scholarly journals Sample size determination in group-sequential clinical trials with two co-primary endpoints

2014 ◽  
Vol 33 (17) ◽  
pp. 2897-2913 ◽  
Author(s):  
Koko Asakura ◽  
Toshimitsu Hamasaki ◽  
Tomoyuki Sugimoto ◽  
Kenichi Hayashi ◽  
Scott R. Evans ◽  
...  
PLoS ONE ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. e0180405 ◽  
Author(s):  
Wong-Shian Huang ◽  
Hui-Nien Hung ◽  
Toshimitsu Hamasaki ◽  
Chin-Fu Hsiao

2020 ◽  
pp. 096228022097579
Author(s):  
Duncan T Wilson ◽  
Richard Hooper ◽  
Julia Brown ◽  
Amanda J Farrin ◽  
Rebecca EA Walwyn

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of sample size determination problems, often minimising a single parameter (the overall sample size) subject to power being above a target level. We describe a general framework for solving simulation-based sample size determination problems with several design parameters over which to optimise and several conflicting criteria to be minimised. The method is based on an established global optimisation algorithm widely used in the design and analysis of computer experiments, using a non-parametric regression model as an approximation of the true underlying power function. The method is flexible, can be used for almost any problem for which power can be estimated using simulation, and can be implemented using existing statistical software packages. We illustrate its application to a sample size determination problem involving complex clustering structures, two primary endpoints and small sample considerations.


2018 ◽  
Vol 28 (7) ◽  
pp. 2179-2195 ◽  
Author(s):  
Chieh Chiang ◽  
Chin-Fu Hsiao

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.


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