Hormonal Contraception and the Risk of Breast Cancer in Women of Reproductive Age: A Meta-Analysis.

Simple Summary: Breast cancer (BC) is caused by highly invasive and metastatic malignant tumors and affects a large number of women, threatening their health and quality of life. Previous studies have identified mixed evidence on the relationship between the use of hormonal contraceptives (HC) and the development and progression of breast cancer, especially in women of reproductive age. Our results suggest that there is a higher risk of BC in ever-users of HC, but attempting to determine the risk of developing BC among premenopausal women is difficult due to the high heterogeneity observed among the studies, indicating that our results should be approached with caution when translating them into practice. This study aims to summarize evidence from observational studies about the lifetime use of HC and the risk of BC in women of reproductive age. The PubMed, Cochrane, and EMBASE databases were searched for observational studies published from 2015 to February 2022. Meta-analyses were performed using adjusted odds ratios and relative risks with a random-effects model using the I2 statistic to quantify the heterogeneity among studies. Of the 724 studies identified, 650 were screened for title/abstract selection, 60 were selected for full-text revision, and 22 were included in the meta-analysis. Of these, 19 were case-control studies and 3 were cohort studies. The results of the meta-analysis indicate a significantly higher risk of developing BC in ever users of HC (pooled OR = 1.33; 95% CI = 1.19 to 1.49). This effect is larger in the subgroups of case-control studies (pooled OR = 1.44, 95% CI = 1.21 to 1.70) and in the subgroup of studies that strictly define menopausal status (pooled OR = 1.48; 95% CI, 1.10 to 2.00). Although our meta-analysis of observational studies (cohort and case-control) suggests a significantly increased overall risk of BC in users or ever-users of modern hormonal contraceptives, the high heterogeneity among studies (>70%) related to differences in study design, measurement of variables, confounders, among other factors, as well as publication biases should be considered when interpreting our results. [ABSTRACT FROM AUTHOR]