Literature DB >> 24515845

Multi-regional clinical trial design and consistency assessment of treatment effects.

Hui Quan1, Xuezhou Mao, Joshua Chen, Weichung Joe Shih, Soo Peter Ouyang, Ji Zhang, Peng-Liang Zhao, Bruce Binkowitz.   

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.
Copyright © 2014 John Wiley & Sons, Ltd.

Keywords:  between-region variability; random effects model; sample size configuration; shrinkage estimator; weighted estimator

Mesh:

Year:  2014        PMID: 24515845     DOI: 10.1002/sim.6108

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  1 in total

1.  Random-effects, fixed-effects and the within-between specification for clustered data in observational health studies: a simulation study.

Authors:  Joseph L Dieleman; Tara Templin
Journal:  PLoS One       Date:  2014-10-24       Impact factor: 3.240

  1 in total

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