OVARIAN CANCER PREVENTION: ADVANCES IN RISK ASSESSMENT AND RISK REDUCTION

Abstract

Ovarian cancer remains a significant global health challenge, accounting for high mortality rates due to its typically late diagnosis and limited preventive strategies. This paper explores recent advances in ovarian cancer prevention by focusing on two critical areas: risk assessment and risk reduction. Genetic predispositions, such as BRCA1/BRCA2 mutations and hereditary syndromes, are examined alongside modifiable risk factors including obesity, hormonal exposure, and reproductive history. The integration of emerging technologies—such as polygenic risk scoring, artificial intelligence (AI), and molecular biomarker analysis—is transforming early detection and individualized prevention strategies. Open-source datasets and recent epidemiological trends are utilized to support data-driven insights into survival rates and population-specific risk modeling. Moreover, the paper evaluates current screening methods, risk-reducing surgeries, chemoprevention, and lifestyle interventions. By emphasizing a multidisciplinary and precision-medicine approach, this study contributes to the evolving paradigm of ovarian cancer prevention, aiming to reduce incidence and improve long-term outcomes in high-risk populations