Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs

Ballarini, N.M. and Burnett, T. and Jaki, T. and Jennison, C. and König, F. and Posch, M. (2021) Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs. Statistics in Medicine. ISSN 0277-6715

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Abstract

We design two-stage confirmatory clinical trials that use adaptation to find the subgroup of patients who will benefit from a new treatment, testing for a treatment effect in each of two disjoint subgroups. Our proposal allows aspects of the trial, such as recruitment probabilities of each group, to be altered at an interim analysis. We use the conditional error rate approach to implement these adaptations with protection of overall error rates. Applying a Bayesian decision-theoretic framework, we optimize design parameters by maximizing a utility function that takes the population prevalence of the subgroups into account. We show results for traditional trials with familywise error rate control (using a closed testing procedure) as well as for umbrella trials in which only the per-comparison type 1 error rate is controlled. We present numerical examples to illustrate the optimization process and the effectiveness of the proposed designs.

Item Type:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
153710
Deposited By:
Deposited On:
16 Apr 2021 15:35
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jun 2021 09:10