Use of Random Effect Models in the Design and Analysis of Multi-regional Clinical Trials

Abstract

AbstractIn recent years, global collaboration has become a commonly used strategy for new drug development. To accelerate the development process and shorten the approval time, the design of multi-regional clinical trials (MRCTs) incorporates subjects from many countries around the world under the same protocol. After showing the overall efficacy of a drug in all global regions, one can also simultaneously evaluate the possibility of applying the overall trial results to all regions and subsequently support drug registration in each of them. Several statistical methods have been proposed for the design and evaluation of MRCTs. Most of these approaches, however, assume a common variability of the primary endpoint across regions. In practice, this assumption may not be true due to differences across regions. In this paper, we use a random effect model for modeling heterogeneous variability across regions for the design and evaluation of MRCTs.KeywordsRandom Effect ModelTotal Sample SizeExpected MaximumExpected Maximum AlgorithmSample Size DeterminationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.