Abstract
Two methods for designing adaptive multiarm multistage (MAMS) clinical trials, originating from conceptually different group sequential frameworks are presented, and their operating characteristics are compared. In both methods pairwise comparisons are made, stage‐by‐stage, between each treatment arm and a common control arm with the goal of identifying active treatments and dropping inactive ones. At any stage one may alter the future course of the trial through adaptive changes to the prespecified decision rules for treatment selection and sample size reestimation, and notwithstanding such changes, both methods guarantee strong control of the family‐wise error rate. The stage‐wise MAMS approach was historically the first to be developed and remains the standard method for designing inferentially seamless phase 2‐3 clinical trials. In this approach, at each stage, the data from each treatment comparison are summarized by a single multiplicity adjusted P‐value. These stage‐wise P‐values are combined by a prespecified combination function and the resultant test statistic is monitored with respect to the classical two‐arm group sequential efficacy boundaries. The cumulative MAMS approach is a more recent development in which a separate test statistic is constructed for each treatment comparison from the cumulative data at each stage. These statistics are then monitored with respect to multiplicity adjusted group sequential efficacy boundaries. We compared the powers of the two methods for designs with two and three active treatment arms, under commonly utilized decision rules for treatment selection, sample size reestimation and early stopping. In our investigations, which were carried out over a reasonably exhaustive exploration of the parameter space, the cumulative MAMS designs were more powerful than the stage‐wise MAMS designs, except for the homogeneous case of equal treatment effects, where a small power advantage was discernable for the stage‐wise MAMS designs.
Highlights
Adaptive multiarm multistage (MAMS) clinical trials compare multiple treatment arms in pairwise fashion to a common control arm over two or more stages
Both methods may be viewed as multivariate extensions of the classical two-arm group sequential design they differ in how they control the multiplicity inherent in an adaptive MAMS design
For completeness we present the stage-wise MAMS approach within the group sequential framework of Reference 2, pointing out how it differs with respect to test statistics and group sequential boundaries from the cumulative MAMS approach
Summary
Adaptive multiarm multistage (MAMS) clinical trials compare multiple treatment arms in pairwise fashion to a common control arm over two or more stages. The stage-wise MAMS approach combines independent multiplicity adjusted P-values from the different stages of the trial in accordance with a prespecified combination function and utilizes closed testing[1] to ensure strong control of the family-wise error rate (FWER). It provides full flexibility, at the end of each stage, to make data-dependent adaptive changes, such as selecting a subset of the initial treatments or reestimating the sample size, for the remainder of the trial. One can directly extend this approach to J > 2 stages, as was performed by Lehmacher and Wassmer[6] for the special case of two-arm trials and by Magirr, Stallard, and Jaki[7] (Section 3.1) for multiarm trials
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