A Bayesian adaptive design in cancer phase I trials using dose combinations in the presence of a baseline covariate

DOI10.1155/2018/8654173zbMath1431.62493OpenAlexW2898913558WikidataQ92583854 ScholiaQ92583854MaRDI QIDQ1733138

Márcio Augusto Diniz, Sungjin Kim, Mourad Tighiouart

Publication date: 21 March 2019

Published in: Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2018/8654173

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Medical applications (general) (92C50)

Related Items (1)

Evaluation of phase I clinical trial designs for combinational agents along with guidance based on simulation studies

Uses Software

• JAGS

Cites Work

• Dose finding with escalation with overdose control (EWOC) in cancer clinical trials
• Optimal Bayesian-feasible dose escalation for cancer phase I trials
• Escalation with overdose control using ordinal toxicity grades for cancer phase I clinical trials
• Continual Reassessment Method for Partial Ordering
• A Hierarchical Bayesian Design for Phase I Trials of Novel Combinations of Cancer Therapeutic Agents
• Continual Reassessment Method for Ordered Groups
• Dose-Finding with Two Agents in Phase I Oncology Trials
• A Latent Contingency Table Approach to Dose Finding for Combinations of Two Agents
• TWO-SAMPLE CONTINUAL REASSESSMENT METHOD
• Two‐Dimensional Dose Finding in Discrete Dose Space

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