The 11th question-and-answer document (Q&A) for ICH E5 (1998) was published in 2006. This Q&A describes points to consider for evaluating the possibility of bridging among regions by a multiregional trial. The primary objective of a multiregional bridging trial is to show the overall efficacy of a drug in all participating regions while also evaluating the possibility of applying the overall trial results to each region. To apply the overall results to a specific region, it suggested that the results in that region should be consistent with the overall results. The Japanese Ministry of Health, Labor, and Welfare (MHLW) published the "Basic Principles on Global Clinical Trials" guidance document (2007) and proposed two methods to support the bridging claims. Due to the limited sample sizes allocated to the region, the regular interaction test for treatment by region is not practical. On the other hand, the sample size requirement for the Japanese region as described in Uyama et al. (2005) and Uesaka (2009) is to satisfy an 80% or greater power for the Japanese region, conditioning on the effect of the overall global trial. Quan et al. (2010) further extended the results to trials with various endpoints. Ko, Tsou, Liu and Hsiao (2010) focused on a specific region and established statistical criteria for consistency between the region of interest and overall results. The proposed method was based on the assumption that true effect size is uniform across regions. In this article, we propose to analyze a completed multiregional trial for any specific regional effect by controlling the type I error rate adjusted for the regional sample size and the planned power of the global trial. Accordingly, in order to attain the approval for a specific region, we propose to determine the sample size requirement for the specific regions using the overall power planned and a regional acceptable type I error rate.
In recent years, global collaboration has become a conventional strategy for new drug development. To accelerate the development process and shorten approval time, the design of multi-regional clinical trials (MRCTs) incorporates subjects from many countries/regions around the world under the same protocol. After showing the overall efficacy of a drug in a global trial, one can also simultaneously evaluate the possibility of applying the overall trial results to all regions and subsequently support drug registration in each region. However, most of the recent approaches developed for the design and evaluation of MRCTs focus on establishing criteria to examine whether the overall results from the MRCT can be applied to a specific region. In this paper, we use the consistency criterion of Method 1 from the Japanese Ministry of Health, Labour and Welfare (MHLW) guidance to assess whether the overall results from the MRCT can be applied to all regions. Sample size determination for the MRCT is also provided to take all the consistency criteria from each individual region into account. Numerical examples are given to illustrate applications of the proposed approach.
In recent years, developing pharmaceutical products via multiregional clinical trials (MRCTs) has become standard. Traditionally, an MRCT would assume that a treatment effect is uniform across regions. However, heterogeneity among regions may have impact upon the evaluation of a medicine's effect. In this study, we consider a random effects model using discrete distribution (DREM) to account for heterogeneous treatment effects across regions for the design and evaluation of MRCTs. We derive an power function for a treatment that is beneficial under DREM and illustrate determination of the overall sample size in an MRCT. We use the concept of consistency based on Method 2 of the Japanese Ministry of Health, Labour, and Welfare's guidance to evaluate the probability for treatment benefit and consistency under DREM. We further derive an optimal sample size allocation over regions to maximize the power for consistency. Moreover, we provide three algorithms for deriving sample size at the desired level of power for benefit and consistency. In practice, regional treatment effects are unknown. Thus, we provide some guidelines on the design of MRCTs with consistency when the regional treatment effect are assumed to fall into a specified interval. Numerical examples are given to illustrate applications of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.
One of the challenges of multiregional drug development program is to design and analyze a multiple regional clinical trial with the objective being to satisfy different regional requirements on primary endpoints. Considered in this article is a multiregional clinical trial (MRCT) designed to test for two primary endpoints. Data of a regular fixed-size well-controlled parallel arm trial are used to test for two null hypotheses in terms of two distinct yet correlated endpoints. The two hypotheses may be tested sequentially or simultaneously. Depending on the structure of the hypotheses to be tested and the understanding of type I error rate control, various scenarios of type I error rate adjustments may be applied. Furthermore, for the objective of getting approval from regional authorities for different primary endpoints, various sample size and power determinations may be applied. In this article, comparisons of different approaches are discussed systematically.
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