Evaluating the agreement between sensitivity and primary analyses in observational studies using routinely collected healthcare data: a meta-epidemiology study

作者：Jiayue Xu, Yuning Wang, Qiao He, Shuangyi Xie, Sheng Feng, Wang Xiaofei, Wen Wang, Xin Sun · 发表于：BMC Medicine · 年份：2025 · DOI：10.1186/s12916-025-04199-4 · 被引用次数：10 · 研究领域：Meta-analysis and systematic reviews、Advanced Causal Inference Techniques、Pharmacovigilance and Adverse Drug Reactions

BACKGROUND: Sensitivity analysis is a crucial approach to assessing the "robustness" of research findings. Previous reviews have revealed significant concerns regarding the misuse and misinterpretation of sensitivity analyses in observational studies using routinely collected healthcare data (RCD). However, little is known regarding how sensitivity analyses are conducted in real-world observational studies, and to what extent their results and interpretations differ from primary analyses. METHODS: We searched PubMed for observational studies assessing drug treatment effects published between January 2018 and December 2020 in core clinical journals defined by the National Library of Medicine. Information on sensitivity analyses was extracted using standardized, pilot-tested collection forms. We characterized the sensitivity analyses conducted and compared the treatment effects estimated by primary and sensitivity analyses. The association between study characteristics and the agreement of primary and sensitivity analysis results were explored using multivariable logistic regression. RESULTS: Of the 256 included studies, 152 (59.4%) conducted sensitivity analyses, with a median number of three (IQR: two to six), and 131 (51.2%) reported the results clearly. Of these 131 studies, 71 (54.2%) showed significant differences between the primary and sensitivity analyses, with an average difference in effect size of 24% (95% CI 12% to 35%). Across the 71 studies, 145 sensitivity analy...