ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2019
An information theoretic phase I-II design for molecularly targeted agents that does not require an assumption of monotonicity.
Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Bayesian adaptive model selection design for optimal biological dose finding in phase I/II clinical trials.Biostatistics (Oxford, England) · 2023Trial
- A narrative review of adaptive Phase I/II clinical trial designs for drug combinations in oncology.Frontiers in oncology · 2026Review
- Bayesian model averaging for partial ordering continual reassessment methods.Biostatistics (Oxford, England) · 2025Article
- Using circulating tumor DNA as a novel biomarker of efficacy for dose-finding designs in oncology.Statistical methods in medical research · 2025Article
- crm12comb: Phase I/II adaptive design for drug combinations based on CRM design through R.PloS one · 2025Article
- A seamless Phase I/II platform design with a time-to-event efficacy endpoint for potential COVID-19 therapies.Statistical methods in medical research · 2024Article
- REDOMA: Bayesian random-effects dose-optimization meta-analysis using spike-and-slab priors.Statistics in medicine · 2024Article
- A comparison of model-free phase I dose escalation designs for dual-agent combination therapies.Statistical methods in medical research · 2024Article
- Early phase clinical trials in oncology: Realising the potential of seamless designs.European journal of cancer (Oxford, England : 1990) · 2023Article
- A novel statistical test for treatment differences in clinical trials using a response-adaptive forward-looking Gittins Index Rule.Biometrics · 2023Article
- Optimizing dose-schedule regimens with bayesian adaptive designs: opportunities and challenges.Frontiers in pharmacology · 2023Review
- Practical implementation of the partial ordering continual reassessment method in a Phase I combination-schedule dose-finding trial.Statistics in medicine · 2022Article
- A benchmark for dose-finding studies with unknown ordering.Biostatistics (Oxford, England) · 2022Article
- A dose-finding design for dual-agent trials with patient-specific doses for one agent with application to an opiate detoxification trial.Pharmaceutical statistics · 2022Article
- Response adaptive designs for Phase II trials with binary endpoint based on context-dependent information measures.Computational statistics & data analysis · 2021Article
- uTPI: A utility-based toxicity probability interval design for phase I/II dose-finding trials.Statistics in medicine · 2021Article
- Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.BMC medicine · 2020Article
- A surface-free design for phase I dual-agent combination trials.Statistical methods in medical research · 2020Article
- Flexible Phase I-II design for partially ordered regimens with application to therapeutic cancer vaccines.Statistics in biosciences · 2020Article
- Improving safety of the continual reassessment method via a modified allocation rule.Statistics in medicine · 2020Article
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Authors and funding
2 authors.
Funding
Abstract
For many years phase I and phase II clinical trials have been conducted separately, but there has been a recent shift to combine these phases. Although a variety of phase I-II model-based designs for cytotoxic agents have been proposed in the literature, methods for molecularly targeted agents (TAs) are just starting to develop. The main challenge of the TA setting is the unknown dose-efficacy relationship that can have either an increasing, plateau or umbrella shape. To capture these, approaches with more parameters are needed or, alternatively, more orderings are required to account for the uncertainty in the dose-efficacy relationship. As a result, designs for more complex clinical trials, e.g. trials looking at schedules of a combination treatment involving TAs, have not been extensively studied yet. We propose a novel regimen finding design which is based on a derived efficacy-toxicity trade-off function. Because of its special properties, an accurate regimen selection can be achieved without any parametric or monotonicity assumptions. We illustrate how this design can be applied in the context of a complex combination-schedule clinical trial. We discuss practical and ethical issues such as coherence, delayed and missing efficacy responses, safety and futility constraints.
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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.