Multi‐regional clinical trial design and consistency assessment of treatment effects

• Published in: Statistics in medicine 2014-06, Vol.33 (13), p.2191-2205
• Main Authors: Quan, Hui, Mao, Xuezhou, Chen, Joshua, Shih, Weichung Joe, Ouyang, Soo Peter, Zhang, Ji, Zhao, Peng‐Liang, Binkowitz, Bruce
• Format: Article
• Language: English
• Subjects: between‐region variability; Clinical trials; Clinical Trials as Topic - methods; Comparative analysis; Data Interpretation, Statistical; Estimating techniques; Medical statistics; Medical treatment; Models, Statistical; Outcome Assessment (Health Care) - statistics & numerical data; random effects model; Research Design; Sample Size; sample size configuration; shrinkage estimator; weighted estimator
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.6108

We can apply both fixed and random effects models to multi‐regional clinical trial (MRCT) design and data analysis. Thoroughly, understanding the features of these models in an MRCT setting will help assessing their applicability to an MRCT. In this paper, we discuss the interpretations of trial results from these models. We also evaluate the impact of the number of regions and the sample size configuration across the regions on the required total sample size for the overall treatment effect assessment. For quantifying treatment effects of individual regions, the empirical shrinkage estimator and the James–Stein type shrinkage estimator associate with smaller variability compared with the regular sample estimator. We conduct computation and simulation to compare the performance of these estimators when they are applied to assess consistency of treatment effects across regions. We use a multinational trial example to illustrate the application of these methods. Copyright © 2014 John Wiley & Sons, Ltd.