Literature DB >> 27006374

Multiple testing procedures for adaptive enrichment designs: combining group sequential and reallocation approaches.

Michael Rosenblum1, Tianchen Qian2, Yu Du2, Huitong Qiu2, Aaron Fisher2.   

Abstract

Adaptive enrichment designs involve preplanned rules for modifying enrollment criteria based on accrued data in an ongoing trial. For example, enrollment of a subpopulation where there is sufficient evidence of treatment efficacy, futility, or harm could be stopped, while enrollment for the remaining subpopulations is continued. We propose a new class of multiple testing procedures tailored to adaptive enrichment designs. The procedures synthesize ideas from two general approaches. As in the modified group sequential approach, the procedures gain power by leveraging the covariance among statistics for different stages and different hypotheses. As in the alpha reallocation approach, the procedures lower rejection thresholds for the remaining null hypotheses after others have been rejected. The proposed procedures are proved to have power greater than or equal to several existing methods, and to strongly control the familywise Type I error rate when statistics are normally distributed. The methods are illustrated through simulations of a trial for a surgical intervention for stroke, involving two subpopulations.
© The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Multiple testing procedure; Treatment effect heterogeneity

Mesh:

Year:  2016        PMID: 27006374     DOI: 10.1093/biostatistics/kxw014

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  6 in total

1.  Two-stage adaptive enrichment design for testing an active factor.

Authors:  A Adam Ding; Samuel S Wu; Natalie E Dean; Rachel S Zahigian
Journal:  J Biopharm Stat       Date:  2019-05-28       Impact factor: 1.051

2.  Adaptive Enrichment Designs in Clinical Trials.

Authors:  Peter F Thall
Journal:  Annu Rev Stat Appl       Date:  2021-03       Impact factor: 7.917

3.  BAGS: A Bayesian Adaptive Group Sequential Trial Design With Subgroup-Specific Survival Comparisons.

Authors:  Ruitao Lin; Peter F Thall; Ying Yuan
Journal:  J Am Stat Assoc       Date:  2020-11-30       Impact factor: 4.369

4.  Stochastic optimization of adaptive enrichment designs for two subpopulations.

Authors:  Aaron Fisher; Michael Rosenblum
Journal:  J Biopharm Stat       Date:  2018-08-10       Impact factor: 1.503

5.  Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables.

Authors:  Tianchen Qian; Elizabeth Colantuoni; Aaron Fisher; Michael Rosenblum
Journal:  Contemp Clin Trials Commun       Date:  2017-08-16

6.  A multiple comparison procedure for dose-finding trials with subpopulations.

Authors:  Marius Thomas; Björn Bornkamp; Martin Posch; Franz König
Journal:  Biom J       Date:  2019-09-23       Impact factor: 2.207

  6 in total

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