ArticleJournal of the American Statistical Association2018
A Bayesian Phase I/II Trial Design for Immunotherapy.
Article in Journal of the American Statistical Association, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 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
- A Bayesian phase I/II biomarker-based design for identifying subgroup-specific optimal dose for immunotherapy.Statistical methods in medical research · 2022Trial
- Generalized phase I-II designs to increase long term therapeutic success rate.Pharmaceutical statisticsTrial
- A Biomarker-Based Dose-Schedule Optimization Design for Immunotherapy Trials.Statistics in medicine · 2026Article
- A Bayesian pharmacokinetics integrated phase I-II design to optimize dose-schedule regimes.Biostatistics (Oxford, England) · 2025Article
- A model-free phase I/II dose optimization design for immunotherapy trials.Statistical methods in medical research · 2025Article
- COMIC: A Bayesian Dose Optimization Design for Drug Combination in Multiple Indications With Application to CAR-T Therapies.Statistics in medicine · 2025Article
- Comb-BOIN12: A Utility-Based Bayesian Optimal Interval Design for Dose Optimization in Cancer Drug-Combination Trials.Statistics in biopharmaceutical research · 2025Article
- REDOMA: Bayesian random-effects dose-optimization meta-analysis using spike-and-slab priors.Statistics in medicine · 2024Article
- A Bayesian latent-subgroup platform design for dose optimization.Biometrics · 2024Article
- Adaptive phase I-II clinical trial designs identifying optimal biological doses for targeted agents and immunotherapies.Clinical trials (London, England) · 2024Review
- Statistical and practical considerations in planning and conduct of dose-optimization trials.Clinical trials (London, England) · 2024Review
- A generalized phase 1-2-3 design integrating dose optimization with confirmatory treatment comparison.Biometrics · 2024Article
- Novel Clinical Trial Designs with Dose Optimization to Improve Long-term Outcomes.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Review
- A Bayesian adaptive design for dual-agent phase I-II oncology trials integrating efficacy data across stages.Biometrical journal. Biometrische Zeitschrift · 2023Article
- Modified isotonic regression based phase I/II clinical trial design identifying optimal biological dose.Contemporary clinical trials · 2023Article
- Interval design to identify the optimal biological dose for immunotherapy.Contemporary clinical trials communications · 2022Article
- Combining cytotoxic agents with continuous dose levels in seamless phase I-II clinical trials.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022Article
- TITE-BOIN12: A Bayesian phase I/II trial design to find the optimal biological dose with late-onset toxicity and efficacy.Statistics in medicine · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Immunotherapy is an innovative treatment approach that stimulates a patient's immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands to revolutionize cancer treatment. We propose a Bayesian phase I/II dosefinding design that incorporates the unique features of immunotherapy by simultaneously considering three outcomes: immune response, toxicity and efficacy. The objective is to identify the biologically optimal dose, defined as the dose with the highest desirability in the risk-benefit tradeoff. An Emax model is utilized to describe the marginal distribution of the immune response. Conditional on the immune response, we jointly model toxicity and efficacy using a latent variable approach. Using the accumulating data, we adaptively randomize patients to experimental doses based on the continuously updated model estimates. A simulation study shows that our proposed design has good operating characteristics in terms of selecting the target dose and allocating patients to the target dose.
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What OpenQuestion holds
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.