J Biopharm Stat. 2023 Nov 6:1-15. doi: 10.1080/10543406.2023.2275755. Online ahead of print.
ABSTRACT
Clinical trialists have long been searching for approaches to increase statistical power without increasing sample size. Conventional wait-list controlled (WLC) trials are limited to two trial arms and two or three repeated measurements per person. These features limit statistical power. Furthermore, their analysis is usually based on analysis of covariance or mixed effects modelling, with a focus on estimating treatment effect at one time-period after initiation of therapy. We propose two 3-arm WLC trial designs together with a mixed-effects analysis framework. The designs require three or four repeated measurements per person. The analytic framework defines up to three treatment effect estimands, representing the effects at one to three time-periods after initiation of therapy. The precision (inverse of variance) of the treatment effect estimators in the new and conventional trial designs are analytically derived and evaluated in simulations. The results are interpreted in the context of a cognitive training trial in older people. The proposed designs and analysis methods increase the precision level of treatment effect estimators as compared to conventional designs and analyses. Given a target level of statistical power, the proposed methods require a smaller number of participants per trial than the conventional methods, without necessarily increasing the number of measurements per trial. Furthermore, the proposed analytic framework sheds light on the treatment effects at different times after initiation of therapy, which is not usually considered in conventional WLC trial analysis. In situations that a WLC trial is appropriate, the 3-arm designs are useful alternatives to existing 2-arm designs.
PMID:37929703 | DOI:10.1080/10543406.2023.2275755
