title: Multi-regional clinical trial design and consistency assessment of treatment effects.
abstract: 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.
authors: Biostatistics and Programming, Sanofi, Bridgewater, NJ 08807, U.S.A.
authors: Hui
authors: H
authors: Quan
authors: Xuezhou
authors: X
authors: Mao
authors: Joshua
authors: J
authors: Chen
authors: Weichung Joe
authors: WJ
authors: Shih
authors: Soo Peter
authors: SP
authors: Ouyang
authors: Ji
authors: J
authors: Zhang
authors: Peng-Liang
authors: PL
authors: Zhao
authors: Bruce
authors: B
authors: Binkowitz
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D012107:Research Design; D018401:Sample Size
keywords: between-region variability; random effects model; sample size configuration; shrinkage estimator; weighted estimator