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Group sequential enrichment design incorporating subgroup selection
Author(s) -
Magnusson Baldur P.,
Turnbull Bruce W.
Publication year - 2013
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5738
Subject(s) - sample size determination , interim analysis , type i and type ii errors , early stopping , statistics , subgroup analysis , multiple comparisons problem , computer science , interim , sequential analysis , selection (genetic algorithm) , time point , confidence interval , econometrics , mathematics , clinical trial , medicine , machine learning , archaeology , artificial neural network , history , philosophy , aesthetics
An important component of clinical trials in drug development is the analysis of treatment efficacy in patient subgroups (subpopulations). Because of concerns of multiplicity and of the small sample sizes often involved, such analyses can present substantial statistical challenges and may lead to misleading conclusions. As a confirmatory seamless phase II/III design, we propose an adaptive enrichment group sequential procedure whereby resources can be concentrated on subgroups most likely to respond to treatment. Stopping boundaries are defined through upper and lower spending functions. The procedure is presented in terms of the efficient score, enabling the analysis of normal, binary, or time‐to‐event data. It addresses the dilution effect by eliminating populations at the first stage that appear likely to derive no therapeutic benefit. It subsequently proceeds with the definitive assessment of treatment efficacy among the remaining pooled populations using a group sequential design. The procedure provides strong protection of familywise type I error rate, and we employ a bootstrap algorithm to obtain point and interval estimates that are adjusted for the selection bias. We give examples to demonstrate how the design is used. We make comparisons with adaptive two‐stage combination test procedures and with a group sequential test that does not account for the presence of subgroups. Numerical results show that the procedure has high power to detect subgroup‐specific effects and the use of multiple interim analysis points can lead to substantial sample size savings. Copyright © 2013 John Wiley & Sons, Ltd.