Cancer Biomarkers Aspirin Use and Risk of Breast Cancer ... · included studies independently using...

Review

Aspirin Use and Risk of Breast Cancer: SystematicReview and Meta-analysis of ObservationalStudiesShanliang Zhong1, Lin Chen2, Xiaohui Zhang1, Dandan Yu3, Jinhai Tang3, andJianhua Zhao1

Abstract

Previous studies concerning the association between aspirinuse and breast cancer risk yielded inconsistent results. Weaimed to investigate the association by meta-analysis. PubMedand EMBASE were searched for relevant studies. We calculatedthe summary relative risks (RR) and 95% confidence intervals(CI) using random-effects models. Seventeen cohort studiesand 15 case–control studies were included. The overall resultshowed that aspirin use decreased risk of breast cancer (RR,0.90; 95% CI, 0.85–0.95). However, there was evidence ofpublication bias and heterogeneity and the association disap-peared after correction using the trim-and-fill method. Whenstratified by study design, a significant benefit for aspirin users

was only found in population-based and hospital-based case–control studies but not in cohort or nest case–control studies.Further subgroup analyses showed that aspirin use coulddecrease risk of in situ breast tumors or hormone receptor–positive tumors and reduce risk of breast cancer in postmen-opausal women. Aspirin use may not affect overall risk of breastcancer, but decrease risk of in situ breast tumors or hormonereceptor–positive tumors and reduce risk of breast cancer inpostmenopausal women. Considering between-study signifi-cant heterogeneity and publication bias, confirmation in futurestudies is also essential. Cancer Epidemiol Biomarkers Prev; 24(11);1645–55. �2015 AACR.

IntroductionBreast cancer, one of the most frequently diagnosed cancers

among women of all racial and ethnic groups, leads to the secondmost common cancer-associated death among U.S. women (1).Despite many efforts, fewmodifiable risk factors for breast cancerhave been identified. Recently, the potential anticancer propertiesof aspirin, commonly known as pain reliever, have attractedmoreinterest (2). Aspirin display anticancer activity by inhibitingcyclooxygenase (COX; ref. 3), thus decreasing the formation ofdownstream tissue-specific signaling lipids knownasprostanoids.Prostanoids play an important role in carcinogenesis by affectingcellular proliferation, apoptosis, and angiogenesis (4). Althoughprotection of aspirin against cancer has been showed, the pro-tective effects are seen mainly in colorectal, esophageal, gastric,and endometrial cancers (3, 5). Previously, we have investigatedthe effect of aspirin intake on the mortality in breast cancer, but

only found that aspirin use has a small effect on the survival ofbreast cancer patients (6).

A number of observational studies have investigated the effectof aspirin use on the risk of breast cancer in the past three decades,but their results are conflicting rather than conclusive. A meta-analysis (7) including 33 studies has evaluated the associationand found that a decreased risk of breast cancer for aspirin userswas found in the pooled analysis of all studies [odds ratio (OR)¼0.86; 95% confidence interval (CI) ¼ 0.81–0.92] but not in arandomized controlled trial (OR, 0.98; 95% CI, 0.87–1.09). Theinvestigators concluded that regular use of aspirin may be asso-ciated with reduced risk of breast cancer. However, the subjects oftwo included articles (8, 9) were overlapped in another twoincluded articles (10, 11). The duplicated data could bias theresults. We also noted that two studies (12, 13) examining theassociation between aspirin use and mortality in breast cancerpatients but not between aspirin use and breast cancer risk werealso included in that meta-analysis. In addition, previous meta-analysis has not performed a subgroup analysis according tohormone receptor status, menopausal status, or cancer stage.Since the meta-analysis, seven large observational studies havepublished. Therefore, we performed a meta-analysis with allavailable studies to explore the association between aspirin useand risk of breast cancer. Besides, we also performed a dose–response analysis to further evaluate the potential dose–responserelations.

Materials and MethodsLiterature search

We searched PubMed (from 1980 to present) and Embase(from 1977 to present) using the following terms: "aspirin" or

1Center of Clinical Laboratory Science, Jiangsu Cancer Hospital Affil-iated to Nanjing Medical University, Nanjing, China. 2Department ofOncology, Xuzhou Medical College, Xuzhou, China. 3Department ofGeneral Surgery, JiangsuCancerHospital Affiliated toNanjingMedicalUniversity, Nanjing, China.

Note: Supplementary data for this article are available at Cancer Epidemiology,Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

Corresponding Author: Jianhua Zhao, Center of Clinical Laboratory Science,Jiangsu Cancer Hospital Affiliated to Nanjing Medical University, Baiziting 42,Nanjing 210009, China. Phone: 8625-8328-3334; Fax: 8625-8335-1406; E-mail:[email protected]

doi: 10.1158/1055-9965.EPI-15-0452

�2015 American Association for Cancer Research.

CancerEpidemiology,Biomarkers& Prevention

www.aacrjournals.org 1645

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"acetylsalicylic acid" or "non-steroidal anti-inflammatory drug"or "non-steroidal anti-inflammatory drugs," and "breast cancer"and "risk" or "incidence". The latest date of this search was April2015. All cohort or case–control studies evaluating the relation-ship between aspirin use and risk of breast cancer were eligible,without language restriction. Reference lists from relevant articleswere examined manually to further identify potentially relevantstudies. All searches were conducted independently by tworeviewers; differences were checked by the two and resolved bydiscussion.When two ormore studies presented possible overlap,we included the one with largest populations.

Inclusion criteriaAll the studies were included in this meta-analysis if they met

the following criteria: (i) the exposure of interest was aspirin use;(ii) theoutcomeof interestwas breast cancer; (iii) the studydesignwas case–control or cohort; and (iv) risk estimates and 95% CIswere reported (or information to calculate them).

Data extractionTwo independent investigators extracted data from the eligible

articles. The extracted data included the last name of first author,year of publication, origin of the study, follow-up period, studydesign, sample size, aspirin use, risk estimates, and corresponding95%CIs, and covariates adjusted for in themultivariable analysis.For studies providedmore than one risk estimate, we extracted theone that was adjusted for the greatest number of confoundingfactors. Discrepancies were resolved by consensus, involving athird investigator.

Study quality assessmentTwo investigators assessed the methodological quality of

included studies independently using the nine-star NewcastleOttawa scale (NOS; ref. 14). Each study was evaluated based oneight items, categorized into three broad perspectives, includingselection, comparability, and outcome, for cohort studies orexposure for case–control studies. We considered studies with ascore of 7 or greater as high quality. Discrepancies were resolvedby discussion or through consultation with a third investigator.

Statistical analysisBecause outcomes were relatively rare, the ORs and HRs were

considered approximations of relative risks (RR). Summaryestimates of RRs and 95% CIs were obtained using a ran-dom-effects model where the restricted maximum likelihoodestimator was used to evaluate the interstudy heterogeneity (15,16). We calculated prediction interval (PI) of summary esti-mate for the random effects model to depict the uncertaintyaround the estimate (17). If studies did not report a summaryrisk estimate for aspirin use, a summary risk estimate wascalculated using risk estimates for each of the aspirin usecategories (18–33). Interstudy heterogeneity was estimatedusing a c2-based Q test (34), with a P value of <0.10 consideredstatistically significant (35). We also calculated the I2 quantity(34), which lies between 0% and 100%. A value of 0% indicatesno observed heterogeneity and larger values indicate increasingheterogeneity. Metaregression was conducted to further explorethe sources of heterogeneity. Sensitivity analyses were per-formed to reflect the influence of individual data on summaryHRs. Finally, the potential for publication bias was examined

using Begg and Egger regression test (36). Where publicationbias was found, the trim-and-fill method was used to estimatethe potential influence of this bias on pooled summary esti-mates (37).

A two-stage random-effects dose–response meta-analysis wasperformed to compute the trend from the correlated log RRestimates across levels of aspirin use into account the between-study heterogeneity (38). A potential nonlinear relation betweenaspirin use and risk ofdeathwas investigatedusing restricted cubicsplines with three knots at the 25th, 50th, and 75th percentiles ofthe exposure distribution. Then, the study-specific estimates werecombined using the restricted maximum likelihood method in amultivariate random-effects meta-analysis (39). A P value fornonlinearity was calculated by testing the null hypothesis thatthe coefficient of the second spline is equal to zero. For each study,we calculated the median level of aspirin use for each category byassigning the midpoint of upper and lower boundaries in eachcategory as the average aspirin use level. When the highestcategory was open-ended, we assigned the lower end value ofthe category multiplied by 1.5. Studies were not eligible if therequired data were not reported or could not be estimated. All ofthe statistical analyses were done with R software, version 3.1.1,using the packages metafor (40) and dosresmeta (41). All statis-tical tests were two-sided.

ResultsCharacteristics of the studies

Figure 1 presents the process of study selection. Two thousandsix hundred and ten abstracts and titles were identified andassessed, and 45 studies were evaluated in detail with regard totheir fulfillment of the inclusion criteria. Four articleswere exclud-ed as the exposure of interestwas not aspirin use, or nousable datawere reported (42–45). Nine studies were excluded because their

Figure 1.Flow chart of the selection of publications included in the meta-analysis.

Zhong et al.

Cancer Epidemiol Biomarkers Prev; 24(11) November 2015 Cancer Epidemiology, Biomarkers & Prevention1646



Table

1.Cha

racteristics

ofstud

iesinclud

edin

themeta-an

alysis

First

author

Yea

rCoun

try

Follo

w-upperiod

Stud

ydesign

Sample

size

Asp

irin

use

RR(95%

CI)

Cova

riatead

justmen

t

Brasky

2014

USA

1993–

2010

Coho

rt126,689

Nonu

ser

HR1.0

0Age,

observationa

lstud

yen

rollm

ent,

horm

one

therap

ytrialenrollm

ent,diet

modificationtrialenrollm

ent,calcium/

vitamin

Dtrialenrollm

ent,U.S.reg

ion,

education,

ethn

icity,

height,B

MI,

phy

sicalactivity,alco

holconsum

ption,

pack-ye

arsofsm

oking

,fruitan

dve

getab

leco

nsum

ption,

redmea

tco

nsum

ption,

family

histories

of:

breastcancer,cervicalcancer,

endometrial

cancer,a

ndco

lorectal

cancer;screen

ingfor:breastcancer,

coloncancer,and

cervicalcancer;age

atmen

arche,

ageat

men

opau

se,

gravidity,ag

eat

firstbirth,d

urationof

estrogen

therap

y,durationof

combined

postmen

opau

salho

rmone

therap

y,hy

sterectomystatus,

multivitamin

use,

useof

antihy

pertensivemed

ication,

history

ofco

rona

ryhe

artdisea

se,u

seof

cholesterol-loweringmed

ication,

history

ofa

rthritis,history

ofm

igraine,

history

ofulcer,an

dother

NSAID

use.

Med

ian9.7

years

Inco

nsistent

use

0.99(0.91–1.0

9)

Consistent

use

1.11(1.00–1.24)

Cui

2014

USA

2001–20

11PCC

5,078

Nonu

sers

OR1.0

0Persona

lhistory

ofben

ignbreast

disea

se,fi

rst-deg

reefamily

history

of

breastcancer,m

enopau

salstatus,

history

oflivebirth,a

geat

firstlive

birth,u

seofho

rmone

replacemen

ttherap

y,regular

exercise,a

lcoho

lco

nsum

ption,

andcigarette

smoking

status.

Eve

rusers

0.82(0.69–0

.99)

Hollestein

2014

The

Nethe

rlan

ds

1998–2010

Coho

rt55

,597

Nonu

sers

HR1.0

0Age,

sex,un

ique

number

ofdispen

sing

san

dun

ique

number

ofh

ospitalizations

intheye

arpriorto

startoffollo

w-up.

Med

ian9.7

years(IQR2–

7)Users

1.02(0.97–

1.08)

Lee

2012

China

2002–

2008

PCC

67,38

80–27cD

DD

OR1.0

0Urban

ization,

inco

me,

diabetes

mellitus,

metform

inusag

e,statin

usag

e,estrogen

usag

e,an

dprogesterone

usag

e.

28–3

64cD

DD

0.92(0.87–

0.99)

�365cD

DD

0.86(0.79–0

.93)

Zha

ng20

12USA

1980–2

008

Coho

rt84,602

Nonu

ser

RR1.0

0Age,ag

eat

men

arche,he

ight,B

MIatag

e18

years,weight

chan

gesinceag

e18

years,parityan

dag

eat

firstbirth,

history

ofbreastcancer

inparen

tor

sibling,h

istory

ofben

ignbreast

disea

se,alcoho

lconsum

ption,phy

sical

activity,a

ndpostmen

opau

sal

horm

one

use.

28ye

ars

Past

0.97(0.88–1.08)

Current

0.96(0.87–

1.05)

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Aspirin Use and Risk of Breast Cancer

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Table

1.Cha

racteristics

ofstud

iesinclud

edin

themeta-an

alysis

(Cont'd)

First

author

Yea

rCoun

try

Follo

w-upperiod

Stud

ydesign

Sample

size

Asp

irin

use

RR(95%

CI)

Cova

riatead

justmen

t

Bardia

2011

USA

1986–2

005

Coho

rt26

,580

Nev

erRR1.0

0Age,

education,

family

history

ofbreast

cancer,a

geat

men

arche,

ageat

men

opau

se,p

arity/ag

eat

firstlive

birth,use

ofo

ralcontraceptive

s,useof

horm

one

therap

y,BMIin

1992,

BMIat

age18

years,relative

weight

atag

e12,

history

ofosteo

arthritis,history

of

rheu

matoid

arthritis,sm

oking

,use

of

alco

hol,sm

oking

,and

phy

sicalactivity

leve

l.

13ye

ars

Eve

r0.80(0.71–0.90)

Bosco

2011

USA

1995–

2007

Coho

rt59

,000

Nonu

seRR1.0

Agean

dque

stionn

aire

cyclean

dad

justed

fored

ucation,

BMIat

age18,

vigorous

activity,fem

aleho

rmone

use,

andsm

oking

.Modelsforaspirin

adjusted

furthe

rforother

NSAIDs,

other

NSAIDsad

justed

foraspirin,and

acetam

inophe

nforaspirin

andother

NSAIDs.

Form

eruse

1.15(0.95–

1.38)

Current

use

0.79(0.66–0

.95)

Brasky

2010

USA

1996–2001

PCC

3,28

5Nonu

sers

OR1.0

0Age,

race,e

ducation,

ageat

men

arche,

ageat

men

opau

se,p

arity,

useof

horm

one

therap

y,ben

ignbreast

disea

se,fam

ilyhistory

ofbreast

cancer,a

ndother

NSAID

use.

Users

0.80(0.68–0

.94)

Cronin–

Fen

ton

2010

Den

mark

1991–20

06

NCC

90,14

5Nev

erOR1.0

0Use

ofho

rmone

replacemen

ttherap

y,rheu

matoid

arthritisan

dmigraine.

Eve

r0.98(0.90–1.07)

Eliassen

2009

USA

1989–2

003

Coho

rt112,29

2Nonu

sers

RR1.0

0Ageat

men

arche,

height,B

MIat

age18

years,weight

chan

gesinceag

e18

years,oralcontraceptive

use,

parity

andag

eat

firstbirth,a

lcoho

lco

nsum

ption,history

ofben

ignbreast

disea

se,fam

ilyhistory

ofbreast

cancer.

14ye

ars

Pastusers

1.21(1.03–

1.41)

Current

users

1.07(0.89–1.29)

Friis

2008

Den

mark

1993–

2003

Coho

rt28

,695

Nonu

sers

RR1.0

0Age,scho

oleducation,parity,nu

mber

of

births,useofHRTan

dhistory

of

ben

ignbreasttumour

surgery.

Ave

rage7.5ye

ars(Ran

ge

0.1–

10.1)

Users

1.31(1.12

–1.53)

Gierach

2008

USA

1995–

2003

Coho

rt126,12

4Nev

erRR1.0

0Age,

race,a

geat

firstbirth,h

orm

one

therap

yuse,

number

ofbreast

biopsies,a

lcoho

lintake,h

istory

of

hypertension,

family

history

ofbreast

cancer

infirst-deg

reerelative

and

freq

uencyofuseofopposite

NSAID

type.

Ave

rage3.43ye

arsforcases

(ran

ge,

1day

to7.13

years);

6.75ye

arsforno

ncases

(ran

ge,

1day

to7.17

years)

<1times/w

eek

0.95(0.89–1.03)

1–6times/w

eek

0.95(0.87–

1.04)

�1times/day

0.93(0.85–

1.01)

Rea

dy

2008

USA

2000–2004

Coho

rt35

,323

None

HR1.0

0Age,

race,B

MI,family

history

ofbreast

cancer,h

istory

ofbreastbiopsy,

mam

mogram

in2ye

arspriorto

baseline,ag

eat

men

arche,ag

eat

first

birth,a

geat

men

opau

se,h

istory

of

surgical

men

opau

se,y

ears

of

combined

estrogen

andprogesterone

horm

one

therap

y,multivitamin

use

andalco

holu

seas

wella

sad

justmen

tforuseofother

categories

ofNSAIDs.

Any

0.99(0.80–1.23)

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Zhong et al.




Table

1.Cha

racteristics

ofstud

iesinclud

edin

themeta-an

alysis

(Cont'd)

First

author

Yea

rCoun

try

Follo

w-upperiod

Stud

ydesign

Sample

size

Asp

irin

use

RR(95%

CI)

Cova

riatead

justmen

t

Gallicchio

2007

USA

1989–2

006

Coho

rt15,651

Nonu

sers

RR1.0

0Age.

Users

0.90(0.70–1.16

)Gill

2007

USA

1993–

2002

Coho

rt98,920

Current

users

Age,

ethn

icity,

BMI,family

history

of

breastcancer,e

ducation,

mam

mography

screen

ing,a

lcoho

lintake,a

geat

men

arche,

ageat

first

liveb

irth,n

umber

ofchild

ren,

men

opau

salstatus,a

geat

men

opau

se,h

orm

one

replacemen

ttherap

y,an

dallp

ainmed

icationuse.

Nonu

sers

HR1.0

0�1

year

1.01(0.79–1.30)

2–5ye

ars

0.89(0.72–

1.09)

�6ye

ars

1.05(0.88–1.25)

Pastusers

Nonu

sers

HR1.0

0�1

year

1.07(0.87–

1.32)

2–5ye

ars

0.95(0.75–

1.22)

�6ye

ars

1.04(0.84–1.27)

Jaco

bs

2007

USA

1992–

2003

Coho

rt76

,303

Noreported

use

RR1.0

0Age,

race,e

ducation,

smoking

,BMI,

phy

sicalactivityleve

l,useofho

rmone

replacemen

ttherap

y,history

of

mam

mography

,history

ofco

lorectal

endoscopy,useofno

naspirin

NSAIDs,

andhistory

ofhe

artattack,d

iabetes,

andhy

pertension.

Less

than

daily,

low–d

ose,o

rpastuse

1.10(1.00–1.21)

Current

daily

use,

<5ye

ars

1.02(0.88–1.19

)

Current

daily

use,

�5ye

ars

0.83(0.63–

1.10)

Kirsh

2007

Can

ada

1996–1998

PCC

4,872

Nonu

sers

OR1.0

0Age,

arthritis,an

dben

ignbreastcysts.

Users

0.75(0.64–0

.88)

Slattery

2007

USA

1999–2004

PCC

4,850

No

OR1.0

0Age,

stud

ycenter,referen

tye

arBMI,

lifetim

ephy

sicala

ctivityscore,p

arity,

andpercentag

eNativeAmerican

ancestry.

Yes

0.92(0.74–1.15

)

Harris

2006

USA

2003–

2004

HCC

770

Nonu

sers

OR1.0

0Age,

bodymass,parity,

men

opau

sal

status,fam

ilyhistory,smoking

,and

alco

holintake.

Users

0.49(0.26–0

.94)

Marshall

2005

USA

1995–

2001

Coho

rt114,460

Noregular

use

RR1.0

0Race,

BMI,first-deg

reefamily

history

of

breastcancer,m

enopau

sala

ndho

rmone

therap

yusestatus,smoking

,alco

holintake,p

hysicala

ctivity,

mam

mography

history,b

reastbiopsy

history,p

aritystatus

before

age30

,an

dne

ighb

orhoodsocioecono

mic

status.

Reg

ular

use

1–6days/wee

k1.0

9(0.98–1.22)

Daily

0.98(0.86–1.13

)

Rah

me

2005

Can

ada

1998–2

002

NCC

46,080

Notexposed

OR1.0

0Age,mam

mography

inye

ars2or3prior

toindex

date,breastprocedurein

the

prior3ye

ars,ben

ignne

oplasm

ofthe

breastintheprior3

years,other

breast

disea

sein

theprior3ye

ars,estrogen

replacemen

ttherap

yin

thepriorye

ar,

andvisitto

agyn

ecologistin

theprior

year.

�100mg/day

0.91(0.71–1.16)

>100mg/day

0.75(0.64–0

.89

Swed

e20

05

USA

1982–

1998

HCC

4,861

Nev

erOR1.0

0Ageat

men

arche,

ageat

1stbirth,B

MI,

history

of1st-deg

reerelative

with

breastcancer,a

ndhistory

ofben

ign

breastdisea

se.

Occasiona

l0.80(0.67–

0.96)

Reg

ular

0.85(0.74–0

.97)

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Table

1.Cha

racteristics

ofstud

iesinclud

edin

themeta-an

alysis

(Cont'd)

First

author

Yea

rCoun

try

Follo

w-upperiod

Stud

ydesign

Sample

size

Asp

irin

use

RR(95%

CI)

Cova

riatead

justmen

t

Zha

ng20

05

USA

1976

–2002

HCC

3,960

Nev

erused

OR1.0

0Age,ye

arofinterview

,studycenter,race,

yearsofed

ucation,

ben

ignbreast

disea

se,n

umber

ofphy

sician

visits

2ye

arsbefore

hospitalization,

duration

offemaleho

rmone

supplemen

tuse,

durationofo

ralcontraceptive

use,ag

eat

men

arche,

ageat

men

opau

se,a

ge

atfirstbirth,p

arity,

alco

hol

consum

ption,

family

history

ofbreast

cancer,p

racticeofbreastself-

exam

ination,

andBMI.

Reg

ular

use

0.86(0.64–1.16

)

GarciaRodrigue

z20

04

UK

1995–

2001

NCC

23,708

Nouse

OR1.0

0Age,

calend

arye

ar,B

MI,sm

oking

,alco

hol,priorben

ignbreastdisea

se,

NSAIDs,paracetam

ol,steroidan

dHRT

use.

Current

use

0.88(0.75–

1.04)

Pastuse

0.90(0.70–1.15

)

Terry

2004

USA

1996–1997

PCC

2,862

Nonu

sers

OR1.0

0Ageat

diagno

sis,migrainehe

adache

,BMI,an

dsimultane

ously

adjusted

for

theother

typeofmed

icationuse.

Eve

rusers

0.80(0.66–0

.97)

Harris

2003

USA

From

1992

Coho

rt80,741

0–11months

RR1.0

0Age.

Ave

rage43months

1–4ye

ars

0.90(0.72–

1.13)

�5ye

ars

0.81(0.66–0

.99)

Moorm

an20

03

USA

1996–2000

PCC

2,631

Nonu

sers

OR1.0

0Agean

drace.

Eve

rusers

0.4

(0.3–0

.7)

Harris

1999

USA

1991–1996

Coho

rt32

,505

0,<

1pill/w

eek

RR1.0

0Age.

Ave

rage4.7

years

1–3pills/wee

k0.57(0.40–0

.81)

�4pills/wee

k0.64(0.45–

0.90)

Neu

gut

1998

USA

1989–1992

HCC

428

Nonu

sers

OR1.0

0Age,

education,

parity,

men

opau

sal

status,a

ndfamily

history

ofbreast

cancer.

Users

0.80(0.35–

1.80)

Harris

1996

USA

Notstate

PCC

2,045

Nonu

sers

OR1.0

0Age,

parity,

men

opau

salstatus,a

ndfamily

history.

Users

0.69(0.46–0

.99)

Schreinem

ache

rs1994

USA

1971–1987

Coho

rt7,029

Nonu

sers

RR1.0

0Age.

Ave

rage12.4

years

Users

0.72(0.52–

1.00)

Pag

anini-Hill

1989

USA

1981–1988

Coho

rt7,439

Nonu

sers

RR1.0

0None

.Users

1.00(0.76–1.33)

Abbreviations:B

MI,bodymassindex;cDDD,cum

ulativedefi

neddailydose;C

I,co

nfiden

ceinterval;H

CC,hospital-based

case–controlstudy;NCC,nestcase–controlstudy;NSAID,nonsteroidalan

ti-infl

ammatory

drugs;PCC,

population-based

case–controlstudy.

Zhong et al.




data duplicated or overlapped with other articles (8, 9, 46–52).Nevertheless, one of these studies (46) was included in thesubgroup analysis by hormone receptor status, and anotherstudy (48) was included in dose–response analysis. Finally, 17cohort studies (10, 18, 20–25, 29–31, 53–58) and 15 case–control studies (11, 19, 26–28, 32, 33, 59–66) involving1350,913 participants were selected for meta-analysis. Table 1shows the characteristics of the included studies. Supplemen-tary Tables S1 and S2 summarize the methodological quality ofall the included studies. The NOS results showed that theaverage score was 6.9 (range 4–9) for cohort studies and 6.3(range 4–9) for case–control studies. There were 18 studies witha score of 7 or more.

Evidence synthesisFigure 2 presents the pooled RR of the association between

aspirin use and risk of breast cancer. When the association ofaspirin use on breast cancer risk was analyzed as users versusnonusers, a RR of 0.90 (95% CI, 0.85–0.95, P < 0.01; 95% PI,0.68–1.19) was found. In stratified by study design, a significantbenefit for aspirin users was only found in population-basedcase–control (PCC) studies (RR, 0.80; 95% CI, 0.73–0.88, P <0.01; 95%PI, 0.65–0.98) and hospital-based case–control (HCC)studies (RR, 0.82; 95% CI, 0.75–0.91, P < 0.01; 95% PI, 0.75–0.91; Fig. 2). In the subgroup analysis by estrogen receptor (ER)or/and progesterone receptor (PR) status, a decreased breastcancer risk was found for aspirin users with ER-positive tumors(RR, 0.90; 95% CI, 0.81–0.99, P ¼ 0.04; 95% PI, 0.68–1.19), PR-positive tumors (RR, 0.87; 95% CI, 0.77–0.98, P ¼ 0.02; 95% PI,0.67–1.13), and ER- and PR-positive tumors (RR, 0.88; 95% CI,0.79–0.99, P¼ 0.04; 95% PI, 0.68–1.14; Fig. 3). When stratifyingby menopausal status, the results revealed that postmenopausalwomenwhoused aspirinhad aRRof 0.86 (95%CI, 0.80–0.93,P<0.01; 95% PI, 0.75–1.00) for breast cancer risk (Fig. 3). Furtheranalysis by cancer stage showed that aspirin use was only asso-ciated with decreased risk of in situ breast cancer (RR, 0.79; 95%CI, 0.71–0.88, P < 0.01; 95% PI, 0.71–0.88; Fig. 3).

Dose–response meta-analysisThe dose–response effects of aspirin on breast cancer risk were

assessed with 14 studies (10, 11, 18, 20, 22, 24, 27–29, 48, 54, 55, 60, 63). Among these studies, exposure to aspirinwas expressed in duration of exposure (11, 18, 20, 24, 27–29, 55, 63) or frequency (e.g., pills/week; refs. 10, 22, 27, 48, 54,55, 60, 63). If exposure to aspirin was expressed in a times/week(or days/week) scale (10, 22, 55), we assumed the scale equals topills/week. A linear relationship was found for both duration (Pfor nonlinearity¼0.29) and frequency (P for nonlinearity¼0.88)of aspirin use (Fig. 4). A 1-year increment in duration of exposureto aspirin conferred aRRof 0.98 (95%CI, 0.97–1.00,P¼0.02) forbreast cancer risk (Fig. 4A). The risk of breast cancer was decreasedby 4% for every 3 pills/week increment in aspirin use (RR, 0.96;95% CI, 0.92–0.99, P ¼ 0.02; Fig. 4B).

Sensitivity analysis and publication biasFrom the results of the leave-one-out sensitivity analysis, the

summary RR was not materially altered (data not shown). Weexplored the source of heterogeneity by country (United Statesand others), study design (cohort, NCC, PCC, and HCC), pub-lication year, methodological quality (continuous variables), andsample size (�8,000 and <8,000 subjects) with metaregression.

The results revealed that noneof them contributed to the source ofheterogeneity (data not shown).

The results of Begg (P < 0.05) and Egger tests (P ¼ 0.01) haveshown the evidence of publication bias. Then, trim-and-fill meth-od was used to correct the result, and nine potential missingstudieswere required in the right side of the funnel plot in order tomake the plot symmetric (Supplementary Fig. S1). However, thecorrection achieved a nonsignificant reduction of breast cancerrisk for aspirin users (RR, 0.95; 95%CI, 0.88–1.02, P¼ 0.12; 95%PI, 0.65–1.38).

DiscussionThe current meta-analysis investigated the relationship

between aspirin use and risk of breast cancer involving1350,913 participants. The summary results, as derived from17 cohort studies and 15 case–control studies, indicated that theaverage effect of aspirin use was associated with decreased risk ofbreast cancer. However, there was evidence of publication biasand the association between aspirin use and breast cancer risk nolonger existed after correction using the trim-and-fill method. We

Figure 2.Pooled analyses and subgroup analyses by study design for theassociation between aspirin use and risk of breast cancer. The squares andhorizontal lines correspond to the study-specific relative risk and95%CIs. The area of the square is proportional to the inverse of the sumof thebetween studies variance and the study-specific variance. The diamondrepresents the pooledmultivariate relative risk and 95% CI. The dotted line ofthe diamond indicates the bounds of the 95% PI.





Figure 3.Subgroup analyses by hormone receptor status, menopausal status, and cancer stage for the association between aspirin use and risk of breast cancer.The squares and horizontal lines correspond to the study-specific relative risk and 95% CIs. The area of the square is proportional to the inverse of the sum of thebetween studies variance and the study-specific variance. The diamond represents the pooled multivariate relative risk and 95% CI.

Zhong et al.




also noted significant heterogeneity between included studies.Weexplored the source of heterogeneity using meta-regression andsubgroup analysis but failed to find convincing explanations forthe significant heterogeneity. When stratified by study design, asignificant benefit for aspirin users was only found in PCC andHCC studies but not in cohort and nest case–control (NCC)studies. PCC and HCC studies give a lower level of evidence thancohort and NCC studies and might provide spurious resultsbecause of selection bias and recall bias, which might havecontributed to the different results. Considering above men-tioned, we conclude that aspirin use may not be associated withdecreased risk of breast cancer overall.

In subgroup analysis by ER or/and PR status, a benefit foraspirin use on breast cancer risk was only found in hormonereceptor–positive tumors. Evidence suggested that endogenousestrogens are important risk factors for breast cancer (67). Post-menopausal women who are regular users of aspirin showedlower estrogen levels compared with nonusers, which couldpotentially lower the risk of breast cancer (68). As our resultindicated, the effect for ever use of aspirin was beneficial amongpostmenopausal women but not premenopausal women. The

different effect of aspirin may be due to postmenopausal womentend to have more hormone receptor–positive tumors (69).Further analysis by cancer stage showed that aspirin use was onlyassociated with decreased risk of in situ breast cancer. AlthoughCOX2 overexpression has been observed in both invasive and insitu breast tumors, a higher frequency of COX2 expression wasobserved in in situ tumors suggesting that the potential therapeuticimpact of COX2 inhibitionmay bemore relevant for in situ breastcancer than invasive tumors (70).

We further explored the dose–response relationship betweenaspirin use and risk of breast cancer. Our results indicated a linearand borderline significant relationship between aspirin use andbreast cancer risk. The risk of breast cancer was decreased by 2%for 1-year increment of aspirin use. There was a 4% breast cancerrisk reduction for every 3 pills/week increment in aspirin use.Considering the small effect, long-term or high-frequency aspirinuse is not recommended for prevention of breast cancer.

There is significant heterogeneity between included studies.However, we failed to find the source of heterogeneity. Severalreasons may account for the heterogeneity. First, seven cohortstudies reassessed exposure to aspirin during the course offollow-up, while ten cohort studies assessed the exposure onlyat baseline (Supplementary Table S1), which can lead to immor-tal time bias (71). Second, misclassification of aspirin use islikely to impact on the effect estimates of aspirin use. Moststudies assessed the exposure to aspirin based on self-reported,while some studies obtained exposure data from prescriptiondatabase or medical record. Self-reported data are not expectedto be accurately recalled. Third, studies conducted among popu-lations are varying in age and ethnicity. All of these may partlyexplain the significant heterogeneity between studies.

The potential limitations of our study should be consideredwhen interpreting the results. First, there was evidence of pub-lication bias and heterogeneity among included studies. Second,although included studies had adjusted for important riskfactors, unmeasured factors related to aspirin use may also haveinfluenced results of individual studies. Third, in the subgroupanalyses, the limited study number with relatively small samplesize in each subgroup may not have enough statistical power toexplore the real association. Fourth, the included studies weremajor conducted in Western countries, and hence the resultsshould be extrapolated to other populations with caution.

In conclusion, aspirin use may not affect overall risk of breastcancer, but decrease risk of in situ breast tumors or hormonereceptor–positive tumors and reduce breast cancer risk in post-menopausal women. Considering the heterogeneity and publi-cation bias, our results on the effect of aspirin use on risk of breastcancer overall or in the subgroups should be confirmed in futurestudies with well-controlled confounding factors, long enoughfollow-up time, and more accurate assessment of aspirin use,including quantity, frequency, and duration of use.

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

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received May 4, 2015; revised June 12, 2015; accepted August 4, 2015;published OnlineFirst August 27, 2015.

Figure 4.The dose–response analysis with restricted cubic splines in a multivariaterandom-effects dose–response model for the relationships of duration ofaspirin use and risk of breast cancer (A) and frequency of aspirin use and riskof breast cancer (B). The solid line and the short dash line represent theestimated relative risk and its 95% CI.





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