Use of interval estimations in design and evaluation of multiregional clinical trials with continuous outcomes. (July 2019)

• Record Type: Journal Article
• Authors: Chiang, Chieh; Hsiao, Chin-Fu
• Is Part Of: Statistical methods in medical research. Volume 28:Number 7(2019)
• Page Start: 2179
• Page End: 2195
• Publication Date: 2019-07
• Subjects: Multiregional clinical trial -- interval estimation -- sample size determination -- Behrens–Fisher problem -- consistency; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280217751277
• Languages: English
• ISSNs: 0962-2802

Abstract

Multiregional clinical trials have been accepted in recent years as a useful means of accelerating the development of new drugs and abridging their approval time. The statistical properties of multiregional clinical trials are being widely discussed. In practice, variance of a continuous response may be different from region to region, but it leads to the assessment of the efficacy response falling into a Behrens–Fisher problem—there is no exact testing or interval estimator for mean difference with unequal variances. As a solution, this study applies interval estimations of the efficacy response based on Howe's, Cochran–Cox's, and Satterthwaite's approximations, which have been shown to have well-controlled type I error rates. However, the traditional sample size determination cannot be applied to the interval estimators. The sample size determination to achieve a desired power based on these interval estimators is then presented. Moreover, the consistency criteria suggested by the Japanese Ministry of Health, Labour and Welfare guidance to decide whether the overall results from the multiregional clinical trial obtained via the proposed interval estimation were also applied. A real example is used to illustrate the proposed method. The results of simulation studies indicate that the proposed method can correctly determine the required sample size and evaluate the assurance probability of the consistency criteria.