Regional Efficacy Evaluation in Multi-Regional Clinical Trials Using a Discounting Factor Weighted Z Test

• Activity Number: 77 - Contributed Poster Presentations: Biopharmaceutical Section
• Type: Contributed
• Date/Time: Monday, August 3, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Jingwei Wu and XUANXUAN YU* and Jianling Bai and Hao Yu
• Companies: College pf Public Health, Temple University and Dept of Epidemiology & Biostatistics, School of Public Health, University of South Carolina and School of Public Health, Nanjing Medical University and School of Public Health, Nanjing Medical University
• Keywords: multi-regional clinical trial; ethnic difference; Kolmogorov-Smirnov statistic; discounting factor; weighted Z test

Abstract

One primary objective of a multi-regional clinical trial (MRCT) is to extrapolate the overall treatment result to the specific region given that the global efficacy of test drug is demonstrated in all regions. It is not only required each local regulatory agency to prove the effectiveness of test drug in local region before drug registration, but also recommended to utilize information from all other regions to evaluate specific regional treatment effect. However, it remains a challenge to determine what proportion of information we should use given the non-negligible ethnic differences among multiple regions. In this research, we propose a weighted Z test based on discounting factor as an index of how much external information we can use to evaluate regional treatment effect. Specifically, we use Kolmogorov-Smirnov (KS) statistic to measure the ethnic difference among local region and other regions, while deriving tuning parameters that link KS statistic to discounting factor by simulation. We perform simulation studies on both continuous and binary endpoints to examine the performance of proposed method, and showed that proposed efficacy test yield reasonable performance.