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

高血压作为卵巢癌风险预测因子:系统评价和荟萃分析

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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.

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