Statistical Methods to Adjust for Treatment Switching in Real-World Clinical Studies: A Scoping Review and Descriptive Comparison.

ABSTRACT: Real-world data from sources, such as patient registries and electronic health records, can complement randomized controlled trials by providing timely, generalizable insights that better reflect routine clinical practice. However, the absence of randomization can introduce bias, particularly when treatment switching-defined as deviation from or discontinuation of the initial treatment-is influenced by time-varying confounders, that is, variables that are associated with both treatment decisions and outcomes over time. This study presents a comprehensive overview of statistical methods used to adjust for treatment switching in real-world studies to improve causal inference. We systematically searched MEDLINE and Embase for studies comparing at least two statistical methods for adjusting fo

SUBMITTER: Collet RJ 

PROVIDER: S-EPMC12598132 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature