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An evaluation of a Bayesian method of dose escalation based on bivariate binary responses

Whitehead, J., Zhou, Y., Stevens, J. and Blakey, G. (2004) An evaluation of a Bayesian method of dose escalation based on bivariate binary responses. Journal of Biopharmaceutical Statistics, 14 (4). pp. 969-983. ISSN 1054-3406

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To link to this item DOI: 10.1081/BIP-200035471


Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
ID Code:9435
Uncontrolled Keywords:Bayesian decision procedure, Continual reassessment method, Dose escalation, Logistic regression, Phase I clinical trial

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