AI Article Synopsis

  • MAMS trials compare multiple treatments against a common control arm, allowing for flexible adjustments related to treatment variations like dose or administration route.
  • Effective management of the family-wise error rate (FWER) is crucial in these designs, especially when introducing new treatments mid-trial.
  • The conditional error approach helps integrate new hypotheses while maintaining the statistical integrity of the trial, as demonstrated through simulations.

Article Abstract

Multi-arm multi-stage (MAMS) platform trials efficiently compare several treatments with a common control arm. Crucially MAMS designs allow for adjustment for multiplicity if required. If for example, the active treatment arms in a clinical trial relate to different dose levels or different routes of administration of a drug, the strict control of the family-wise error rate (FWER) is paramount. Suppose a further treatment becomes available, it is desirable to add this to the trial already in progress; to access both the practical and statistical benefits of the MAMS design. In any setting where control of the error rate is required, we must add corresponding hypotheses without compromising the validity of the testing procedure.To strongly control the FWER, MAMS designs use pre-planned decision rules that determine the recruitment of the next stage of the trial based on the available data. The addition of a treatment arm presents an unplanned change to the design that we must account for in the testing procedure. We demonstrate the use of the conditional error approach to add hypotheses to any testing procedure that strongly controls the FWER. We use this framework to add treatments to a MAMS trial in progress. Simulations illustrate the possible characteristics of such procedures.

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Source
http://dx.doi.org/10.1002/sim.10090DOI Listing

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