MOnitoring human papillomavirus Vaccine effect on Infection and cErvical diseases (MOVIE): Protocol for a cohort study using electronic health records from Yinzhou, China

作者：Siwei Deng, Sarah Welby, Zhike Liu, Yu Yang, Ruogu Meng, Yixin Sun, Junting Yang, Guangxu Liu, Yunkun He, Ning Jiang, Zhenhua Wu, Keruo Liu, Dominique Rosillon, Catherine Cohet, Dorota Borys, Siyan Zhan · 发表于：Human Vaccines & Immunotherapeutics · 年份：2023 · DOI：10.1080/21645515.2023.2257989 · 被引用次数：6 · 研究领域：Cervical Cancer and HPV Research、Reproductive tract infections research、Hepatitis B Virus Studies

Cervical cancer is the fourth most common cancer in women, with a high disease burden worldwide. Human papillomavirus (HPV) vaccination reduces HPV-related infection and associated cervical lesions and cancers. Few studies have explored HPV vaccination impact in real-world settings in China. This study aims to monitor HPV vaccine uptake and its effects on HPV-related diseases, evaluating vaccine effectiveness in a real-world context and complementing clinical trial results. Electronic health records (EHRs) from 2010 to 2020 from the Yinzhou Regional Health Information Platform (YRHIP) will be queried/extracted to identify and monitor HPV vaccine uptake in females aged 9-45 years, and HPV-related screening and prevalence (i.e., cervical HPV infection, cervical intraepithelial neoplasia [CIN] grades 1-3, and cervical cancer) in a cohort of females aged 9-70 years. Cervical cancer screening guidelines and expert consultation will be used for intra-database validation, to determine the best algorithm for identifying HPV-related disease. Pre-launch (2010-2016) and post-launch (2018-2020) periods are predefined. A time trend analysis will be performed to describe the vaccination impact on disease prevalence and, if prerequisite conditions are met, vaccine effectiveness will be computed using logistic regression, adjusting for age, calendar year, history of screening and HPV infection. Cohort study design, outcomes validation, data linkage, and multi-step statistical analyses could ...