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. 2018 Oct 15;78(20):6011-6021.
doi: 10.1158/0008-5472.CAN-18-0502. Epub 2018 Sep 5.

Pooled Analysis of Nine Cohorts Reveals Breast Cancer Risk Factors by Tumor Molecular Subtype

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Pooled Analysis of Nine Cohorts Reveals Breast Cancer Risk Factors by Tumor Molecular Subtype

Mia M Gaudet et al. Cancer Res. .

Abstract

Various subtypes of breast cancer defined by estrogen receptor (ER), progesterone receptor (PR), and HER2 exhibit etiologic differences in reproductive factors, but associations with other risk factors are inconsistent. To clarify etiologic heterogeneity, we pooled data from nine cohort studies. Multivariable, joint Cox proportional hazards regression models were used to estimate HRs and 95% confidence intervals (CI) for molecular subtypes. Of 606,025 women, 11,741 invasive breast cancers with complete tissue markers developed during follow-up: 8,700 luminal A-like (ER+ or PR+/HER2-), 1,368 luminal B-like (ER+ or PR+/HER2+), 521 HER2-enriched (ER-/PR-/HER2+), and 1,152 triple-negative (ER-/PR-/HER2-) disease. Ever parous compared with never was associated with lower risk of luminal A-like (HR, 0.78; 95% CI, 0.73-0.83) and luminal B-like (HR, 0.74; 95% CI, 0.64-0.87) as well as a higher risk of triple-negative disease (HR, 1.23; 95% CI, 1.02-1.50; P value for overall tumor heterogeneity < 0.001). Direct associations with luminal-like, but not HER2-enriched or triple-negative, tumors were found for age at first birth, years between menarche and first birth, and age at menopause (P value for overall tumor heterogeneity < 0.001). Age-specific associations with baseline body mass index differed for risk of luminal A-like and triple-negative breast cancer (P value for tumor heterogeneity = 0.02). These results provide the strongest evidence for etiologic heterogeneity of breast cancer to date from prospective studies.Significance: These findings comprise the largest study of prospective data to date and contribute to the accumulating evidence that etiological heterogeneity exists in breast carcinogenesis. Cancer Res; 78(20); 6011-21. ©2018 AACR.

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Conflict of interest statement

Conflicts of interest: The authors declare no potential conflicts of interest.

Figures

Figure 1.
Figure 1.
Exclusion cascade resulting in an analytical dataset of 606,025 participants of which 11,741 were breast cancer cases in a pooled analysis of nine prospective cohort studies

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