Dose finding with escalation with overdose control (EWOC) in cancer clinical trials

DOI10.1214/10-STS333zbMath1328.62598arXiv1011.6479OpenAlexW2952060368MaRDI QIDQ903293

Mourad Tighiouart, André Rogatko

Publication date: 5 January 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1011.6479

zbMATH Keywords

cancer phase I trialsdose-limiting toxicityescalation with overdose controloptimal Bayesian feasibletolerated dose

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian problems; characterization of Bayes procedures (62C10) Medical applications (general) (92C50)

Related Items (9)

A new design of the continual reassessment method ⋮ Escalation with overdose control using ordinal toxicity grades for cancer phase I clinical trials ⋮ Methodology and application of adaptive and sequential approaches in contemporary clinical trials ⋮ Number of patients per cohort and sample size considerations using dose escalation with overdose control ⋮ A continual reassessment method without undue risk of toxicity ⋮ Stochastic approximation and modern model-based designs for dose-finding clinical trials ⋮ Adaptive clinical trial designs for phase I cancer studies ⋮ A Bayesian adaptive design in cancer phase I trials using dose combinations in the presence of a baseline covariate ⋮ Incoherent dose-escalation in phase I trials using the escalation with overdose control approach

Uses Software

• WinBUGS
• EWOC

Cites Work

• Unnamed Item
• Continual Reassessment Method: A Practical Design for Phase 1 Clinical Trials in Cancer
• Unifying CRM and EWOC designs for phase I cancer clinical trials
• Optimal Bayesian-feasible dose escalation for cancer phase I trials
• Dose finding in drug development.
• Coherence principles in dose-finding studies
• TWO-SAMPLE CONTINUAL REASSESSMENT METHOD
• Sequential Designs for Phase I Clinical Trials with Late‐Onset Toxicities
• Statistical properties of the traditional algorithm-based designs for phase I cancer clinical trials

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