A Workflow for Evaluating Regional Treatment Effect Heterogeneity in Multi-Regional Clinical Trials

2026-05-16

AI Summary

Exploratory analyses of regional treatment effect heterogeneity in multi-regional clinical trials often lack a systematic framework, are susceptible to sampling variability, and thus struggle to support reliable interpretation or regulatory decision-making. This work proposes a problem-oriented, structured evaluation framework that aligns specific analytical objectives with tailored statistical methods through four key scientific questions, establishing the first comprehensive approach dedicated to assessing regional heterogeneity. The validity of this framework is demonstrated via simulation studies encompassing diverse scenarios—including absence of heterogeneity and heterogeneity driven by either observed or unobserved effect modifiers—showing enhanced transparency, interpretive caution, and analytical robustness. This approach provides a reliable tool for conducting exploratory analyses of regional differences in treatment effects.

Abstract

Multi-regional clinical trials (MRCTs) enable efficient global drug development by assessing treatment effects across regions within a single protocol. While powered for overall efficacy, MRCTs are typically not designed to provide confirmatory evidence on regional differences, making an assessment of observed regional heterogeneity largely exploratory and susceptible to sampling variability. Despite this challenge, understanding regional heterogeneity remains important for interpretation and regulatory decision-making. This paper proposes a structured, question-driven framework to guide exploratory assessments of regional heterogeneity in MRCTs. We formulate four key questions to clarify the objectives of such analyses and propose a set of statistical methods to address them. Simulation studies evaluate performance under scenarios with no heterogeneity and heterogeneity driven by observed or unobserved treatment effect modifiers, illustrating how a structured approach can support transparent and cautious interpretation.

Problem

• regional heterogeneity
• multi-regional clinical trials
• treatment effect
• exploratory analysis
• regulatory decision-making

Innovation

• regional heterogeneity
• multi-regional clinical trials
• treatment effect modifiers
• exploratory analysis
• structured framework