ArticleStatistics in medicine2022
BIPSE: A biomarker-based phase I/II design for immunotherapy trials with progression-free survival endpoint.
Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Bayesian phase I/II design to determine subgroup-specific optimal dose for immunotherapy sequentially combined with radiotherapy.Pharmaceutical statistics · 2023Trial
- 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
- A Biomarker-Based Dose-Schedule Optimization Design for Immunotherapy Trials.Statistics in medicine · 2026Article
- A model-free phase I/II dose optimization design for immunotherapy trials.Statistical methods in medical research · 2025Article
- Adaptive phase I-II clinical trial designs identifying optimal biological doses for targeted agents and immunotherapies.Clinical trials (London, England) · 2024Review
- Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses.Clinical trials (London, England) · 2024Review
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Authors and funding
2 authors.
Funding
Abstract
A Bayesian biomarker-based phase I/II design (BIPSE) is presented for immunotherapy trials with a progression-free survival (PFS) endpoint. The objective is to identify the subgroup-specific optimal dose, defined as the dose with the best risk-benefit tradeoff in each biomarker subgroup. We jointly model the immune response, toxicity outcome, and PFS with information borrowing across subgroups. A plateau model is used to describe the marginal distribution of the immune response. Conditional on the immune response, we model toxicity using probit regression and model PFS using the mixture cure rate model. During the trial, based on the accumulating data, we continuously update model estimates and adaptively randomize patients to doses with high desirability within each subgroup. Simulation studies show that the BIPSE design has desirable operating characteristics in selecting the subgroup-specific optimal doses and allocating patients to those optimal doses, and outperforms conventional designs.
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Registered trials
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