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The design of clinical trials often requires knowledge of quantities such as between- and within subject variances about which only imprecise information exists. To provide assurance that the study has the desired power to detect a minimum clinically meaningful difference between treatment groups. Gould, Gould and Shih, and Shih have recommended obtaining relevant information from the trial at an interim stage without unblinding. Wittes and Brittain provided a similar recommendation, but viewed the portion up to the interim stage as an (internal) pilot study and required unblinding. This paper considers the problem of re-evaluating the design specifications in longitudinal clinical trials when the key response is the rate of change (slope). The proposed method aims to re-evaluate the sample size and study duration in a way that maintains the trial's blinding, using an EM algorithm. Simulation results show that the effect on type I error rate in negligible, but the potential gain in power can be substantial. The procedure is simple to use in practice, as it does not unblind patients' treatment identifications, and, since it does not unveil the relative efficacy of treatments, it fulfils the requirement of a valid 'administrative' (interim) analysis.
Shih et al. (Mon,) studied this question.