The application of sequential analysis for continuous post-market vaccine safety surveillance

VernacularTitle:序贯分析在疫苗上市后安全性动态监测中的应用
Author: Zixuan LU ¹ ; Musu LI ; Jiahe PAN ; Yiwen WU ; Huilin LI ; Er YU ; Hongmei WO ; Shaowen TANG ; Yang ZHAO ; Juncheng DAI ; Honggang YI
Author Information

1. 南京医科大学公共卫生学院生物统计学系，南京　211166
Publication Type:Journal Article
Keywords: Safety surveillance; Adverse events; Bayesian sequential analysis; Pharmacovigilance
From: Chinese Journal of Epidemiology 2025;46(3):514-518
CountryChina
Language:Chinese
Abstract: To explore the application of sequential analysis in post-market safety dynamic surveillance of vaccines. Under the dynamic monitoring data of vaccines post-market approval, this research introduces the fundamental principles of maximizing sequential probability ratio test (MaxSPRT) and Bayesian sequential analysis, employing R software. Through an example of dynamic safety monitoring data of vaccines post-market approval, we analyze using the MaxSPRT and Bayesian sequential analysis. The MaxSPRT identified a safety signal in week 4 ( P<0.05), while Bayesian sequential analysis indicated that the 95% highest density interval for the RR value at week 4 is 1.13-3.27, suggesting the first appearance of a safety signal at week 4. The MaxSPRT and Bayesian sequential analysis effectively leverage continuously accumulating dynamic monitoring data, thereby serving as a valuable method for post-market safety surveillance of vaccines.