A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients

DOI10.1080/01621459.2013.806927OpenAlexW2019966306WikidataQ37291757 ScholiaQ37291757MaRDI QIDQ2861803

Jin Zhang, Thomas M. Braun

Publication date: 11 November 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3821780

zbMATH Keywords

Bayesian statisticsclinical trialdynamic treatment regimedose-escalation studynonmixture cure model

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

DICE: A Bayesian model for early dose finding in phase I trials with multiple treatment courses ⋮ Bayesian dose regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics ⋮ Adaptive clinical trial designs for phase I cancer studies

Cites Work

• Continual Reassessment Method: A Practical Design for Phase 1 Clinical Trials in Cancer
• AMCMC: an R interface for adaptive MCMC
• Analysis of multivariate survival data
• A nonidentifiability aspect of the problem of competing risks.
• Optimal Dynamic Treatment Regimes
• Sequential Designs for Phase I Clinical Trials with Late‐Onset Toxicities
• Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials
• Determining a Maximum‐Tolerated Schedule of a Cytotoxic Agent

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