Subgroup-specific dose finding for phase I-II trials using Bayesian clustering.

ABSTRACT: In most models and algorithms for dose-finding clinical trials, it is assumed that the trial participants are homogeneous-the optimal dose is the same for all those who qualify for the trial. However, if there are heterogeneous populations who may benefit from the same treatment, it is inefficient to conduct dose-finding separately for each group, and assuming homogeneity across all subpopulations may lead to identification of the incorrect dose for some (or all) subgroups. To accommodate heterogeneity in dose-finding trials when both efficacy and toxicity outcomes must be used to identify the optimal dose (as in immunotherapeutic oncology treatments), we utilize an adaptive Bayesian clustering method which borrows strength among similar subgroups and clusters truly homogeneous subgroups.

SUBMITTER: Curtis A 

PROVIDER: S-EPMC9324955 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature