Dataset Information

BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis.

ABSTRACT:

Background

The effects of body mass index (BMI) and reproductive factors may vary among breast cancer molecular subtypes, evidence of which is lacking in East Asia.

Methods

From 2002 to 2010, 1256 breast cancer patients and 1416 healthy women were recruited. Anthropometric and reproductive factors were collected from medical charts. Breast cancer subtype was defined by ER, PR, and HER2 status. Polytomous logistic regression was used to evaluate associations between risk factors and breast cancer subtypes, with subgroup analysis by menopausal status. A meta-analysis of relevant published studies in East Asia was also performed.

Results

In our case-control study, late menarche was negatively associated with luminal tumor risk (P_trend = 0.03). Higher BMI was associated with risk of both luminal and triple-negative tumors (P_trend<0.001). Late age at first live birth was associated with a 1.41- to 2.08-fold increased risk of all subtypes, while late menopause increased risk by 2.62-5.56 times. Heterogeneity of these associations was not detected for different menopausal statuses. The meta-analysis revealed a positive dose-response relationship between BMI and risk of both luminal and ER-PR- subtypes (P_trend<0.05). Early menarche and nulliparity increased luminal tumor risk by 1.39 and 1.26 times, respectively. Non-breastfeeding also increased the risk of all subtypes.

Conclusions

For East Asian women, overweight, late menopause, and lack of breastfeeding appear to increase risk of both luminal and ER-PR- tumors. Early menarche and nulliparity mainly impacted luminal tumor risk. These associations were not impacted by menopausal status.

SUBMITTER: Li H

PROVIDER: S-EPMC5376312 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis.

Li Hui H Sun Xuezheng X Miller Erline E Wang Qiong Q Tao Ping P Liu Li L Zhao Ying Y Wang Mengjie M Qi Yana Y Li Jiayuan J

Journal of epidemiology 20161209 4

<h4>Background</h4>The effects of body mass index (BMI) and reproductive factors may vary among breast cancer molecular subtypes, evidence of which is lacking in East Asia.<h4>Methods</h4>From 2002 to 2010, 1256 breast cancer patients and 1416 healthy women were recruited. Anthropometric and reproductive factors were collected from medical charts. Breast cancer subtype was defined by ER, PR, and HER2 status. Polytomous logistic regression was used to evaluate associations between risk factors an ...[more]

PMID: 28142040

Similar Datasets

Project description:Aside from age, sex, and family history, risk of developing breast cancer is largely linked to reproductive factors, which characterize exposure to sex hormones. Given that, molecular testing at the tumor level is currently possible, clinical characterization of tumor subtypes is routinely conducted to guide treatment decisions. However, despite the vast amount of published data from observational studies on reproductive factor associations and breast cancer risk, relatively fewer reports have been published on associations specific to breast tumor subtypes. We conducted a review of the literature and summarized the results of associations between reproductive factors and risk or odds of three distinct tumor subtypes: estrogen receptor/progesterone receptor positive (hormone receptor positive, HR+ tumors), tumors overexpressing the human epidermal receptor 2 protein (HER2+), and triple negative breast cancer (TNBC), which lacks the three markers. Results show that the most consistent evidence for associations with reproductive risk factors exists for HR+ breast cancers, with nulliparity, current use of menopausal hormone therapy, and prolonged interval between menarche and age at first birth being the strongest risk factors; increased age at first birth and decreased age at menarche were fairly consistently associated with HR+ cancers; and though less consistent, older age at menopause was also positively associated, while lactation was inversely associated with HR+ tumors. Fewer consistent associations have been reported for TNBC. The single protective factor most consistently associated with TNBC was longer duration of breastfeeding. Increased parity, younger age at first birth, older age at menarche, and oral contraceptive use were less consistently shown to be associated with TNBC. No remarkable associations for HER2+ breast cancers were evident, although this was based on relatively scarce data. Findings suggest heterogeneity in reproductive risk factors for the distinct subtypes of breast tumors, which may have implications for recommended prevention strategies.

Project description:BackgroundFew studies have investigated risk factor heterogeneity by molecular subtypes in indigenous African populations where prevalence of traditional breast cancer (BC) risk factors, genetic background, and environmental exposures show marked differences compared to European ancestry populations.MethodsWe conducted a case-only analysis of 838 pathologically confirmed BC cases recruited from 5 groups of public, faith-based, and private institutions across Kenya between March 2012 to May 2015. Centralized pathology review and immunohistochemistry (IHC) for key markers (ER, PR, HER2, EGFR, CK5-6, and Ki67) was performed to define subtypes. Risk factor data was collected at time of diagnosis through a questionnaire. Multivariable polytomous logistic regression models were used to determine associations between BC risk factors and tumor molecular subtypes, adjusted for clinical characteristics and risk factors.ResultsThe median age at menarche and first pregnancy were 14 and 21 years, median number of children was 3, and breastfeeding duration was 62 months per child. Distribution of molecular subtypes for luminal A, luminal B, HER2-enriched, and triple negative (TN) breast cancers was 34.8%, 35.8%, 10.7%, and 18.6%, respectively. After adjusting for covariates, compared to patients with ER-positive tumors, ER-negative patients were more likely to have higher parity (OR = 2.03, 95% CI = (1.11, 3.72), p = 0.021, comparing ≥ 5 to ≤ 2 children). Compared to patients with luminal A tumors, luminal B patients were more likely to have lower parity (OR = 0.45, 95% CI = 0.23, 0.87, p = 0.018, comparing ≥ 5 to ≤ 2 children); HER2-enriched patients were less likely to be obese (OR = 0.36, 95% CI = 0.16, 0.81, p = 0.013) or older age at menopause (OR = 0.38, 95% CI = 0.15, 0.997, p = 0.049). Body mass index (BMI), either overall or by menopausal status, did not vary significantly by ER status. Overall, cumulative or average breastfeeding duration did not vary significantly across subtypes.ConclusionsIn Kenya, we found associations between parity-related risk factors and ER status consistent with observations in European ancestry populations, but differing associations with BMI and breastfeeding. Inclusion of diverse populations in cancer etiology studies is needed to develop population and subtype-specific risk prediction/prevention strategies.

Project description:BackgroundIdentifying breast cancer risk factors is a critical component of preventative strategies for this disease. This study aims to identify modifiable and non-modifiable risk factors of breast cancer in Iranian women.MethodsWe used international databases (PubMed/Medline, Scopus, Web of Knowledge, and Embase) and national databases (SID, Magiran, and ISC) to retrieve relevant studies until November 13, 2022. The odds ratio (OR) with a 95% confidence interval using the random-effect model was used to estimate the pooled effect. The publication bias was assessed by the Egger and Begg test. A sensitivity analysis was conducted to evaluate the effect of each included study on the final measurement.ResultsOf the 30,351 retrieved articles, 24 matched case-control records were included with 12,460 participants (5675 newly diagnosed cases of breast cancer and 6785 control). This meta-analysis showed that of the known modifiable risk factors for breast cancer, obesity (vs normal weight) had the highest risk (OR = 2.17, 95% CI 1.47 to 3.21; I2 = 85.7) followed by age at marriage (25-29 vs < 18 years old) (OR = 2.00, 95% CI 1.53 to 2.61; I2 = 0), second-hand smoking (OR = 1.86, 95% CI 1.58 to 2.19; I2 = 0), smoking (OR = 1.83, 95% CI 1.41 to 2.38; I2 = 18.9), abortion history (OR = 1.44, 95% CI 1.02 to 2.05; I2 = 66.3), oral contraceptive use (OR = 1.35, 95% CI 1.11 to 1.63; I2 = 74.1), age at marriage (18-24 vs < 18 years old) (OR: 1.22, 95% CI 1.02 to 1.47; I2 = 0). Of non-modifiable risk factors, history of radiation exposure (OR = 3.48, 95% CI 2.17 to 5.59; I2 = 0), family history of breast cancer (OR = 2.47, 95% CI 1.83 to 3.33; I2 = 73), and age at menarche (12-13 vs ≥ 14 years old) (OR = 1.67, 95% CI 1.31-2.13; I2 = 25.4) significantly increased the risk of breast cancer.ConclusionsSince most risk factors related to breast cancer incidence are modifiable, promoting healthy lifestyles can play an influential role in preventing breast cancer. In women with younger menarche age, a family history of breast cancer, or a history of radiation exposure, screening at short intervals is recommended.

Project description:BackgroundRecent epidemiological studies suggest that reproductive factors are associated with breast cancer (BC) molecular subtypes. However, these associations have not been thoroughly studied in the African populations. The present study aimed to investigate the prevalence of BC molecular subtypes and assess their association with reproductive factors in Tanzanian BC patients.MethodsThis hospital-based case-only cross-sectional study consisted of 263 histologically confirmed BC patients in Tanzania. Clinico-pathological data, socio-demographic characteristics, anthropometric measurements, and reproductive risk factors were examined using the Chi-square test and one-way ANOVA. The association among reproductive factors and BC molecular subtypes was analyzed using multinomial logistic regression. The heterogeneity of the associations was assessed using the Wald test.ResultsWe found evident subtype heterogeneity for reproductive factors. We observed that post-menopausal status was more prevalent in luminal-A subtype, while compared to luminal-A subtype, luminal-B and HER-2 enriched subtypes were less likely to be found in post-menopausal women (OR: 0.21, 95%CI 0.10-0.41, p = 0.001; OR: 0.39, 95%CI 0.17-0.89, p = 0.026, respectively). Also, the luminal-B subtype was more likely to be diagnosed in patients aged ≤ 40 years than the luminal-A subtype (OR: 2.80, 95%CI 1.46-5.32, p = 0.002). Women who had their first full-term pregnancy at < 30 years were more likely to be of luminal-B (OR: 2.71, 95%CI 1.18-4.17, p = 0.018), and triple-negative (OR: 2.28, 95%CI 1.02-4.07, p = 0.044) subtypes relative to luminal-A subtype. Furthermore, we observed that breastfeeding might have reduced odds of developing luminal-A, luminal-B and triple-negative subtypes. Women who never breastfed were more likely to be diagnosed with luminal-B and triple-negative subtypes when compared to luminal-A subtype (OR: 0.46, 95%CI 0.22-0.95, p = 0.035; OR: 0.41, 95%CI 0.20-0.85, p = 0.017, respectively). .ConclusionOur results are the first data reporting reproductive factors heterogeneity among BC molecular subtypes in Tanzania. Our findings suggest that breast-feeding may reduce the likelihood of developing luminal-A, luminal-B, and triple-negative subtypes. Meanwhile, the first full-term pregnancy after 30 years of age could increase the chance of developing luminal-A subtype, a highly prevalent subtype in Tanzania. More interventions to promote modifiable risk factors across multiple levels may most successfully reduce BC incidence in Africa.

Dataset Information

BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis.

Background

Methods

Results

Conclusions

Publications

BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets