Chen Yi-Hau, Wu Ya-Chi, Wang Mey
Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, ROC.
J Biopharm Stat. 2009 Sep;19(5):900-15. doi: 10.1080/10543400903105471.
A multiregional trial, conducted in more than one region under a common protocol, is a promising strategy making valuable medicines available to patients globally without time lag. When evaluating the treatment effect for each local region, one may wish to utilize information from other regions to enhance the statistical power. This work proposes a Bayesian approach to bridging data across different regions in a multiregional trial to get an improved analysis of treatment effect for a local region. The new proposal has the following distinct features: (1) It performs internal bridging in a multiregional trial, with the degree of bridging automatically determined by the interregional variability of the treatment effect across different regions; (2) it usually ensures the consistency of the conclusions from local and global inference when the treatment effect is virtually homogeneous across regions and is found nonsignificant globally; (3) it generally protects against overbridging of the global information for evaluating the treatment effect in a very small region. Formulas for statistical power of the proposed method are provided. We illustrate the utility of the proposed method by two numerical examples reflecting typical issues we may encounter in evaluating regional treatment effect in a multiregional trial.
一项按照共同方案在多个地区开展的多区域试验，是一种很有前景的策略，能让全球患者无时间延迟地用上有价值的药物。在评估每个局部地区的治疗效果时，人们可能希望利用其他地区的信息来提高统计效能。这项工作提出了一种贝叶斯方法，用于在多区域试验中整合不同地区的数据，以改进对局部地区治疗效果的分析。新方法具有以下显著特点：（1）它在多区域试验中进行内部整合，整合程度由不同地区治疗效果的区域间变异性自动确定；（2）当各地区治疗效果实际相同时且全球范围内无显著差异时，它通常能确保局部和全局推断结论的一致性；（3）它一般能防止在评估非常小的地区的治疗效果时过度整合全局信息。文中给出了所提方法的统计效能公式。我们通过两个数值例子说明了所提方法的实用性，这两个例子反映了在多区域试验中评估区域治疗效果时可能遇到的典型问题。
