Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium.

Abstract

Background: Polycystic ovary syndrome (PCOS), and one of its distinguishing characteristics, oligomenorrhea, have both been associated with ovarian cancer risk in some but not all studies. However, these associations have been rarely examined by ovarian cancer histotypes, which may explain the lack of clear associations reported in previous studies.Methods: We analyzed data from 14 case-control studies including 16,594 women with invasive ovarian cancer (n = 13,719) or borderline ovarian disease (n = 2,875) and 17,718 controls. Adjusted study-specific ORs were calculated using logistic regression and combined using random-effects meta-analysis. Pooled histotype-specific ORs were calculated using polytomous logistic regression.Results: Women reporting menstrual cycle length >35 days had decreased risk of invasive ovarian cancer compared with women reporting cycle length ≤35 days [OR = 0.70; 95% confidence interval (CI) = 0.58-0.84]. Decreased risk of invasive ovarian cancer was also observed among women who reported irregular menstrual cycles compared with women with regular cycles (OR = 0.83; 95% CI = 0.76-0.89). No significant association was observed between self-reported PCOS and invasive ovarian cancer risk (OR = 0.87; 95% CI = 0.65-1.15). There was a decreased risk of all individual invasive histotypes for women with menstrual cycle length >35 days, but no association with serous borderline tumors (Pheterogeneity = 0.006). Similarly, we observed decreased risks of most invasive histotypes among women with irregular cycles, but an increased risk of borderline serous and mucinous tumors (Pheterogeneity < 0.0001).Conclusions: Our results suggest that menstrual cycle characteristics influence ovarian cancer risk differentially based on histotype.Impact: These results highlight the importance of examining ovarian cancer risk factors associations by histologic subtype. Cancer Epidemiol Biomarkers Prev; 27(2); 174-82. ©2017 AACR.