Annual Review of Statistics and Its Application Adaptive Enrichment Designs in Clinical Trials Peter F. Thall Department of Biostatistics, M.D. Anderson Cancer Center, University of Texas, Houston, Texas 77030, USA; email:
[email protected] Annu. Rev. Stat. Appl. 2021. 8:393–411 Keywords The Annual Review of Statistics and Its Application is adaptive signature design, Bayesian design, biomarker, clinical trial, group online at statistics.annualreviews.org sequential design, precision medicine, subset selection, targeted therapy, https://doi.org/10.1146/annurev-statistics-040720- variable selection 032818 Copyright © 2021 by Annual Reviews. Abstract All rights reserved Adaptive enrichment designs for clinical trials may include rules that use in- terim data to identify treatment-sensitive patient subgroups, select or com- pare treatments, or change entry criteria. A common setting is a trial to Annu. Rev. Stat. Appl. 2021.8:393-411. Downloaded from www.annualreviews.org compare a new biologically targeted agent to standard therapy. An enrich- ment design’s structure depends on its goals, how it accounts for patient heterogeneity and treatment effects, and practical constraints. This article Access provided by University of Texas - M.D. Anderson Cancer Center on 03/10/21. For personal use only. first covers basic concepts, including treatment-biomarker interaction, pre- cision medicine, selection bias, and sequentially adaptive decision making, and briefly describes some different types of enrichment. Numerical illus- trations are provided for qualitatively different cases involving treatment- biomarker interactions. Reviews are given of adaptive signature designs; a Bayesian design that uses a random partition to identify treatment-sensitive biomarker subgroups and assign treatments; and designs that enrich superior treatment sample sizes overall or within subgroups, make subgroup-specific decisions, or include outcome-adaptive randomization.