Diao Guoqing, Zeng Donglin, Ibrahim Joseph G, Rong Alan, Lee Oliver, Zhang Kathy, Chen Qingxia
a Department of Statistics , George Mason University , Fairfax , Virginia , USA.
b Department of Biostatistics , University of North Carolina at Chapel Hill , Chapel Hill , North Carolina , USA.
J Biopharm Stat. 2017;27(6):933-944. doi: 10.1080/10543406.2017.1293075. Epub 2017 Mar 15.
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.
非劣效性多区域临床试验（MRCTs）最近在药物研发中受到越来越多的关注。虽然MRCT的一个主要目标是估计全球治疗效果，但评估多个区域治疗效果的一致性也很重要。在本文中，我们在随机效应建模框架下提出了一个关于跨区域非劣效治疗效果一致性的直观定义。具体来说，我们通过达到预定义治疗界值的区域百分比来量化治疗效果的一致性。这种新方法使我们能够在一个建模框架中实现两个目标。我们建议使用符号似然比检验来检验全球治疗效果和非劣效治疗效果的一致性。此外，我们提供了分配规则的指导方针，以实现检验多个区域之间一致性的最佳效能。进行了广泛的模拟研究以检验所提出方法的性能。还提供了一个实际数据示例的应用。
