Two-arm group sequential designs have been widely used for over 40 years, especially for studies with mortality endpoints. The natural generalization of such designs to trials with multiple treatment arms and a common control (MAMS designs) has, however, been implemented rarely. While the statistical methodology for this extension is clear, the main limitation has been an efficient way to perform the computations. Past efforts were hampered by algorithms that were computationally explosive. With the increasing interest in adaptive designs, platform designs, and other innovative designs that involve multiple comparisons over multiple stages, the importance of MAMS designs is growing rapidly. This article provides break-through algorithms that can compute MAMS boundaries rapidly thereby making such designs practical. For designs with efficacy-only boundaries the computational effort increases linearly with number of arms and number of stages. For designs with both efficacy and futility boundaries the computational effort doubles with successive increases in number of stages.
Keywords: Adaptive designs; Computation of stopping boundaries; Early efficacy stopping; Futility stopping; Generalized Dunnett tests; Group sequential; Multiple comparisons; Platform designs; Spending functions; Strong control of type-1 error.
© 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.