Quantitative bias analysis for external control arms using real-world data in clinical trials: a primer for clinical researchers.

ABSTRACT: Development of medicines in rare oncologic patient populations are growing, but well-powered randomized controlled trials are typically extremely challenging or unethical to conduct in such settings. External control arms using real-world data are increasingly used to supplement clinical trial evidence where no or little control arm data exists. The construction of an external control arm should always aim to match the population, treatment settings and outcome measurements of the corresponding treatment arm. Yet, external real-world data is typically fraught with limitations including missing data, measurement error and the potential for unmeasured confounding given a nonrandomized comparison. Quantitative bias analysis (QBA) comprises a collection of approaches for modelling the magnitud

SUBMITTER: Thorlund K 

PROVIDER: S-EPMC10945419 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature