrieved andchecked for relevance in terms of intervention, populationstudied, and reporting of cancer incidence/mortality data.Twenty-four (25–48) articles were excluded (Supplemen-

tary Table S1). Because the UKPDS trials had partiallyoverlapping patient populations, only the risk estimate forthe metformin monotherapy trial was included (49).

Overall we included estimates from 47 studies and65,540 cancer cases: 19 studies (50–67) presented data onoverall cancer incidence, 7 studies (38, 49, 54, 68–72) onoverall cancer mortality, and 32 studies (45, 48, 50, 52–54, 56, 57, 59, 66, 73–96) reported estimates on singlecancer sites. Table 1 shows the characteristics of these 47studies. There were 11 prospective cohort studies, 16 case–control studies, 14 retrospective cohort studies, and 6clinical trials of patients with diabetes randomized to met-formin versus other treatment published between 1998 and2013. Treatment comparators were sulfonylureas, insulin,or other antidiabetic treatments. If more than one estimatewas presented, the estimate for metformin alone was pre-ferred to metformin combined with other treatments and acomparator other than insulin was chosen.

We also examined SRRs stratified by BMI adjustment andtime-related bias. For the latter analysis, 18 studies werejudged to have avoided these biases (49, 51, 52, 55, 57,61, 62, 64, 70, 71, 75, 77, 78, 80, 86, 87). However, thesmall number of studies may imply lack of robustness ofthe SRR estimates and where fewer than 3 studies wereadjusted for BMI, the BMI-adjusted SRRs are not reported.Estimates from randomized clinical trials were consideredto be adjusted for BMI.

Overall cancer incidence and mortality—effects of BMIand study type

The SRRs for metformin and overall cancer incidence(50–59) and mortality (45, 50–54, 56–59, 73–84, 86, 87)are shown in Table 2 and Fig. 2. A risk reduction of 31%(SRR, 0.69; 95% CI, 0.52–0.90), with high heterogeneity(I2 ¼ 88%), was estimated for overall cancer incidence insubjects taking metformin compared with other antidia-betic compounds. There was a statistically significant, 34%reduction in cancer mortality (0.66, 95% CI, 0.54–0.81),with limited heterogeneity (I2 ¼ 21%).

A significant reduction in overall cancer incidence inmetformin users was also found when the estimates wereadjusted for BMI (SRR, 0.82; 95%CI, 0.70–0.96; I2¼ 76%),but not in BMI-unadjusted studies (SRR, 0.58 with 95%CI,0.31–1.09 and I2¼94%;P¼0.49 for thedifferencebetweenestimates). However, no reduction was found when theanalysis was restricted to prospective studies (SRR, 0.71;95% CI, 0.47–1.07; I2¼ 89%) or randomized clinical trials(SRR, 0.95; 95%CI, 0.69–1.30; I2¼5%), although the latterstudies included only 321 events. Meta-regression alsoindicates that publication year is not associated with riskestimates (P ¼ 0.59), nor was there an association with theuse of insulin treatment as comparator (P ¼ 0.89).

The SRR for cancer mortality from BMI-adjusted resultsconfirmed a significant reductionwithmetforminuse (SRRsadjusted for BMI: 0.60; 95%CI, 0.45–0.80; I2¼ 0), whereasthe reduction fromunadjusted estimates was not significant(SRR, 0.75; 95% CI, 0.23–2.46; I2 ¼ 71%). Analysis ofprospective studies only showed a statistically significant

750 citations identified:•716 Medline, EMBASE, ISI Web of SCIENCE (Science Citation Index Expanded)•34 Reference list

679 citations excluded–reviews; title and/or abstract not relevant for the study endpoint

71 full-text original articles considered for inclusion

24 studies excluded–did not meet inclusion criteria (see Supplementary Table S1)

47 independent studies included

24 independent studies included for all cancer sites (incidence and/or mortality)

23 independent studies included for ONLY single cancer sites

Figure 1. Study flow diagram. Of 750 citations identified, 47 independentstudies were included in the analysis.

Metformin Meta-Analysis

www.aacrjournals.org Cancer Prev Res; 7(9) September 2014 869




Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

UKPDStudyGroup

(49)

(UK)

RCT

Mortality

Cas

es:1

39Atris

k:75

3Any

site:0

.71

(0.29–

1.76

)aDietalon

e(n

¼41

1)vs

.intens

iveblood

-gluc

oseco

ntrolp

olicy

with

metform

in(n

¼34

2)

n.a.

Sch

erntha

ner(61,72

)QUARTE

TM

(Europ

e)RCT

Inciden

ceCas

es:9

Atris

k:1,19

4Any

site:0

.51

(0.14–

1.90

)Metform

inmon

othe

rapy

(n¼

597)

vs.

pioglita

zone

(n¼

597)

n.a.

Han

efeld(62,72

)QUARTE

TC

(Europ

ean

dNorth

America)

RCT

Inciden

ceCas

es:9

Atris

k:63

9Any

site:1

.99

(0.43–

12.32)

Metform

inþ

sulfo

nylurea(n

¼32

0)vs.p

ioglita

zone

þsu

lfony

lurea(n

¼31

9)

n.a.

Yan

g(85)

(UK)

Gen

eral

prac

ticene

sted

case

–co

ntrolina

retros

pec

tiveco

hort

Inciden

ceCas

es:1

25Con

trols:

1,19

5Colon

:1.00

(0.60–

1.70

)3or

moreye

arsof

metform

intherap

yvs

.no

nins

ulin

users

Smok

ing,

historyof

cholec

ystectom

y,diabetes

duration,

BMI,

sulfo

nylureaus

e,as

pirin/NSAID

use

Bow

ker(69)

(Can

ada)

Pop

ulation-bas

edretros

pec

tiveco

hort

Mortality

Cas

es:4

07Atris

k:10

,309

Any

site:0

.77

(0.63–

0.91

)Metform

invs

.su

lfony

lureas

use

Insu

linus

ean

dCDS.

Mon

ami(55

)(Ita

ly)

Hos

pita

l-bas

edretros

pec

tiveca

se–

controls

tudy

Inciden

ceCas

es:1

95Con

trols:

195

Any

site:0

.28

(0.13–

0.57

)Exp

osureto

metform

informorethan

36mon

thsvs

.other

hypog

lyce

mic

drugs

users

Durationof

diabetes

,BMI,HbA1c

,co

morbidity

,smok

ing

andalco

hola

bus

e,co

ncom

itant

hypog

lyce

mic

trea

tmen

tOliveria

(76)

(USA)

Pop

ulation-bas

edretros

pec

tiveco

hort

Inciden

ceCas

es:8

13Atris

k:19

1,22

3Colon

:0.67(0.52–

0.85

)Bladder:0

.99(0.70–

1.39

)Liver:0

.73(0.34–

1.56

)Pan

crea

s:1.26

(0.80–

1.99

)

Eve

rus

eof

metform

inmon

othe

rapy

vs.

neve

rus

e

HBVan

dHCVinfection,

cirrho

sis,

alco

holism,

polyp

s,ob

esity

,ulce

rativ

eco

litis,

Crohn

'sdisea

se,c

ystic

fibrosis,

chronic

pan

crea

titis,

dermatom

yositis

,polym

yositis

,idiopathicDVT,

partial

gastrectom

y,pelvic

radiatio

n,an

dsc

histos

omiasis.

(Con

tinue

don

thefollo

wingpag

e)

Gandini et al.





Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Currie

(59)

(UK)

Gen

eral

practice

retros

pec

tiveco

hort

Inciden

ceCas

es:3

73Atris

k:7,89

7Any

site:0

.74(0.65–

0.84

);Breas

t:1.02

(0.71–

1.45

);Colon

:0.56

(0.40–

0.76

);Prostate:

0.93

(0.67–

1.32

);Pan

crea

s:0.20

(0.11–

0.36

)

Metform

inmon

othe

rapy

vs.s

ulfony

lureas

mon

othe

rapy

Smok

ing,

comorbidity

,HbA1c

,diabetes

duration,

weigh

t

Don

adon

(80)

(Italy)

Hos

pita

l-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:4

65Con

trols:

490

Live

r:0.33

(0.10–

0.70

)Metform

inus

ers

vs.n

onus

ers

Noad

justingva

riables

wereco

nsidered

Hom

e(52)

RECORD,

(Europ

e)RCT

Inciden

ceCas

es:1

25Atris

k:2,22

5Any

site:1

.22(0.86–

1.74

)Breas

t:1.0(0.32–

3.10

)bProstate:

2.0

(0.68–

5.82

)bPan

crea

s:5.99

(0.72–

49.6)bLive

r:4.0(0.18–

88.7)b

Metform

in(n¼1,12

2)vs

.rosiglita

zone

(n¼

1,10

3)

n.a.

Li(86)

(USA)

Hos

pita

l-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:2

55Con

trols:

106

Pan

crea

s:0.38

(0.22–

0.69

)Metform

inus

ers

vs.n

onus

ers

Rac

e,sm

oking,

alco

hol,

BMI,family

historyof

canc

er,d

urationof

diabetes

,and

insu

linus

e.Libby(54)

(Sco

tland

,UK)

Pop

ulation-bas

edretros

pec

tiveco

hort

Inciden

cean

dmortality

Cas

es:7

71Atris

k:8,17

0Any

site

inciden

ce:0

.63

(0.53–

0.75

);Breas

t:0.60

(0.32–

1.10

);Colon

:0.60(0.38–

0.94

);Lu

ng:0

.70

(0.43–

1.15

)Any

site

mortality:

0.63

(0.49–

0.81

)

Metform

inus

ers

vs.n

onus

ers

Smok

ing,

BMI,HbA1c

,materiald

epriv

ation,

othe

rdrugus

e(sulfony

lureas

orinsu

lin)

Wrig

ht(79)

(USA)

Pop

ulation-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:9

7Con

trols:

101

Prostate:

0.56

(0.32–

1.00

)Metform

inus

ers

vs.n

onus

ers

BMI,statin

andas

pirin

use,

othe

rdiabetes

trea

tmen

t,PSA

screen

inghistory,

family

historyof

prostateca

ncer

(Con

tinue

don

thefollo

wingpag

e)






Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Bod

mer

(73)

(UK)

Gen

eral

practice

retros

pec

tivene

sted

case

–co

ntrol

Inciden

ceCas

es:1

7Con

trols:

120

Breas

t:0.44

(0.24–

0.82

)Use

rsof

40þ

pres

criptio

ns(>5

years)of

metform

invs.

nonu

sers

c

Gen

eral

practicean

dca

lend

artim

eby

match

ing,

othe

rus

eof

prand

ialg

luco

seregu

lators,a

carbos

e,es

trog

ens,

smok

ing,

BMI,diabetes

duration,

andHbA

1cHas

san(81)

(USA)

Hos

pita

l-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:1

22Con

trols:

86Live

r:0.30

(0.20–

0.60

)Bigua

nideus

ersvs

.no

nuse

rsRac

e,ed

ucationa

llev

el,

ciga

rettesm

oking,

alco

hold

rinking

,HCV,

HBV,fam

ilyhistoryof

canc

erKah

n(63)

ADOPT(USA)RCT

Inciden

ceCas

es:1

60Atris

k:4,35

1Any

site:A

DOPT-G:

0.78

(0.53–

1.14

)ADOPT-R:0

.92(0.63–

1.35

)Breas

t:2.0(0.60–

6.62

)bColon

:1.75

(0.51–

5.96

)bProstate:

1.0(0.41–

2.40

)b

Pan

crea

s:0.1(0.005

–

1.84

)b

Metform

in(n¼1,45

4)vs

.gliben

camide(n

¼1,44

1)vs

.rosiglita

zone

(n¼

1,45

6)

n.a.

Land

man

(70)

(Nethe

rland

s)Gen

eral

practice

prosp

ectiv

eco

hort

Mortality

Cas

es:1

22Atris

k:1,35

3Any

site:0

.43

(0.23–

0.80

)Metform

inus

ers

vs.n

onus

ers

Smok

ing,

diabetes

duration,HbA1c

,serum

crea

tinine,

BMI,blood

press

ure,

total

choles

terol/H

DL,

album

inuria,ins

ulin

use,

sulfo

nylureaus

ean

dmac

rova

scular

complications

Williams-Herman

(64)

(18co

untries

worldwide)

RCT

Inciden

ceCas

es:1

8Atris

k:54

3Any

site:0

.61

(0.22–

1.79

)Metform

in(n

¼36

4)vs

.Sita

gliptin

(n¼17

9)n.a.

Yan

g(58)

(China

)Hos

pita

l-bas

edprosp

ectiv

eco

hort

Inciden

ceCas

es:2

71Atris

k:6,10

3Any

site:0

.99

(0.70,

1.41

)Sulfony

lureaus

eþ

ever

useof

metform

invs

.nev

erus

eof

metform

in

BMI,sm

okingstatus

,alco

hol,HbA1c

,SBP,

LDL-C–relatedris

k,HDLan

dtriglyce

ride,

statins,

RASinhibitor

usag

e,insu

linus

age

(Con

tinue

don

thefollo

wingpag

e)

Gandini et al.





Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Azo

ulay

(77)

(Can

ada)

Pop

ulation-bas

edretros

pec

tivene

sted

case

–co

ntrol

Inciden

ceCas

es:7

39Con

trols:

7,35

9Prostate:

1.23

(0.99–

1.52

)Eve

rvs

.nev

erus

ers

ofmetform

inc

HbA

1c,a

lcoh

olus

e,ob

esity

,smok

ing,

lower

urinarytrac

tsym

ptoms,

previou

sca

ncer,

previou

sus

eof

NSAID,

antih

ypertens

ivedrug

s,an

dstatins,us

eof

othe

ran

tidiabetic

agen

tsBau

r(65)

(German

y)Hos

pita

l-bas

edprosp

ectiv

eco

hort

Inciden

cean

dmortality

Cas

es:6

6Atris

k:1,30

8Any

site

inciden

ce:0

.66

(0.26–

1.64

)Any

site

mortality:

0.71

(0.2–

2.59

)

Metform

inus

ersvs.

nonu

sers

Smok

ing,

BMI,HbA1c

Bos

co(74)

(Den

mark)

Pop

ulation-bas

edretros

pec

tivene

sted

case

–co

ntrol

Inciden

ceCas

es:3

93Con

trols:

3,93

0Breas

t:0.81

(0.63–

0.96

)Metform

inforat

leas

t1

year

vs.w

omen

not

pres

cribed

antid

iabetic

med

ication,

orus

edmetform

infora

tlea

st1

year

Diabetes

complications

,clinical

obes

ityye

arof

birth,

parity

,pos

tmen

opau

sal

horm

oneus

e.

Ferrara(75)

(USA)

Pop

ulation-bas

edprosp

ectiv

eco

hort

Inciden

ceCas

es:9

,082

Atris

k:25

2,46

7Breas

t:0.90

(0.80–

1.00

);Colon

:1.00(0.90–

1.20

);Prostate:

1.00

(0.90–

1.10

);Pan

crea

s:1.20

(1.00–

1.50

);Lu

ng:

1.00

(0.80–

1.10

);NHL:

1.00

(0.80–

1.20

);Corpus

Uteri:

0.90

(0.80–

1.20

);Kidne

y/rena

lpelvis:

1.30

(1.0–

1.6);R

ectum:0

.90

(0.70–

1.20

);Melan

oma:

0.80

(0.60–

1.10

)

Eve

rus

eof

piog

litaz

one

andmetform

invs.

neve

ruse

ofmetform

in

Yea

rof

coho

rten

try,

race

/ethnicity,inc

ome,

smok

ing,

glyc

emic

control,diabetes

duration,

crea

tinine

leve

ls,c

onge

stivehe

art

failure,u

seof

othe

rdiabetes

med

ications

Hen

se(51)

(German

y)Pop

ulation-bas

edprosp

ectiv

eco

hort

Inciden

ceCas

es:1

,364

Atris

k:26

,742

Any

site:0

.95

(0.90–

1.01

)Metform

in(only)

users

vs.n

onus

ers

Diabetes

duratio

n,BMI,

insu

lintherap

yLa

i(84

)(Ta

iwan

)Pop

ulation-bas

edretros

pec

tiveco

hort

Inciden

ceCas

es:1

29Atris

k:19

,624

Lung

:0.55(0.37–

0.82

)Metform

inus

ersvs.

nonu

sers

Pulmon

ary

tubercu

losis,

chronic

obstructivepulmon

ary

disea

se,a

ndpropen

sity

score

(quintile).

(Con

tinue

don

thefollo

wingpag

e)






Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Lee(53)

(Sou

thKorea

)Pop

ulation-bas

edprosp

ectiv

eco

hort

Incide

nce

Cas

es:3

39Atris

k:15

,717

Any

site:0

.12(0.08–

0.19

);Colon

:0.36

(0.13–

0.98

);Live

r:0.06

(0.02–

0.16

);Eso

pha

gus:

0.44

(0.07–

2.61

);Stomac

h:1.41

(0.42–

4.73

)

Atleas

t2presc

riptio

nof

metform

invs.a

nyothe

roral

antih

yperglyc

emic

med

ication

Other

oral

antih

yperglyc

emic

med

ication,

Cha

rlson

comorbidity

index

score,

metform

indo

sage

andduration

Mellbin

(71)

(Swed

en)

Prosp

ectiv

eco

hort

follo

w-upan

alysis

from

RCT

Mortality

N¼

1,07

3N

even

ts¼

37Any

site:0

.25(0.08–

0.83

)Patientsus

ingmetform

invs

.not

usingat

disch

arge

Smok

ingha

bits,

prev

ious

myo

cardial

infarctio

nor

previou

sco

nges

tivehe

art

failure,c

reatinineat

rand

omization,

percutan

eous

tran

slum

inal

corona

ryan

giop

lastyor

corona

ryartery

byp

assgraftin

gdu

ringthe

hosp

italization,

and

mea

nup

dated

blood

gluc

ose

Morden

(56)

(USA)

Gen

eral

prac

tice

retros

pec

tiveco

hort

Incide

nce

Cas

es:5

,466

Atris

k:81

,681

Any

site:1

.01(0.94–

1.08

);Breas

t:1.28

(1.05–

1.57

);Colon

:0.94

(0.72–

1.22

);Prostate:

0.97

(0.76–

1.24

);Pan

crea

s:1.25

(0.89–

1.75

)

Metform

invs

.not

ininsu

lin-treated

patients

Rac

e,low-inc

ome

subsidystatus

,co

morbidities

,tob

acco

expo

sure,C

harls

on,

comorbidities

exclud

ingmaligna

ncy,

diab

etes

,ins

ulin

dos

equ

artiles

Bo(68)

(Italy)

Hos

pita

l-bas

edretros

pec

tiveco

hort

Mortality

Cas

es:1

22Atris

k:3,70

3Any

site:0

.56

(0.34–

0.94

)Metform

inus

evs

.diet

controlo

nly

Diabetes

duration,

HbA1c

,smok

ing,

BMI,

pres

ence

ofretin

opathy

,ne

phropathy

,coron

ary

orperiphe

rala

rtery

dise

ase,

othe

rco

-morbidities

andtheus

eof

antih

ypertens

ive

drug

san

dac

etylsa

licylic

acid

(Con

tinue

don

thefollo

wingpag

e)

Gandini et al.





Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Bod

mer

(83)

(UK)

Gen

eral

practice

retros

pec

tivene

sted

case

–co

ntrol

Incide

nce

Cas

es:9

20Con

trols:

5,51

9Colon

:1.43(1.08–

1.90

)Metform

inus

ers(50þ

presc

riptio

ns)v

s.no

nuse

rs

Diabetes

duration,

BMI,

smok

ing,

prio

rus

eof

aspirin,

NSAID,s

tatin

s,es

trog

enus

e(w

omen

),su

lfony

lureas

and

insu

linus

eBod

mer

(82)

(UK)

Gen

eral

practice

retros

pec

tiveca

se–

control

Incide

nce

Cas

es:3

07Con

trols:

1,34

7Pan

crea

s:0.83

(0.57–

1.21

)Metform

inus

ersvs

.no

nuse

rsBMI,sm

oking,

alco

hol

cons

umption,

diab

etes

duratio

n,othe

ran

tidiabeticsdrugs

Bod

mer

(88)

(UK)

Gen

eral

practice

retros

pec

tiveca

se–

control

Incide

nce

Cas

es:1

.029

Con

trols:

6,17

4Lu

ng:1

.09(0.85–

1.38

)Metform

inus

ers(40þ

presc

riptio

ns)v

s.no

nuse

rs

BMIa

ndsm

oking

Chleb

owsk

i(48

,95)

(USA)

Prosp

ectiv

eCoh

ort

(WHIp

rogram

)Incide

nce

Cas

es:2

33Atris

k:68

,019

Breas

t:0.65

(0.46–

0.91

)Metform

invs

.other

antid

iabe

ticdrugs

Family

history,

prio

rbrea

stbiops

y,ag

eat

men

arch

e,men

opau

se,p

arity

,age

atfirstlivebirth,

brea

stfeed

ing,

educ

ation,

smok

ing,

alco

holu

se,B

MI,

phys

ical

activ

ity,

duratio

nof

prio

res

trog

enalon

e,es

trog

enþ

prog

esterone

use,

bilateral

oopho

rectom

y,weigh

tloss

Hsieh

(89)

(Taiwan

)Pop

ulation-bas

edprosp

ectiv

eco

hort

Incide

nce

Cas

es:6

.554

Atris

k:61

,777

Any

site:0

.56(0.44–

0.71

)Breas

t:0.57

(0.33–

0.97

)Colon

:0.54

(0.39–

0.76

)Prostate:

0.97

(0.60–

1.55

)Lun

g:0.64

(0.45–

0.90

)Liver:0

.66(0.49–

0.91

)Pan

crea

s:0.63

(0.28–

1.42

)Stomac

h:0.63

(0.39–

1.08

)

Metform

invs

.su

lfony

lurea

Onlyag

ean

dse

x

(Con

tinue

don

thefollo

wingpag

e)






Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Lehm

an(78)

(USA)

Pop

ulation-bas

edretros

pec

tiveco

hort

Inciden

ceCas

es:3

60Atris

k:5,04

2Prostate:

2.15

(1.83–

2.52

)Metform

inve

rsus

sulfo

nylureaon

ly(re

stric

tedto

nons

tatin

users)c

HbA1c

,diabetes

duration,

race

/ethn

icity

,Cha

rlson

comorbidity

score

Liao

(91)

(Taiwan

)Pop

ulation-bas

edprosp

ectiv

eco

hort

Inciden

ceCas

es:5

6Atris

k:49

,803

Pan

crea

s:0.85

(0.39–

1.89

)Metform

inus

ers

vs.n

onus

ers

Noad

justingva

riables

wereco

nsidered

Mag

liano

(66)

(Aus

tralia)Com

mun

ity-bas

edlong

itudinal

coho

rtInciden

ceCas

es:3

09Atris

k:1,29

4Any

site:0

.88

(0.67–

1.17

);Prostate:

2.16

(1.19–

3.9)

Metform

inus

ers

vs.n

onus

ers

Noad

justingva

riables

wereco

nsidered

Maz

zone

(94)

(USA)

Hos

pita

l-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:5

07Con

trols:

507

Lung

:0.48(0.28–

0.81

)Metform

inus

ers

vs.n

onus

ers

Med

icationus

e,BMI,

HbA1C

,smok

ing

Ngw

ana(50)

(Belgium

)Gen

eral

practice

retros

pec

tiveco

hort

Inciden

ceCas

es:2

21Atris

k:4,01

2Any

site:0

.20

(0.03–

1.64

);Breas

t:0.46

(0.07–

3.10

);Colon

:0.11(0.01–

1.07

);Prostate:

0.61

(0.31–

1.19

)

Metform

invs.o

ther

antid

iabetic

trea

tmen

tsan

ddiet

only

Weigh

tan

dinitial

HbA1c

Red

aniel(90

)(UK)

Gen

eral

practice

retros

pec

tiveco

hort

Inciden

ceCas

es:8

73Atris

k:52

,657

Breas

t:1.02

(0.79–

1.3)

Metform

invs.

sulfo

nylurea

Period,reg

ion,

BMI,

year

ofdiagn

osis

Ruiter(57

)(Nethe

rland

s)Hos

pita

l-bas

edprosp

ectiv

eco

hort

Inciden

ceCas

es:3

,552

Atris

k:85

,289

Any

site:0

.90(0.88–

0.91

);Breas

t:0.95

(0.91–

0.98

);Colon

:0.91

(0.88–

0.94

);Prostate:

0.92

(0.88–

0.94

);Pan

crea

s:0.73

(0.66–

0.80

);Live

r:0.67

(0.53–

0.86

);Lu

ng:0

.87

(0.84–

0.91

);Eso

pha

gus:

0.90

(0.82–

0.97

);Stomac

h:0.83

(0.76–

0.90

)

Metform

invs.

sulfo

nylurea

derivatives

c

Age

atfirstoral

gluc

ose-

loweringdrug

presc

riptio

n,nu

mber

ofothe

rdrugs

used

inthe

year

before

thestartof

OGLD

,num

ber

ofho

spita

lizations

inthe

year

before

thestartof

OGLD

,calen

dar

time

Bec

ker(96)

(UK)

Gen

eral

practice

retros

pec

tiveca

se–

control

Inciden

ceCas

es:2

91Con

trols:

1,74

6End

ometria

l:0.88

(0.58–

1.32

)Metform

inus

ers

(25þ

presc

riptio

ns)vs.

nopriorus

e

BMI,sm

oking,

diabetes

duration

Cha

iteerak

ijet

al.(93

)(USA)

Hos

pita

l-bas

edretros

pec

tiveca

se–

control

Inciden

ceCas

es:1

05Con

trols:

34Live

r:0.4(0.2–0.9)

Metform

inus

ersvs.

nonu

sers

Ethnicity,a

ndresiden

tial

area

,propen

sity

scores

forstatin-use

(Con

tinue

don

thefollo

wingpag

e)

Gandini et al.





Tab

le1.

Epidem

iologicstud

iesof

metform

inan

dca

ncer

risk

(Con

t'd)

Firstau

thor(ref.)

(coun

try)

Studydes

ign

End

point

Sam

ple

size

Riskes

timates

(95%

CI)

Treatmen

tco

mparison

Adjustingva

riab

les

(other

than

agean

dse

x)

Che

n(92)

(Taiwan

)Pop

ulation-bas

edretros

pec

tiveca

se–

control

Incide

nce

Cas

es:2

2,04

7Con

trols:

25,773

Live

r:0.79

(0.75–

0.83

)Metform

inus

ers

vs.n

onus

ers

Cirrho

sis,

HCV,D

Mduration,

comorbidities

,other

med

ications

Chu

ng(67)

(Sou

thKorea

)Pop

ulation-bas

edretros

pec

tiveco

hort

Incide

nce

Cas

es:7

3Atris

k:1,21

7Any

site:0

.57(0.39–

0.85

)Metform

inus

ersvs

.no

nuse

rsNot

spec

ified

Currie

(60)

(UK)

Gen

eral

practice

retros

pec

tiveco

hort

Incide

nce

Cas

es:4

,029

Atris

k:84

,622

Any

site:0

.91(0.83–

1.00

)Metform

invs

.su

lfony

lurea

Systolic

blood

press

ure,

HbA

1c,total

choles

terol,se

rum

crea

tinine,

BMI,

smok

ingstatus

,an

tihyp

ertens

ivelip

id-

lowering,

antip

latelet

therap

y,durationof

diabe

tes,

prio

rhistory

ofca

ncer,L

VD,

microva

scular

disea

se,

number

ofco

ntac

tswith

thege

neral

practition

erin

theye

arbeforetheindex

date,

Cha

rlson

comorbidity

index

Smiech

owsk

i(87

)(Can

ada)

Pop

ulation-bas

edprosp

ectiv

ene

sted

case

–co

ntrol

Incide

nce

Cas

es:8

08Con

trols:7,76

4Lu

ng:0

.94(0.76–

1.17

)Metform

inus

ersvs

.no

nuse

rsDiabetes

duration,

HbA

1c,o

bes

ity,

smok

ing,

exce

ssive

alco

holu

se,p

reviou

sca

ncer,c

hron

icob

structivepulmon

ary

disea

se,a

sthm

a,no

nsteroidal

anti-

inflam

matorydrug

s,as

pirin,

statins,

and

othe

rantidiabe

ticdrugs

Abbreviations

:ADOPT,

adiabetes

outcom

eprogres

sion

trial;%CI,pe

rcen

tCI;CDS,c

hron

icdisea

sesc

ore;

DVT,

dee

pve

inthrombos

is;H

bA1c

,hem

oglobin

A1c

;HBV,h

epatitisB

virus;HCV,h

epatitisCvirus;HDL,

high

-den

sity

lipop

rotein;L

DL-C,low

-den

sity

lipop

rotein

choles

terol;N,n

umber;N

SAID,n

onsteroidalan

ti-inflam

matorydrug;

OGLD

,oralg

luco

seloweringdrug

s;PSA,prostate-sp

ecifican

tigen

;RAS,renin–

angioten

sinsy

stem

;RCT,

rand

omized

controlledtrial;RECORD,rosiglita

zone

evalua

tedforca

rdiacou

tcom

esan

dregu

latio

nof

glyc

aemia

indiabetes

;SBP,s

ystolic

blood

pressure;

UKPDS,U

nitedKingd

omProsp

ectiv

eDiabetes

Study.

aRiskes

timateforus

ersof

metform

inalon

e.bADOPT-Gan

dADOPT-R,g

liben

clam

idean

drosiglita

zone

armsof

ADOPTstud

y.Riskes

timates

represe

ntmultip

leco

mparison

sfrom

asing

letrial,an

dthean

alysistake

sac

coun

tof

correlationbetwee

nthes

eco

mparison

s;ris

kes

timates

forsing

leca

ncer

siteswereca

lculated

from

crud

edata.

cExc

luded

patientson

mon

othe

rapy

with

insu

lin.






reduction with metformin, in contrast to the effect seen oncancer incidence (SRR, 0.48; 95% CI, 0.23–0.97; I2 ¼ 0).

Organ specific analyses—effects of BMI and study typeon cancer incidence

The SRR estimates for breasts, prostate, colon, pancreas,liver, and lungs are illustrated in Fig. 3 and Table 2. The riskreduction with metformin use in unadjusted analysesreached statistical significance only for liver (9 studies, SRR,0.47; 95% CI, 0.28–0.78; I2 ¼ 82%) and lung cancer (8studies, SRR, 0.82; 95% CI, 0.67–0.99; I2 ¼ 66%; Table 2).Analysis of prospective studies confirmed this associationfor liver but not lung cancer. Too few liver or lung cancerstudies were available to address the effect of BMI. Mostnotably, the summary estimate for lung cancer adjusted forsmoking showedno significant association (SRR, 0.95; 95%CI, 0.82–1.11; I2 ¼ 58%).

The meta-analysis of the 13 studies on breast cancer riskshowed a nonsignificant trend (SRR, 0.88; 95% CI, 0.75–1.03; I2 ¼ 60%). However, BMI adjustment showed bor-derline significance in 5 studies (SRR, 0.82; 95% CI, 0.67–1.00; I2 ¼ 48%). Analysis of 7 prospective studies showedstatistical significance (SRR, 0.94; 95% CI, 0.90–0.99; I2 ¼44). Metformin treatment and prostate cancer risk did notshow any association in 12 studies (SRR, 1.06; 95% CI,0.80–1.41; I2 ¼ 91%), even upon BMI adjustment. How-ever, in the subgroup of 6 prospective studies, the reductionbecame significant (SRR, 0.93; 95% CI, 0.89–0.97; I2 ¼59%), albeit with lowmagnitude. For colon cancer, the SRRsuggested borderline significant risk reduction (12 studies,SRR, 0.80, 95% CI, 0.64–1.00; I2 ¼ 76%). The SRRs fromsubgroups of studies adjusted for BMI and with prospectivedesigns did not suggest a significant reduction in cancer risk.No risk reduction was found for metformin use in

Table 2. Summary risk estimates (SRRs) and 95% CIs for all endpoints

Endpoints Groups SRR (95% CI) I2 Number of studiesa

Cancer incidence All studies 0.69 (0.52–0.90) 88 19Adjusted for BMI 0.82 (0.70–0.96) 76 11Adjusted for time-related bias 0.90 (0.89–0.91) 56 8Prospective studies 0.71 (0.47–1.07) 89 12Randomized clinical trials 0.95 (0.69–1.30) 5 5

Cancer mortality All studies 0.66 (0.54–0.81) 21 7Adjusted for BMI 0.60 (0.45–0.80) 0 5Adjusted for time-related bias 0.45 (0.16–1.26) 0 3Prospective studies 0.48 (0.23–0.97) 0 4

Single cancer sitesBreast All studies 0.88 (0.75–1.03) 60 13

Adjusted for BMI 0.82 (0.67–1.00) 48 7Adjusted for time-related bias 0.94 (0.90–0.99) 32 6Prospective studies 0.94 (0.90–0.99) 44 7

Colon All studies 0.80 (0.64–1.00) 76 12Adjusted for BMI 0.84 (0.50–1.40) 81 6Adjusted for time-related bias 0.92 (0.85–0.98) 24 3Prospective studies 0.82 (0.57–1.17) 74 5

Prostate All studies 1.06 (0.80–1.41) 91 12Adjusted for BMI 0.98 (0.68–1.40) 55 6Adjusted for time-related bias 1.25 (0.87–1.80) 96 6Prospective studies 0.93 (0.89–0.97) 59 6

Pancreas All studies 0.75 (0.49–1.15) 84 11Adjusted for time-related bias 0.48 (0.16–1.43) 83 5Time-related unbiased 0.77 (0.38–1.55) 40 5Prospective studies 0.89 (0.61–1.29) 80 6

Liver All studies 0.47 (0.28–0.79) 82 9Adjusted for time-related bias 0.65 (0.39–1.08) 38 3Prospective studies 0.78 (0.72–0.85) 52 5

Lung All studies 0.82 (0.67–0.99) 57 5Adjusted for smoking 0.95 (0.82–1.11) 57 5Adjusted for time-related bias 0.88 (0.81–0.95) 36 3Prospective studies 0.97 (0.69–1.35) 26 3

aEstimates may not correspond to number of studies.


Gandini et al.




pancreatic cancer (SRR, 0.75; 95%CI, 0.49–1.15; I2¼ 84%)even after BMI adjustment or when the analysis was limitedto 6 prospective studies (SRR, 0.89; 95%CI, 0.61–1.29; I2¼80%).We also evaluated the effect of the BMI adjustment within

studies (not only between studies) when the data wereavailable. For 12 observational studies, we were able toextract risk estimates adjusted for BMI (or a proxy such asobesity) and crude estimates in order to measure the size ofthis confounding (Supplementary Table S2). Overall, thedata show similar RR estimates between fully adjusted andcrude RR estimates, suggesting limited confounding effect.

Summary risk estimates for individual organswere obtainedonly for breast cancer, for which we had at least 4 studies.SRRs were very similar: 0.79 (0.54, 1.16) and 0.72 (0.48,1.07) for adjusted and unadjusted estimates, respectively.

These analyses focused on patients with diabetes. Insome studies, the diagnosis of diabetes was not verifiedand the comparator was "antidiabetic drug users"(57, 69, 73, 82, 83). A sensitivity analysis excluding thosestudies did not modify the results except for colorectalcancer, which became statistically significant (SRR, 0.73;95% CI, 0.58–0.92) after excluding the paper by Ruiter andcolleagues (83). When the potential bias because of insulin

A Cancer incidence

B Cancer mortality

UKPDS, 1998

Bowker, 2006

Landman, 2009Libby, 2009Bo, 2011

Melbin, 2011

Baur, 2011

0.2 0.6 0.8 1.0 1.5 3.0

Summary RR: 0.66 (0.54–0.81) I 2 = 21

SRR adjusted for BMI: 0.60 (0.45–0.80)

SRR unadjusted: 0.75 (0.22–2.46)

Schernthaner, 2004 (QUARTET-M)Hanefeld, 2004 (QUARTET-C)Kahn, 2006 (ADOPT-G)Kahn, 2006 (ADOPT-R)

Ngwana, 2012

Monami, 2009Currie, 2009Libby, 2009Home, 2010 (RECORD)Williams-Herman, 2010

Hense, 2011Yang, 2010

Currie, 2013

Lee, 2011Morden, 2011

Baur, 2011

Chung, 2013Ruiter, 2012

Hsieh, 2012Magliano, 2012

0.05 0.10 0.20 0.60 1.00 3.00 8.00



Summary RR: 0.69 (0.52–0.90) I 2 = 88

P for BMI = 0.48

P for BMI = 0.002

Figure 2. Forest plot of theassociation between metforminand cancer incidence or cancermortality. Forest plots of riskestimates from observationalstudies and randomizedcontrolled trials of metformin useand cancer incidence (A) or cancermortality (B). Black boxes indicateHRs, and horizontal linesrepresent 95% CIs. Blackdiamonds, SRR estimates. Thevertical dotted line represents arisk estimate of 1.00.






treatment as comparator was taken into account, the con-clusions did not change. No indication for publication biaswas found for any of the summary estimates.

Analysis of studies without time-related biasesThe SRRs for overall cancer incidence, organ-specific

cancer incidence, and overall cancer mortality obtainedfrom analysis of studies that avoided time-related biasesare shown in Table 2. The SRR for overall cancer incidence

was statistically significant in 8 studies (SRR, 0.90; 95%CI, 0.89–0.91; I2 ¼ 56%). The SRR for breast and colo-rectal cancer also became statistically significant: SRR,0.94 (95% CI, 0.90–0.99; I2 ¼ 32%) and SRR, 0.92(95% CI, 0.85–0.98; I2 ¼ 24%), respectively. On theother hand, the risk reduction for overall cancer mortalityand liver cancer incidence lost statistical significance(SRR, 0.45; 95% CI, 0.16–1.26 and SRR, 0.65; 95% CI,0.39–1.08, respectively). For lung cancer, the SRR

A Breast B Prostate

C Colon D Pancreas

E Liver F Lung

Currie, 2009Libby, 2009Bodmer, 2010Home (RECORD), 2010Home (ADOPT), 2010Bosco, 2011

Ferrara, 2011Morden, 2011

Chlebowski, 2013

Hsieh, 2012

Ngwana, 2012

Ruiter, 2012

Redaniel, 2012

Summary RR: 0.88 (0.75–1.03)

0.2 0.6 1.0 1.7 2.5I 2 = 60



Yang, 2004

Oliveira, 2008

Currie, 2009Libby, 2009Home, 2010 (ADOPT)Bodmer, 2012Ngwana, 2012

Ferrara, 2011Lee, 2011Morden, 2011Hsieh, 2012Ruiter, 2012

0.2 0.6 1.0 2.5

Summary RR: 0.80 (0.64–1.00) I 2 = 76



Currie, 2009Wright, 2009Home, 2010 (ADOPT)Home, 2010 (RECORD)

Ferrara, 2011Morden, 2011

Azoulay, 2011Ngwana, 2012

Lehman, 2012

Ruiter, 2012Magliano, 2012

Hsieh, 2012

0.2 0.6 0.8 1.0 1.3 1.7 2.5

Summary RR: 1.06 (0.80–1.41) I2 = 91



Oliveira, 2008Donadon, 2009 (Italy)Hassan, 2010Home, 2010 (RECORD)Lee, 2011Chen, 2013Hsieh, 2012Ruiter, 2012Chaiteerakij, 2013

0.01 0.05 0.20 0.60 1.70 10.00

Summary RR: 0.47 (0.28–0.79) I 2 = 82

Libby, 2009Ferrara, 2011Lai, 2011Bodmer, 2012Hsieh, 2012Mazzone, 2012Ruiter, 2012Smiechowski, 2012

0.3 0.6 0.8 1.0 1.3

Summary RR: 0.82 (0.67–0.99) I 2 = 66

Oliveira, 2008

Currie, 2009Li, 2009Home, 2010 (ADOPT)Home, 2010 (RECORD)Bodmer, 2012

Ferrara, 2011Lee, 2011Morden, 2011Hsieh, 2012Liao, 2012Ruiter, 2012

0.01 0.05 0.20 0.60 1.70 4.50 10.00

Summary RR:0.75 (0.49–1.15) I 2 = 84



P for BMI = 0.87

P for BMI = 0.73

P for BMI = 0.48

P for BMI = 0.55

Figure 3. Forest plots of the association betweenmetformin use and individual site cancer incidence. Forest plots of risk estimates from observational studiesand randomized controlled trials of metformin use and breast cancer (A), prostate cancer (B), colon cancer (C), pancreas cancer (D), liver cancer (E), and lungcancer (F). Black boxes indicate HRs, and horizontal lines represent 95% CIs. Black diamonds, SRR estimates. The vertical dotted line represents a riskestimate of 1.00. P for BMI is the P value for the interaction between BMI-adjusted analysis and unadjusted analysis.


Gandini et al.




suggested significant risk reduction, but adjustment forsmoking eliminated the effect.When only studies without time-related biases and

adjusted for BMI were analyzed, the SRR for overall cancerincidence and breast cancer lost significance: SRR, 0.94(95% CI, 0.88–1.01) and SRR ¼ 0.89 (95% CI, 0.56–1.41), respectively. These numbers, however, were small.

DiscussionResearch onmetformin use and cancer risk andmortality

has expanded considerably over recent years, with conflict-ing data arising from different epidemiologic, human, andanimal carcinogenesis studies. Several previous meta-anal-yses have concluded that patients with diabetes who usemetformin have significantly lower risk of overall cancerincidence (30%–40%), mortality, and site-specific cancerincidence than those who use other antidiabetic medica-tions (11–14). However, the studies included in thesemeta-analyses are susceptible to several confounders and biases.Here we focused for the first time on 2 critical issues withpotential to skew the literature, the effect of BMI, and time-related biases in observational studies. The main resultsfrom our study show that metformin use is associated withdecreased overall cancer incidence even after adjustment forBMI or time-related biases, but the magnitude of this effectis considerably smaller than observed without such adjust-ments (10%–18% vs. 31%). Simultaneous adjustment forboth BMI and time-related biases results in loss of statisticalsignificance, albeit based on few studies. This is reminiscentof results from Thakkar and colleagues, who showed adiminution in metformin’s effect when considering cohortstudies (30%) versus case–control studies (10%) versusrandomized controlled trials (no effect; ref. 14). Examina-tion of individual organ sites, which is limited by feweravailable studies for analysis, shows nonsignificant associa-tions or similarly smaller effects after adjustment. Takentogether, these data underscore the importance of under-standing the limitation in the current literature and suggestthat if metformin use is associated with a reduced risk ofcancer, the effect may be smaller than previously shown.Obesity and its surrogate, high BMI, are intimately linked

to increased risk of several cancer types (97, 98). Potentialmechanisms include both direct and indirect effects ofobesity on insulin, IGF-1, sex hormones, adipokines, andinflammation, many of which are directly impacted bymetformin. In our analysis, BMI-adjusted studies showedstatistically significant reduction in cancer incidence andmortality whereas unadjusted studies showed no effect. In12 prospective studies where it was possible to compareBMI-adjusted versus crude estimates within each study,similar RR estimates were noted, suggesting limited con-founding effect of BMI. Likewise, summary risk estimateswithin 4 breast cancer studies were similar. BMI adjustmentdid not significantly affect the cancer risk estimates forindividual organ sites, although the risk estimates for breastcancer became borderline significant. A direct correlationbetween BMI and inflammation, adipocyte size, and

aromatase expression has been shown in breast tissue fromwomen undergoing breast cancer surgery, pointing toinflammation as a potential biologic basis for the cancer–obesity connection (99). However, BMI and insulin resis-tance had a modifying effect on themetforminmodulationof breast cancer cell proliferation in a presurgical trial (16).Furthermore, metformin is the drug of choice in obesepatients with diabetes because it reduces weight (3, 100),so its use is associated with obesity. Thus, modification ofthe cancer–obesity relationship bymetformin is likely com-plex and requires extensive study.

A recent review by Suissa and Azoulay underscored theprevalence of time-related biases in observational studies,potentially leading to inflated estimates of the protectiveeffect of metformin (17). These biases include immortaltime bias (unexposed time is misclassified as drug-exposedtime), time-windowbias (differential exposure opportunitytime windows between exposed and unexposed subjects),and time-lag bias (comparison of treatment given duringdifferent stages of the disease). Of note, exclusion of time-biased studies from our analysis resulted in statisticallysignificant 10% risk reduction in overall cancer incidence,although the magnitude is substantially smaller than thepreviously reported 30% to 40%. In organ-specific analyses,reduction in colorectal cancer incidence became significant(8%), whereas liver cancer risk reduction became nonsig-nificant. Exclusion of time-biased studies in the analysis ofcancer mortality resulted in loss of statistical significance.

The effect of metformin use on cancer mortality mayresult from different mechanisms than the effect on inci-dence. Retrospective analyses suggest that diabetics treatedwith metformin during chemotherapy have better survivalthan those treated with other antidiabetic agents (28, 101).Interestingly, mouse xenograft models show that metfor-min targets breast cancer stem cells and synergizes withdoxorubicin to prevent relapse (102). If metforminincreases the effectiveness of chemotherapy, then its inclu-sion in chemotherapeutic regimens may exert a favorableimpact on survival.

This study has several limitations. These include hetero-geneity of study designs and treatment comparators. Morethan two thirds of the studies had a retrospective design,which is prone to important sources of bias. However, ouranalyses of prospective studies generally found similarSRRs, although for breast, liver, and prostate cancer, theseresults became statistically significant. A second limitationis the nature of the comparator group, which mainlyincluded treatmentwith insulin and insulin secreatagogues.These classes of agents increase insulin levels and have beenassociated with increased cancer risk (14, 55, 69, 103).Thus, the potential protective effect of metformin in anuntreated or noninsulin using population cannot be pre-cisely estimated. A third factor to consider is allocation bias,with metformin users being at different stage of diabetesthan comparators, as discussed previously with regard totime-lag bias. Generally, treatment withmetformin starts ata younger age, likely because of treatment guidelines (104)and in subjects with higher BMI, possibly because of its






weight lowering effects (105). Although the majority ofstudies adjusted for confounders such as age, we herepresented the analyses adjusting for BMI and excludingtime-biased studies. However, BMI is dynamic, and weightgain is an important risk factor for mortality of severalcancers (106). Therefore, adjustment for a single BMI valuemight be inadequate to account for confounding by BMIdynamics over time. Finally, the effect of other confounders,both known (but not adjusted for) or heretofore unrecog-nized, should not be underestimated. This is best illustratedby lung cancer, where overall and time-unbiased analysespoint to a protective effect, whereas adjustment for smok-ing, which is by far themost important cause of lung cancer,leads to loss of significance.

A critical question emerging from this meta-analysis ofstudies in diabetic patients is the generalizability to non-diabetic populations. Our data demonstrate a cancer pre-ventive signal, albeit of lesser magnitude once the appro-priate adjustments are made than previously reported. Thissignal now needs to be studied in controlled clinical trialsfocusing on carefully defined populations, such as theprediabetic population in the Diabetes Prevention ProgramTrial (3, 4), for which long-term follow-up to ascertain theeffects of metformin on cancer incidence is currently ongo-ing. However, it needs to be emphasized that existing dataaboutmetforminuse innondiabetic populations are severe-ly limited.

Clinical trials are needed to determine if the observationsseen in diabetic populations can be expanded to prediabeticor nondiabetic populations and to whom they should beexpanded for the best benefit/risk ratio. Although some of

these early phase trials are ongoing, additional informationis needed before making general recommendations orlaunching large-scale clinical efforts.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: S. Gandini, M. Puntoni, B.M. Heckman-Stoddard,B.K. Dunn, L. Ford, A. DeCensi, E. SzaboDevelopment of methodology: S. Gandini, M. Puntoni, B.M. Heckman-Stoddard, A. DeCensiAcquisitionofdata (provided animals, acquired andmanagedpatients,provided facilities, etc.): S. Gandini, M. Puntoni, B.M. Heckman-StoddardAnalysis and interpretation of data (e.g., statistical analysis, biosta-tistics, computational analysis): S. Gandini, M. Puntoni, B.M. Heckman-Stoddard, L. FordWriting, review, and/or revision of the manuscript: S. Gandini,M. Puntoni, B.M. Heckman-Stoddard, B.K. Dunn, A. DeCensi, E. SzaboAdministrative, technical, or material support (i.e., reporting or orga-nizing data, constructing databases): S. Gandini, M. Puntoni, B.M. Heck-man-Stoddard, L. FordStudy supervision: M. Puntoni, A. DeCensi, E. Szabo

Grant SupportThe studywas supported by grants from the Italian Association for Cancer

Research AIRC (IG 12072), the Italian Ministry of Health (RF-2009-1532226), and the Italian League Against Cancer (14/08) to A. DeCensi.A.DeCensi’s workwas partially performedduring a sabbatical at theDivisionof Cancer Prevention, National Cancer Institute, NIH.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

ReceivedDecember 5, 2013; revisedMay13, 2014; accepted June26, 2014;published OnlineFirst July 1, 2014.

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2014;7:867-885. Published OnlineFirst July 1, 2014.Cancer Prev Res Sara Gandini, Matteo Puntoni, Brandy M. Heckman-Stoddard, et al. Meta-analysis Taking into Account Biases and ConfoundersMetformin and Cancer Risk and Mortality: A Systematic Review and

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Metformin and Cancer Risk and Mortality: A Systematic ...Research Article Metformin and Cancer Risk and Mortality: A Systematic Review and Meta-analysis Taking into Account Biases