Statistical design of noninferiority multiple region clinical trials to assess global and consistent treatment effects.

TitleStatistical design of noninferiority multiple region clinical trials to assess global and consistent treatment effects.
Publication TypeJournal Article
Year of Publication2017
AuthorsDiao, Guoqing, Donglin Zeng, Joseph G. Ibrahim, Alan Rong, Oliver Lee, Kathy Zhang, and Qingxia Chen
JournalJ Biopharm Stat
Volume27
Issue6
Pagination933-944
Date Published2017
ISSN1520-5711
KeywordsDrug Approval, Global Health, Humans, Models, Statistical, Multicenter Studies as Topic, Randomized Controlled Trials as Topic, Sample Size, Treatment Outcome
Abstract

Noninferiority multiregional clinical trials (MRCTs) have recently received increasing attention in drug development. While a major goal in an MRCT is to estimate the global treatment effect, it is also important to assess the consistency of treatment effects across multiple regions. In this paper, we propose an intuitive definition of consistency of noninferior treatment effects across regions under the random-effects modeling framework. Specifically, we quantify the consistency of treatment effects by the percentage of regions that meet a predefined treatment margin. This new approach enables us to achieve both goals in one modeling framework. We propose to use a signed likelihood ratio test for testing the global treatment effect and the consistency of noninferior treatment effects. In addition, we provide guidelines for the allocation rule to achieve optimal power for testing consistency among multiple regions. Extensive simulation studies are conducted to examine the performance of the proposed methodology. An application to a real data example is provided.

DOI10.1080/10543406.2017.1293075
Alternate JournalJ Biopharm Stat
Original PublicationStatistical design of noninferiority multiple region clinical trials to assess global and consistent treatment effects.
PubMed ID28296570
PubMed Central IDPMC5787861
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 GM070335 / GM / NIGMS NIH HHS / United States