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Bayesian decision procedures for binary and continuous bivariate dose-escalation studies

Zhou, Y., Whitehead, J., Bonvini, E. and Stevens, J.S. (2006) Bayesian decision procedures for binary and continuous bivariate dose-escalation studies. Pharmaceutical Statistics, 5 (2). pp. 125-133. ISSN 1539-1612

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To link to this item DOI: 10.1002/pst.222

Abstract/Summary

In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included. Copyright (C) 2006 John Wiley & Sons, Ltd.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
Faculty of Life Sciences > School of Biological Sciences
ID Code:10256
Uncontrolled Keywords:Bayesian decision procedure, dose escalation, logistic regression, linear regression, phase I clinical trial, I/II CLINICAL-TRIALS, PHASE-I TRIALS, REASSESSMENT METHOD, DESIGNS, OUTCOMES, CANCER
Publisher:Wiley

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