ArticleAmerican journal of biostatistics2016
A Bayesian Adaptive Design for Combination of Three Drugs in Cancer Phase I Clinical Trials.
Article in American journal of biostatistics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?Brazilian journal of biometrics · 2022Article
- A nonparametric Bayesian method for dose finding in drug combinations cancer trials.Statistics in medicine · 2022Article
- A Bayesian Adaptive Design in Cancer Phase I Trials Using Dose Combinations with Ordinal Toxicity Grades.Stats · 2020Article
- Cancer phase I trial design using drug combinations when a fraction of dose limiting toxicities is attributable to one or more agents.Biometrical journal. Biometrische Zeitschrift · 2019Article
- AAA: triple adaptive Bayesian designs for the identification of optimal dose combinations in dual-agent dose finding trials.Journal of the Royal Statistical Society. Series C, Applied statistics · 2019Article
- A Bayesian Adaptive Design in Cancer Phase I Trials using Dose Combinations in the Presence of a Baseline Covariate.Journal of probability and statistics · 2018Article
- Dose Finding for Drug Combination in Early Cancer Phase I Trials using Conditional Continual Reassessment Method.Journal of biometrics & biostatistics · 2017Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
We describe a Bayesian adaptive design for early phase cancer trials of a combination of three agents. This is an extension of an earlier work by the authors by allowing all three agents to vary during the trial and by assigning different drug combinations to cohorts of three patients. The primary objective is to estimate the Maximum Tolerated Dose (MTD) surface in the three-dimensional Cartesian space. A class of linear models on the logit of the probability of Dose Limiting Toxicity (DLT) are used to describe the relationship between doses of the three drugs and the probability of DLT. Trial design proceeds using conditional escalation with overdose control, where at each stage of the trial, we seek a dose of one agent using the current posterior distribution of the MTD of this agent given the current doses of the other two agents. The MTD surface is estimated at the end of the trial as a function of Bayes estimates of the model parameters. Operating characteristics are evaluated with respect to trial safety and percent of dose recommendation at dose combination neighborhoods around the true MTD surface.
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Registered trials
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.