ArticleJCO precision oncology2020
BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding in Immunotherapy and Targeted Therapies.
Article in JCO precision oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 137 citations in OpenAlex.
- Trial
- Bayesian adaptive model selection design for optimal biological dose finding in phase I/II clinical trials.Biostatistics (Oxford, England) · 2023Trial
- Surv-CRM-12: A Bayesian phase I/II survival CRM for right-censored toxicity endpoints with competing disease progression.Statistics in medicine · 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
- 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
- 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
- DOSET: dose optimization with simultaneous efficacy and toxicity evaluation, motivated by a first-in-human phase I CAR T lymphoma trial.ESMO open · 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
- BAR12: Bayesian Autoregressive Phase 1-2 Design for Cell Therapy Trials With Manufacturing Changes.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 narrative review of adaptive Phase I/II clinical trial designs for drug combinations in oncology.Frontiers in oncology · 2026Review
- BOP2-Comb: Bayesian Optimal Phase II Design for Optimizing Doses and Assessing Contribution of Components in Drug Combinations.Therapeutic innovation & regulatory science · 2026Article
- Now you see me; now you don't.Science translational medicine · 2025Review
- Randomized optimal selection design for dose optimization.Biometrics · 2025Article
- Dose Optimization in Oncology Drug Development: Risk Factors for Postmarketing Requirements and Commitments.Clinical pharmacology and therapeutics · 2025Article
- Estimands for Early-Phase Dose Optimization Trials in Oncology.Biometrical journal. Biometrische Zeitschrift · 2025Article
- A randomized Bayesian phase I-II dose optimization design for combination cancer therapies with progression-free survival end point.BMC medical research methodology · 2025Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeFor immunotherapy, such as checkpoint inhibitors and chimeric antigen receptor T-cell therapy, where the efficacy does not necessarily increase with the dose, the maximum tolerated dose may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biologic dose (OBD) that optimizes patients' risk-benefit trade-off.
methodsWe propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off. The BOIN12 design makes the decision of dose escalation and de-escalation by simultaneously taking account of efficacy and toxicity and adaptively allocates patients to the dose that optimizes the toxicity-efficacy trade-off. We performed simulation studies to evaluate the performance of the BOIN12 design.
resultsCompared with existing phase I/II dose-finding designs, the BOIN12 design is simpler to implement, has higher accuracy to identify the OBD, and allocates more patients to the OBD. One of the most appealing features of the BOIN12 design is that its adaptation rule can be pretabulated and included in the protocol. During the trial conduct, clinicians can simply look up the decision table to allocate patients to a dose without complicated computation.
conclusionThe BOIN12 design is simple to implement and yields desirable operating characteristics. It overcomes the computational and implementation complexity that plagues existing Bayesian phase I/II dose-finding designs and provides a useful design to optimize the dose of immunotherapy and targeted therapy. User-friendly software is freely available to facilitate the application of the BOIN12 design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.