Faculty, Staff and Student Publications
Language
English
Publication Date
1-1-2026
Journal
Journal of Biopharmaceutical Statistics
DOI
10.1080/10543406.2024.2429481
PMID
39582234
PMCID
PMC12102293
PubMedCentral® Posted Date
1-8-2026
PubMedCentral® Full Text Version
Author MSS
Abstract
We propose a Bayesian optimal phase 2 design for jointly monitoring efficacy and toxicity, referred to as BOP2-TE, to improve the operating characteristics of the BOP2 design proposed by Zhou et al. (2017). BOP2-TE utilizes a Dirichlet-multinomial model to jointly model the distribution of toxicity and efficacy endpoints, making go/no-go decisions based on the posterior probability of toxicity and futility. In comparison to the original BOP2 and other existing designs, BOP2-TE offers the advantage of providing rigorous type I error control in cases where the treatment is toxic and futile, effective but toxic, or safe but futile, while optimizing power when the treatment is effective and safe. As a result, BOP2-TE enhances trial safety and efficacy. We also explore the incorporation of BOP2-TE into multiple-dose randomized trials for dose optimization, and consider a seamless design that integrates phase I dose finding with phase II randomized dose optimization. BOP2-TE is user-friendly, as its decision boundary can be determined prior to the trial’s onset. Simulations demonstrate that BOP2-TE possesses desirable operating characteristics. We have developed a user-friendly web application as part of the BOP2 app, which is freely available at www.trialdesign.org.
Keywords
Bayes Theorem, Humans, Clinical Trials, Phase II as Topic, Research Design, Dose-Response Relationship, Drug, Computer Simulation, Models, Statistical, Randomized Controlled Trials as Topic, Treatment Outcome, Bayesian design, phase II trials, dose optimization, go/no go decision, multiple-dose randomized trials
Published Open-Access
yes
Recommended Citation
Chen, Kai; Zhou, Heng; Lee, J Jack; et al., "BOP2-Te: Bayesian Optimal Phase 2 Design for Jointly Monitoring Efficacy and Toxicity With Application to Dose Optimization" (2026). Faculty, Staff and Student Publications. 6067.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6067
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