Intrauterine environments and breast cancer risk: meta-analysis and systematic review

bcr1850 BCJ Research article Intrauterine environments and breast cancer risk: meta-analysis and systematic review Park Kyung Sue suepark@snu.ac.kr Kang Daehee dhkang@snu.ac.kr McGlynn A Katherine mcglynnk@mail.nih.gov Garcia-Closas Montserrat garciacm@exchange.nih.gov Kim Yeonju kyju@snu.ac.kr Yoo Young Keun kyyoo@plaza.snu.ac.kr Brinton A Louise brintonl@exchange.nih.gov

Department of Preventive Medicine, Seoul National University College of Medicine, Yeongeon-dong, Jongro-gu, Seoul 110-799, Seoul, Republic of Korea

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Executive Blvd, Rockville, Maryland 20892-7234, USA

Cancer Research Institute, Seoul National University, Yeongeon-dong, Jongro-gu, Seoul 110-799, Seoul, Republic of Korea

National Cancer Center, Madu1-Dong, Ilsandong-Gu, Goyang-Si, Gyeonggi-Do 410-769, Republic of Korea

Breast Cancer Research 1465-5411 2008 10 1 R8 http://breast-cancer-research.com/content/10/1/R8 18205956 10.1186/bcr1850 20 7 2007 23 8 2007 30 9 2007 21 1 2008 21 01 2008 2008 Park et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Introduction

Various perinatal factors, including birth weight, birth order, maternal age, gestational age, twin status, and parental smoking, have been postulated to affect breast cancer risk in daughters by altering the hormonal environment of the developing fetal mammary glands. Despite ample biologic plausibility, epidemiologic studies to date have yielded conflicting results. We investigated the associations between perinatal factors and subsequent breast cancer risk through meta-analyses.

Methods

We reviewed breast cancer studies published from January 1966 to February 2007 that included data on birth weight, birth order, maternal age, gestational age, twin status, and maternal or paternal smoking. Meta-analyses using random effect models were employed to summarize the results.

Results

We found that heavier birth weights were associated with increased breast cancer risk, with studies involving five categories of birth weight identifying odds ratios (ORs) of 1.24 (95% confidence interval [CI] 1.04 to 1.48) for 4,000 g or more and 1.15 (95% CI 1.04 to 1.26) for 3,500 g to 3,999 g, relative to a birth weight of 2,500 to 2,599 g. These studies provided no support for a J-shaped relationship of birthweight to risk. Support for an association with birthweight was also derived from studies based on three birth weight categories (OR 1.15 [95% CI 1.01 to 1.31] for ≥4,000 g relative to <3,000 g) and two birth weight categories (OR 1.09 [95% CI 1.02 to 1.18] for ≥3,000 g relative to <3,000 g). Women born to older mothers and twins were also at some increased risk, but the results were heterogeneous across studies and publication years. Birth order, prematurity, and maternal smoking were unrelated to breast cancer risk.

Conclusion

Our findings provide some support for the hypothesis that in utero exposures reflective of higher endogenous hormone levels could affect risk for development of breast cancer in adulthood.

Introduction

Intrauterine environmental exposures to endogenous or exogenous hormones, notably estrogens, may influence the subsequent development of breast cancer in offspring 1. During pregnancy, levels of circulating estrogens and other hormones with growth-enhancing properties are at least 10 times higher than those in nonpregnant women, with increases seen with advancing gestational age 234. The hypothesis that breast cancer in daughters may be influenced by the intrauterine environment is receiving increased attention 5. Perinatal factors, including birth weight, birth order, maternal age, gestational age, twin status, and parental smoking, have been postulated as risk factors for breast cancer through altered hormonal influences on the developing fetal mammary glands 1. Despite ample biologic plausibility, this hypothesis is difficult to evaluate directly 5, and previous epidemiologic studies have reported conflicting results 67.

Here we review the epidemiologic studies that have assessed the association between perinatal factors and breast cancer risk in daughters. A meta-analytical approach was applied in order to clarify further the possible role played by the intrauterine environment in the etiology of breast cancer.

Materials and methods

Identification of studies

The data retrieved for the systematic review were based on searches of all published papers, letters, abstracts, and review articles on birth weight, birth order, maternal age, gestational age, twin status, and maternal or paternal smoking and breast cancer using the MEDLINE database from January 1966 through February 2007. We used keywords combining text words, with terms for six perinatal factors combined with terms for breast cancer (Table 1). We also manually searched the reference lists of all studies that fulfilled the inclusion criteria for further relevant publications. Articles were included in our systematic review if they fulfilled the following three criteria: the exposure status of at least one of six perinatal risk factors of interest was compared with nonexposure status; the outcome focused on the daughter's breast cancer morbidity or mortality using an epidemiologic study design (case-control design, data linkage study, or cohort study design); and the article was written in English language. We excluded animal studies, investigations focusing on male breast cancer, reviews, and studies that did not provide separate relative risks for breast cancer. We also excluded studies if odds ratios (ORs) or relative risks (RRs) were not specifically provided, raw data were not available for calculation of risks, or the emphasis of analyses was on hazard ratios or standardized incidence ratios.

Table 1

Search terms used in systematic review

Subject

Search term

Breast neoplasm

Breast neoplasms, subsequent breast neoplasm, breast neoplasm and daughter

Birth weight

Cirth weight, birthweight, birth size

Birth order

Birth order, birth rank

Maternal age

Maternal age, mother's age, parental age

Gestational age

Gestational age, preterm, prematurity, abruption placenta, pre-eclampsia, eclampsia

Twinship

Twin, twining, multiple births, multiple pregnancy, monozygote twin, dizygote twin,

Parental smoking

Maternal smoking, mother's smoking, paternal smoking, father's smoking, parental smoking

Others

Prenatal factors, perinatal factors, intrauterine environment, intrauterine factor, In-utero exposure

Statistical analyses

For the purposes of meta-analysis, birth weight was classified in three different ways: five categories (<2,500 g, 2,500 to 2,999 g [referent], 3,000 to 3,499 g, 3,500 to 3,999 g, and ≥4,000 g); three categories (<3,000 g [referent], 3,001 to 3,999 g, and ≥4,000 g); and two categories (<3,000 g [or ≤3,000 g; referent] and ≥3,000 g [or >3,000 g]). Birth order was examined using two different categorical schemes: 1 (referent) versus ≥2; and 1 (referent), 2 to 4, and ≥5. Maternal age was classified into three categories: <25 years old (referent), 25 to 29 years old, and ≥30 years old. Gestational age was also analyzed in two ways: ≤36 weeks versus ≥37 weeks (referent); and ≤32 weeks versus ≥33 weeks (referent). To examine twin status, three classification schemes were employed: twin versus singleton (referent); monozygotic twin (or sister twins if zygosity was not reported) versus singleton (referent); and dizygotic twin (or sister-brother twins if zygosity was not reported) versus singleton (referent). Maternal or paternal smoking was considered as follows: no smoking during pregnancy (referent) versus smoking during pregnancy. If the criteria utilized in an article were slightly different from our criteria, then we included the data and described the difference in a footnote.

ORs and 95% confidence intervals (CIs) were recalculated from published frequency tables of individual studies using the Mantel-Haenszel common OR estimate. However, the reported OR (95% CI) was used when the published studies did not provide further details as to the frequencies of the exposure variables. If the manuscript reported the results after performing a stratified analysis, then we re-calculated the crude OR by combining across strata. A random-effects model was used to obtain summary ORs and 95% CIs.

Heterogeneity was assessed by heterogeneity test using Cochran Q statistics 8. Publication bias was assessed according to the Egger regression asymmetry test, and the Begg and Mazumdar adjusted rank correlation tests 910. The Egger test is a simple linear regression of the natural log of ORs or RRs against its precision (the inverse of its standard error) 10. The Begg and Mazumdar rank correlation test reports the rank correlation (Kendall's tau) between the standardized effect size and the standard errors of these effects. If asymmetry is caused by publication bias, then we would expect that high standard errors (small studies) would be associated with larger effect sizes (ORs or RRs) or low standard errors (large studies) would be associated with smaller effect sizes 9. The Begg and Mazumdar test makes fewer assumptions than does the Egger test, but it is insensitive to many types of bias (lower power) that the Egger test is sensitive to 11.

When significant heterogeneity or publication bias was found, we performed subgroup analyses by study design (case-control study versus cohort study), and the source of information (data linkage versus self-report) to assess the impact on between-study variations (heterogeneity). Many of the large-scale studies, especially cohort studies, were published after 2000; thus, we classified publication years into before 2000 versus 2000 or later in order to assess publication biases associated with small study sizes. Few studies focused on either Asians or African-Americans, and so it was not possible to examine ethnicity effects. All statistical analyses were conducted using STATA (Version 8.2 [special edition]; Stata Corp., College Station, TX, USA).

Results

We identified 34 studies that assessed the association between birth weight and breast cancer risk (Table 2): 19 case-control studies (eight population based, three nested, six record linkage based, and two twin-based) and 15 cohort studies (seven population based and eight record linkage based). Many studies showed positive association between heavier birth weight and breast cancer risk 1213141516171819202122232425262728293031, and some of the studies observed stronger effects among younger (<45 years) or premenopausal women 14222930. In contrast, studies observing no association 32333435363738394041 or a negative one 42434445 also have been reported. Additionally, some authors reported a J-shaped relationship between birth weight and breast cancer risk 121415182533353745, particularly for early-onset cancers 18.

Table 2

Studies assessing the association of birth weight and the risk for breast cancer

Type of study

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Birthweight (g)

OR (95% CI)

Comments

Case-control studies

[42]

1988

PCC

153

461

USA

1,162–2,948

Referent

Matched analysis; P for trend = 0.41

2,949–3,340

0.65 (0.33–1.26)

3,341–4,451

0.76 (0.41–1.43)

[12]^a

1992

LCC

458

1,197

Sweden

<2,500

1.18 (0.60–2.33)

Adjusted for age and birth date

2,500–2,999

Referent

3,000–3,499

1.29 (0.90–1.91)

3,500–3,999

1.47 (1.00–2.18)

≥ 4,000

1.23 (0.80–2.00)

[13]

1996

NCC

550

1,478

USA

<2,500

0.56 (0.34–0.93)

Adjusted for age

2,500–2,999

0.68 (0.47–0.99)

3,000–3,499

0.71 (0.50–0.99)

3,500–3,999

0.85 (0.59–1.22)

≥ 4,000

Referent

[14]

1996

PCC

922

1,194

USA

Age 21–45 years:

Adjusted for age, menopausal status, and maternal smoking; P for trend = 0.06 among both groups. The OR (95% CI) for birth weight ≥ 4,000 g among patients with early-onset breast cancer (≤ 30 years old) was 3.3 (1.0–11.0)

<2,500

1.3 (0.9–2.0)

2,500–2,999

Referent

3,000–3,499

1.3 (1.0–1.7)

3,500–3,999

1.2 (0.8–1.6)

≥ 4,000

1.7 (1.1–2.5)

Age 50–64 years:

<2,500

0.9 (0.5–1.7)

2,500–2,999

Referent

3,000–3,499

1.1 (0.7–1.7)

3,500–3,999

0.8 (0.4–1.3)

≥ 4,000

0.6 (0.3–1.1)

[32]

1997

NCC

1068

2,027

Sweden

<2,500

0.80 (0.50–1.26)

Adjusted for maternal age, socioeconomic status, parity, and pre-eclampsia or eclampsia, neonatal jaundice, severe prematurity, and twinship

2,500–2,999

Referent

3,000–3,499

1.00 (0.79–1.28)

3,500–3,999

0.99 (0.77–1.26)

≥ 4,000

1.04 (0.77–1.41)

[33]

1998

PCC

510

436

USA

<2,500

1.2 (0.7–2.1)

Crude ORs

2,500–2,999

Referent

3,000–3,499

1.0 (0.7–1.5)

3,500–3,999

1.0 (0.7–1.5)

≥ 4,000

1.3 (0.7–2.3)

[15]

2000

LCC

484

2,870

USA

<1,500

1.59 (0.61–4.11)

Crude ORs

1,500–2,499

1.33 (0.94–1.90)

2,500–3,499

Referent

3,500–4,499

1.08 (0.87–1.34)

≥ 4,500

3.29 (1.37–7.92)

[34]

2001

LTCC

Sweden

<1,999

Referent

Matched analysis by conditional logistic regression

2,000–2,499

1.6 (0.6–4.0)

2,599–2,999

2.4 (0.9–6.2)

≥ 3,000

1.6 (0.4–5.6)

(P trend = 0.05)

[43]

2001

LCC

319

768

USA

<2,500

1.4 (0.55–3.4)

Crude ORs. Higher birth weight (≥ 3,500 g) carried a marginal significantly higher risk for breast cancer (OR 1.76 [95% CI 0.90–3.35]) relative to lower birth weight (<3,500 g)

2,500–3,750

Referent

≥ 3,750

0.9 (0.50–1.6)

[16]

2001

LTCC

Sweden

≤ 2,000

Referent

Crude ORs. Study subjects were women with opposite-sexed pair twins

2,001–2,500

3.2 (0.8–12.6)

2,501–3,000

3.5 (1–13)

3,001–3,500

5.8 (1.3–25.7)

≥ 3,501

12.1 (1.1–138.8)

[35]

2002

PCC

2,088

2,187

USA

<2,500

1.10 (0.90–1.35)

Adjusted for age and residential regions (states)

2,500–2,999

0.90 (0.70–1.10)

3,000–3,499

Referent

3,500–3,999

1.07 (0.90–1.30)

4,000–4,499

0.89 (0.70–1.14)

≥ 4,500

1.18 (0.90–1.51)

[44]

2002

PCC

288

350

China

<2,500

0.9 (0.4–2.0)

Adjusted for age income, family history of breast cancer in first-degree relative, history of fibroadenoma, age at menarche, parity, and age at first live birth.

2,500–2,999

Referent

3,000–3,499

1.1 (0.8–1.6)

3,500–3,999

0.8 (0.4–1.4)

≥ 4,000

0.7 (0.4–1.4)

[17]

2002

LCC

373

1,150

USA

<3,090

Referent

Adjusted for parity and age at first birth. P for trend = 0.02

3,090–3,410

1.1 (0.8–1.5)

3,420–3,720

1.2 (0.9–1.6)

≥ 3,630

1.4 (1.1–1.9)

[18]

2003

LCC

881

3,423

Denmark

<2,500

1.66 (1.00–2.51)

Adjusted for mother's marital status, maternal age, and birth order

2,500–2,999

0.83 (0.60–1.10)

3,000–3,499

Referent

3,500–3,999

0.98 (0.80–1.17)

≥ 4,000

1.25 (1.00–1.55)

[19]

2004

NCC

238

Sweden

100 g increase

1.06 (1.00–1.12)

Adjusted for gestational age, birth year, and maternal hypertension/proteinuria

[45]

2004

LCC

2471

9801

USA

<1,500

0.64 (0.40–1.11)

Adjusted for age and maternal age at first birth

1,500–1,999

1.05 (0.70–1.68)

2,000–2,499

1.02 (0.80–1.31)

2,500–3,499

Referent

3,500–3,999

0.97 (0.90–1.08)

4,000–4,499

0.93 (0.80–1.11)

≥ 4,500

0.69 (0.40–1.09)

[36]

2004

PCC

196

167

USA

All subjects:

Adjusted for age, race and sampling fractions, body mass index, household income, and maternal age. Tertiles are race specific with cutpoints derived from controls. White women: <3,062, 3,062–3,458, >3,458 g; black women: <3,146, 3,146–3,488, >3,488 g. Restricted data using birth weight measured in pounds and ounces and participant delivered in a medical facility by a physician

Lower tertile

1.0 (0.6–1.7)

Central tertile

Referent

Upper tertile

0.7 (0.4–1.2)

White, restricted

data:

Lower tertile

1.1 (0.5–2.4)

Central tertile

Referent

Upper tertile

1.4 (0.6–2.0)

[20]

2006

PCC

2,386

2,502

Poland

<2,500

Referent

Adjusted for: age, education, age at menarche, menopausal status and age at menopause, age at first full-term pregnancy, number of full-term pregnancies, family history of breast cancer among first-degree relatives, mammography screening, and current body mass index. Lower birth weight (<2,500 g) carries greater risk than birth weight of 2,500–4,000 g among women under 45 years old

2,500–4,000

1.22 (0.92–1.62)

>4,000

1.54 (1.08–2.19)

(p-trend = 0.01)

[37]

2006

PCC

1,166

2,105

USA

<2,495

1.19 (0.85–1.66)

Adjusted for age (years), education (years), race, body mass index, history of breast benign disease, family history of breast cancer, lactation (months), age at menarche (years), age at first full-term pregnancy (years), age at menopause (years), parity

2,495–3,130

Referent

3,131–3,855

0.97 (0.75–1.25)

>3,855

1.03 (0.74–1.44)

Cohort studies

[21]

1999

LCohort

152,590

Sweden

<2,500

Referent

Standardization for sex, age, and age-specific incidence rate

2,500–3,999

1.3 (0.6–2.4)

4,000–4,499

1.2 (0.0–6.7)

≥ 4,500

1.3 (0.7–2.3)

[22]

2000

Cohort

2,221

All ages

Adjusted for age. P for trend = 0.03 among premenopausal women

<3,000

Referent

3,000–3,499

1.05 (0.41–2.71)

3,500–3,999

1.76 (0.72–4.33)

≥ 4,000

2.02 (0.59–6.90)

Premenopausal ages

<3,000

Referent

3,000–3,499

1.99 (0.40–9.86)

3,500–3,999

3.26 (0.69–15.36)

≥ 4,000

5.65 (0.95–33.84)

[38]

2001

LCohort

177

3,447

Sweden

≤ 2,000

Referent

Crude hazard ratios

2,001–2,500

1.4 (0.6–3.4)

2,501–3,000

1.9 (0.8–4.3)

3,001–3,500

1.5 (0.6–3.5)

≥ 3,501

1.9 (0.7–5.0)

[39]

2001

Cohort

1260

Sweden

≤ 3,000

Referent

Singleton only; adjusted for gestational age and cohort membership

3,010–3,349

1.16 (0.47–2.87)

3,350–3,590

1.65 (0.71–3.86)

3,600–3,960

1.58 (0.67–3.72)

≥ 4,000

1.57 (0.67–3.64)

[23]

2003

LCohort

5,352

Sweden

<3,000

Referent

Crude ORs;P for trend = 0.01