Hypertension as a Predictor of Ovarian Cancer Risk: A Systematic Review and Meta‐Analysis

ABSTRACT Background and Aims Ovarian cancer is a primary contributor to cancer‐related deaths among women and holds a position among the most common gynecological malignancies worldwide. While hypertension has been identified as a potential risk factor for various cancers, its association with ovarian cancer remains inconclusive. This systematic review and meta‐analysis synthesized data from observational studies to provide light on the association between hypertension and the risk of ovarian cancer. Methods This study followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines and secured registration with the PROSPERO under the identifier CRD42025636649. A systematic literature search of PubMed, Embase, and Web of Science was conducted to identify observational studies published through December 10, 2024. Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using a random‐effects model. Heterogeneity was assessed using the I² statistic, and subgroup analyses were conducted based on study design, parity, and body mass index (BMI). Results Out of 2686 articles identified, 11 studies with a total of 2,523,751 participants met the inclusion criteria. There was a risk ratio (RR) of 1.06 (95% CI, 0.96–1.20) for ovarian cancer in patients with hypertension, and considerable heterogeneity was noted (I² = 81%). Within the subgroup analyses, it was noted that parity played a role in reducing ovarian cancer risk (RR, 1.43; 95% CI, 1.05–1.96; p = 0.0025), while obesity (BMI ≥ 25 kg/m²) was associated with an increased risk (RR, 1.12; 95% CI, 1.07–1.18; p < 0.001). No significant associations were found for diabetes, menopausal status, or smoking. Conclusion There is no statistically significant association between high blood pressure and the risk of ovarian cancer, according to this meta‐analysis. To confirm these results, additional research utilizing larger participant groups and robust study designs is essential.