ArticleStatistics in medicine2019
A utility-based Bayesian optimal interval (U-BOIN) phase I/II design to identify the optimal biological dose for targeted and immune therapies.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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Who cites it
60 citing papers in PubMed.
- Trial
- SCI: A Bayesian adaptive phase I/II dose-finding design accounting for semi-competing risks outcomes for immunotherapy trials.Pharmaceutical statistics · 2022Trial
- The use of local and nonlocal priors in Bayesian test-based monitoring for single-arm phase II clinical trials.Pharmaceutical statistics · 2021Trial
- Generalized phase I-II designs to increase long term therapeutic success rate.Pharmaceutical statisticsTrial
- From Phase Ib/II to Seamless Phase II/III: A Simulation-Based Discussion of Design Strategies for Dose Optimization and Confirmatory Phase.Clinical pharmacology and therapeutics · 2026Article
- A review of seamless phase I/II trial designs towards oncology dose optimization with examples of clinical pharmacology considerations in early drug development.European journal of clinical pharmacology · 2026Review
- BE-BOIN: A Dose Optimization Design Accommodating Backfill and Late-Onset Toxicity.Therapeutic innovation & regulatory science · 2026Article
- Generalized Pairwise Comparisons in Dose Optimization Oncology Trials: Beyond Safety to Multi-outcome Dose Selection.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Advancing Platform Trials in Early Oncology by Using MATS and EXNEX in Randomized Controlled Trials.Therapeutic innovation & regulatory science · 2026Article
- DOSET: dose optimization with simultaneous efficacy and toxicity evaluation, motivated by a first-in-human phase I CAR T lymphoma trial.ESMO open · 2026Article
- PRO-ADD: Patient-empowered dose-finding trials integrating safety, preliminary efficacy and patient-reported outcomes for optimal dose selection.Statistical methods in medical research · 2026Article
- Information borrowing in phase II randomized dose-ranging clinical trials in oncology.BMC medical research methodology · 2026Article
- Defining Utility as a Measure of Preference Under Uncertainty in Phase I-II Oncology Dose Finding Trials.Statistics in medicine · 2026Article
- A short review of dose-finding adaptive trial designs for clinical pharmacologists and non-statisticians in oncology.European journal of clinical pharmacology · 2026Review
- BOP2-TE: Bayesian optimal phase 2 design for jointly monitoring efficacy and toxicity with application to dose optimization.Journal of biopharmaceutical statistics · 2026Article
- A Bayesian pharmacokinetics integrated phase I-II design to optimize dose-schedule regimes.Biostatistics (Oxford, England) · 2025Article
- Randomized optimal selection design for dose optimization.Biometrics · 2025Article
- Estimands for Early-Phase Dose Optimization Trials in Oncology.Biometrical journal. Biometrische Zeitschrift · 2025Article
- A robust Bayesian dose optimization design with backfill and randomization for phase I/II clinical trials.Statistical methods in medical research · 2025Article
- BARD: A seamless two-stage dose optimization design integrating backfill and adaptive randomization.Clinical trials (London, England) · 2025Article
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3 authors.
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Abstract
In the era of targeted therapy and immunotherapy, the objective of dose finding is often to identify the optimal biological dose (OBD), rather than the maximum tolerated dose. We develop a utility-based Bayesian optimal interval (U-BOIN) phase I/II design to find the OBD. We jointly model toxicity and efficacy using a multinomial-Dirichlet model, and employ a utility function to measure dose risk-benefit trade-off. The U-BOIN design consists of two seamless stages. In stage I, the Bayesian optimal interval design is used to quickly explore the dose space and collect preliminary toxicity and efficacy data. In stage II, we continuously update the posterior estimate of the utility for each dose after each cohort, using accumulating efficacy and toxicity from both stages I and II, and then use the posterior estimate to direct the dose assignment and selection. Compared to existing phase I/II designs, one prominent advantage of the U-BOIN design is its simplicity for implementation. Once the trial is designed, it can be easily applied using predetermined decision tables, without complex model fitting and estimation. Our simulation study shows that, despite its simplicity, the U-BOIN design is robust and has high accuracy to identify the OBD. We extend the design to accommodate delayed efficacy by leveraging the short-term endpoint (eg, immune activity or other biological activity of targeted agents), and using it to predict the delayed efficacy outcome to facilitate real-time decision making. A user-friendly software to implement the U-BOIN is freely available at www.trialdesign.org.
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