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Critical aspects of the Bayesian approach to phase I cancer trials
Author(s) -
Neuenschwander Beat,
Branson Michael,
Gsponer Thomas
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3230
Subject(s) - bayesian probability , computer science , clinical trial , maximum tolerated dose , prior information , cancer , bayesian inference , data mining , machine learning , operations research , artificial intelligence , medicine , mathematics
The Bayesian approach to finding the maximum‐tolerated dose in phase I cancer trials is discussed. The suggested approach relies on a realistic dose–toxicity model, allows one to include prior information, and supports clinical decision making by presenting within‐trial information in a transparent way. The modeling and decision‐making components are flexible enough to be extendable to more complex settings. Critical aspects are emphasized and a comparison with the continual reassessment method (CRM) is performed with data from an actual trial and a simulation study. The comparison revealed similar operating characteristics while avoiding some of the difficulties encountered in the actual trial when applying the CRM. Copyright © 2008 John Wiley & Sons, Ltd.