ArticleStatistics in medicine2017
Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials.
Article in Statistics in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A Bayesian adaptive design for dual-agent phase I-II oncology trials integrating efficacy data across stages.Biometrical journal. Biometrische Zeitschrift · 2023Article
- Development of consensus-driven SPIRIT and CONSORT extensions for early phase dose-finding trials: the DEFINE study.BMC medicine · 2023Review
- Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?Brazilian journal of biometrics · 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
- A nonparametric Bayesian method for dose finding in drug combinations cancer trials.Statistics in medicine · 2022Article
- Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.BMC medicine · 2020Article
- A Bayesian seamless phase I-II trial design with two stages for cancer clinical trials with drug combinations.Biometrical journal. Biometrische Zeitschrift · 2020Article
- Improving safety of the continual reassessment method via a modified allocation rule.Statistics in medicine · 2020Article
- Proportional odds assumption for modeling longitudinal ordinal multiple toxicity outcomes in dose finding studies of targeted agents: A pooled analysis of 54 studies.Contemporary clinical trials communications · 2020Article
- Comparison between continuous and discrete doses for model based designs in cancer dose finding.PloS one · 2019Article
- Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials.Statistics in medicine · 2017Article
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3 authors.
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Abstract
Phase I trials of anti-cancer therapies aim to identify a maximum tolerated dose (MTD), defined as the dose that causes unacceptable toxicity in a target proportion of patients. Both rule-based and model-based methods have been proposed for MTD recommendation. The escalation with overdose control (EWOC) approach is a model-based design where the dose assigned to the next patient is one that, given all available data, has a posterior probability of exceeding the MTD equal to a pre-specified value known as the feasibility bound. The aim is to conservatively dose-escalate and approach the MTD, avoiding severe overdosing early on in a trial. The EWOC approach has been applied in practice with the feasibility bound either fixed or varying throughout a trial, yet some of the methods may recommend incoherent dose-escalation, that is, an increase in dose after observing severe toxicity at the current dose. We present examples where varying feasibility bounds have been used in practice, and propose a toxicity-dependent feasibility bound approach that guarantees coherent dose-escalation and incorporates the desirable features of other EWOC approaches. We show via detailed simulation studies that the toxicity-dependent feasibility bound approach provides improved MTD recommendation properties to the original EWOC approach for both discrete and continuous doses across most dose-toxicity scenarios, with comparable performance to other approaches without recommending incoherent dose escalation. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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