Bayesian Decision Procedures For Dose-Escalation Studies With Cohort Effects

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Maria Daya Roopa , Dr. Nimitha John

Abstract

This paper considers the methods of modelling for the dose escalation process using the Bayesian hierarchical models. The phase I clinical trial data is analysed to find the optimum Maximum Tolerated Dose (MTD). In this paper we have considered the mixed logistic linear regression model to predict the dose limiting event with respect to the cohort effects and the doses. We have also developed a mixed linear regression model to predict the desirable outcome response in the study. The illustrations of the models have been conducted which is then analysed to find the MTD for the clinical trial study.


 

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