Clinical breast cancer subtypes are categorized basing on the expression of hormone receptors and overexpression of the human epidermal growth factor receptor 2 (HER2). It is still unclear whether parity impact the risk of different breast cancer subtypes.
We searched eight mainstream databases for published epidemiologic studies that assessed the relationship between parity and risk of breast cancer subtypes up to January 12, 2021. Parity number were unified into nulliparity and ever parity. The random-effects or fixed-effect models were used to calculate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) among different subtypes. Restricted cubic spline analysis with four knots was applied to determine the relationship of parity number and risk of breast cancer subtypes.
We pooled sixteen case-control and four cohort studies, and performed an analysis including 7795 luminal A, 3576 luminal B, 1794 HER2-overexpressing, and 5192 triple-negative breast cancer cases among 1135131 participants. The combined ORs for ever parity versus nulliparity indicated a 34% reduction in luminal A risk (OR=0.66, 95% CI: 0.56–0.78), and a 29% reduction in luminal B risk (OR=0.71, 95% CI: 0.63–0.81), there was no significant association in HER2-overexpressing or TNBC risk. In the dose-response analysis, we observed a potentially non-linear and gradually increasing protective relationship between the number of parity and luminal breast cancer risk.
The effect of parity on breast cancer seems to vary among breast tumor subtypes, and it plays a protective role in luminal breast cancer.
- • 16 case-control and 4 cohort studies involving 18357 patients were included to assess parity and breast cancer subtype risk.
- • Ever parity plays a protective role in luminal A and B breast cancer, but the other subtypes were not found.
- • A potentially non-linear and protective relationship was observed between parity number and luminal breast cancer risk.
Breast cancer is the most common cancer among women all over the world. By 2020, breast cancer has surpassed lung cancer and became the most common cancer, with about 2.3 million new cases, accounting for 11.7% of all cancers, and the fifth leading cause of cancer mortality in the world . Breast cancer is a heterogeneity disease , and luminal A, luminal B, HER2-overexpressing, triple-negative subtypes are the most common classifications based on molecular characteristics . These subtypes differ in their biology, etiology, prognosis, and treatments.
Previous studies have shown a clear association between the risk of breast cancer and number of live births . However, it is still unclear whether there are differences between parity and different breast cancer subtypes. On one hand, several epidemiological studies have different ways of grouping parity number, which may contribute to opposite results among different breast cancer subtypes . On the other hand, different results may attribute to the lack of HER2 or TNBC cases, which only account for 30% of all breast cancers . Meta-analyses may be a way to overcome the limitation of statistical power in individual studies. Furthermore, the most recent meta-analysis of 14 observational studies had a high heterogeneity and unadjusted combined effect values, and also did not include a dose-response analysis to evaluate linear or non-linear associations. Therefore, a more precise and systematic research should be conducted to demonstrate the relationship between parity and risk of breast cancer subtypes.
Hence, we conduct this systematic review and meta-analysis to quantitatively evaluate the relationship between parity and the risk for developing luminal A, luminal B, HER2 and triple-negative breast cancer.