Ovarian cancer risk in relation to blood lipid levels and hyperlipidemia: a systematic review and meta-analysis of observational epidemiologic studies

Epidemiologic evidence regarding association of ovarian cancer risk with blood lipid level and hyperlipidemia is inconsistent. We aimed to synthesize available epidemiologic studies to disentangle associations of cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and hyperlipidemia with ovarian cancer risk. We searched PubMed, EMBASE, and Web of Science for eligible studies. A random-effects model was applied for synthesis. Heterogeneity was evaluated by a Chi-squared test for the Cochran Q statistic and the I-squared value. Subgroup analysis was conducted by design, study locale, and ovarian cancer case number. Sensitivity analysis was conducted for studies adjusting for certain covariates or with superior quality. To explore the potential dose-response relationship, we further synthesized effect measures of moderate levels of cholesterol, triglycerides, HDL-C, and LDL-C. Twelve studies (five cohort and seven case-control studies) were included. In primary meta-analysis, the synthesized risk ratio (RRpool) and 95% confidence interval (CI) suggested that high cholesterol was associated with an increased ovarian cancer risk (RRpool 1.22, 95% CI 1.01-1.48, Cochran P value: 0.40, I: 0.5%). High HDL-C was associated with a lower ovarian cancer risk (RRpool 0.61, 95% CI 0.40-0.94, Cochran P value: 0.06, I: 63.7%). We obtained nonsignificant associations for other exposures. Subgroup and sensitivity analyses yielded consistent results as the primary analysis. Only cholesterol showed marginally significant association in synthesis using moderate exposure levels (RRpool 1.18, 95% CI 0.99-1.42, Cochran P value: 0.51, I: 0.0%). Our study suggests that high blood cholesterol is associated with an increased ovarian cancer risk, whereas the etiological significance of other exposures deserves more investigations.