OBJECTIVES: External control arms are emerging as one of the applications of real-world data (RWD) in clinical development. ECAs utilize historical or contemporaneous data as comparators when traditional randomized controlled arms are unfeasible. However, the acceptable statistical methods dictated by regulatory guidelines are always not clear. This study aims to examine the evolving ECA regulatory landscape in the EU and US, evaluate existing statistical methodologies, and propose advancements to enhance precision and rigor in estimating treatment effects using ECA data.

METHODS: A comprehensive literature review was conducted to examine EU and US regulatory guidelines on ECA utilization. Statistical methodologies were critically reviewed with a focus on bias mitigation, assumption validation, and advancements in comparative effectiveness research. The study assessed propensity score matching techniques, Bayesian methods, targeted maximum likelihood estimators, and sensitivity analyses for robustness testing.

RESULTS: The synopsis of current guidelines underscores a progressive acceptance of ECAs in regulatory submissions. Propensity score matching facilitates adjustment for covariate imbalances, Bayesian methods enable integration of prior knowledge, and sensitivity analyses assess the impact of assumptions on study outcomes. These methodologies collectively enhance the reliability and validity of treatment effect estimates derived from ECA data. Newer methods for addressing causal inference such as targeted maximum likelihood estimation are positioned to reduce bias and enhance precision.

CONCLUSIONS: Future research should prioritize refining statistical methodologies to further strengthen the credibility of ECA-derived evidence in clinical research and regulatory decision-making. Collaborative efforts among regulatory bodies, researchers, and industry stakeholders are crucial for establishing standardized guidelines and best practices for ECAs. This will expedite drug development processes, particularly in challenging disease areas where conventional trial designs pose ethical or practical constraints. Emphasizing transparency in methodological choices and robust validation of assumptions will be pivotal in leveraging the full potential of ECAs to advance clinical research.