Optimal group-sequential designs for simultaneous testing of superiority and non-inferiority.
Confirmatory clinical trials comparing the efficacy of a new treatment with an active control typically aim at demonstrating either superiority or non-inferiority. In the latter case, the objective is to show that the experimental treatment is not worse than the active control by more than a pre-specified non-inferiority margin. We consider two classes of group-sequential designs that combine the superiority and non-inferiority objectives: non-adaptive designs with fixed group sizes and adaptive designs where future group sizes may be based on the observed treatment effect. For both classes, we derive group-sequential designs meeting error probability constraints that have the lowest possible expected sample size averaged over a set of values of the treatment effect. These optimized designs provide an efficient means of reducing expected sample size under a range of treatment effects, even when the separate objectives of proving superiority and non-inferiority would require quite different fixed sample sizes. We also present error spending versions of group-sequential designs that are easily implementable and can handle unpredictable group sizes or information levels. We find the adaptive choice of group sizes to yield some modest efficiency gains; alternatively, expected sample size may be reduced by adding another interim analysis to a non-adaptive group-sequential design.
Ohrn
Fredrik
F
AstraZeneca R&D Mölndal, SE-431 83 Mölndal, Sweden. cfo20@bath.ac.uk
Jennison
Christopher
C
D000465:Algorithms; D056808:Biostatistics; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000188:drug therapy; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D018401:Sample Size
D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human