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- Title
Treatment evaluation for a data-driven subgroup in adaptive enrichment designs of clinical trials.
- Authors
Zhang, Zhiwei; Chen, Ruizhe; Soon, Guoxing; Zhang, Hui
- Abstract
Adaptive enrichment designs (AEDs) of clinical trials allow investigators to restrict enrollment to a promising subgroup based on an interim analysis. Most of the existing AEDs deal with a small number of predefined subgroups, which are often unknown at the design stage. The newly developed Simon design offers a great deal of flexibility in subgroup selection (without requiring pre-defined subgroups) but does not provide a procedure for estimating and testing treatment efficacy for the selected subgroup. This article proposes a 2-stage AED which does not require predefined subgroups but requires a prespecified algorithm for choosing a subgroup on the basis of baseline covariate information. Having a prespecified algorithm for subgroup selection makes it possible to use cross-validation and bootstrap methods to correct for the resubstitution bias in estimating treatment efficacy for the selected subgroup. The methods are evaluated and compared in a simulation study mimicking actual clinical trials of human immunodeficiency virus infection.
- Subjects
ALGORITHMS; CLINICAL trials; COMPARATIVE studies; COMPUTER simulation; EXPERIMENTAL design; HIV infections; RESEARCH methodology; MEDICAL cooperation; NONPARAMETRIC statistics; REGRESSION analysis; RESEARCH; STATISTICS; EVALUATION research; TREATMENT effectiveness; STATISTICAL models
- Publication
Statistics in Medicine, 2018, Vol 37, Issue 1, p1
- ISSN
0277-6715
- Publication type
journal article
- DOI
10.1002/sim.7497