A Bayesian Approach to Evaluating Regional Treatment Effect in a Multiregional Trial

• Published in: Journal of biopharmaceutical statistics Vol. 19; no. 5; pp. 900 - 915
• Main Authors: Chen, Yi-Hau, Wu, Ya-Chi, Wang, Mey
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01.09.2009
• Subjects: Antihypertensive Agents - therapeutic use; Antipsychotic Agents - therapeutic use; Bayes Theorem; Computer Simulation; Data Interpretation, Statistical; Empirical Bayes; Global clinical studies; Humans; Models, Statistical; Multicenter Studies as Topic - statistics & numerical data; Odds Ratio; Power; Residence Characteristics - statistics & numerical data; Sample Size; Sample size allocation; Survival Analysis; Time Factors; Treatment Outcome
• ISSN: 1054-3406; 1520-5711
• 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.