The use of group sequential, information-based sample size re-estimation in the design of the PRIMO study of XXXX .

@entity1 @entity740 @entity177 @entity4346 @entity21453 @entity418 @entity65 @entity560
BACKGROUND: @entity740 is associated with a marked increase in risk for @entity4346 and @entity65 compared with the general population. Therapy with @entity560 receptor activators has been linked with reduced mortality in @entity740 and an improvement in @entity4346 in animal studies. PURPOSE: PRIMO ( @entity21453 capsules benefits in @entity177 Induced @entity418 MOrbidity) is a multinational, multicenter randomized controlled trial to assess the effects of @entity21453 (a selective @entity560 receptor activator) on mild to moderate @entity4346 in @entity1 with @entity740 . METHODS: Subjects with mild-moderate @entity740 are randomized to @entity21453 or placebo after confirming @entity4346 using a cardiac echocardiogram. Cardiac magnetic resonance imaging is then used to assess left ventricular mass index at baseline, 24 and 48 weeks, which is the primary efficacy endpoint of the study. Because of limited prior data to estimate sample size, a maximum information group sequential design with sample size re-estimation is implemented to allow sample size adjustment based on the nuisance parameter estimated using the interim data. An interim efficacy analysis is planned at a pre-specified time point conditioned on the status of enrollment. The decision to increase sample size depends on the observed treatment effect. A repeated measures analysis model, using available data at Week 24 and 48 with a backup model of an ANCOVA analyzing change from baseline to the final nonmissing observation, are pre-specified to evaluate the treatment effect. Gamma-family of spending function is employed to control family-wise Type I error rate as stopping for success is planned in the interim efficacy analysis. LIMITATIONS: If enrollment is slower than anticipated, the smaller sample size used in the interim efficacy analysis and the greater percent of missing week 48 data might decrease the parameter estimation accuracy, either for the nuisance parameter or for the treatment effect, which might in turn affect the interim decision-making. CONCLUSIONS: The application of combining a group sequential design with a sample-size re-estimation in clinical trial design has the potential to improve efficiency and to increase the probability of trial success while ensuring integrity of the study.
