Abstract
Precision prevention strategies for cervical cancer that integrate genetic biomarkers provide opportunities for personalized risk assessment and optimized preventive measures. An HPV infection-Precancerous-Cancer risk assessment model incorporating genetic polymorphisms and DNA methylation was developed to better understand the regression and progression of cervical lesions by HPV infection status. Utilizing a virtual cohort of 300,000 Taiwanese women aged 30 years and older, our model simulated the natural history of cervical cancer, capturing transitions from a healthy state through precancerous lesions (LSILs and HSILs) to invasive carcinoma and incorporating the possibility of regression between states. Genetic and epigenetic markers significantly influenced disease transitions, demonstrating heterogeneous risks among women with distinct molecular biomarker profiles. Guided by these individual risk profiles, tailored preventive strategies including varying intervals for Pap smear screening, HPV DNA testing, and HPV vaccination showed improved efficiency and effectiveness in reducing cervical cancer incidence compared to uniform approaches. The proposed dynamic transition model of cervical neoplasms incorporating genetic biomarkers can facilitate the development of an individualized risk-based approach for guiding precision prevention towards the goal of cervical cancer elimination.