Adaptive Bayesian Phase I Clinical Trials Designs for Estimating the Maximum Tolerated Doses for Two Drugs while Fully Utilizing all Toxicity Information 公开

Abstract

Utilization of multiple drug treatment combinations is very common in contemporary medicine, especially in medical oncology. Therefore, we developed an Adaptive Bayesian Phase I clinical trial design entitled Escalation with Overdose Control (EWOC) using a Normalized Equivalent Toxicity Score (NETS) for estimating the Maximum Tolerated Dose (MTD) contour of two-drug combinations denoted (EWOC-NETSCOM). Using NETS as the primary endpoint in a clinical trial and assuming it follows the quasi-Bernoulli distribution treated as a quasi-continuous random variable in the logistic likelihood function. In addition, four parameters with explicit clinical meanings are reparameterized to describe the association between NETS and the dosage levels of the two drugs (Dose-Toxicity Model). Non-informative priors are used while employing the Markov Chain Monte Carlo (MCMC) method to obtain realizations from a highdimensional probability density, as well as to acquire estimation of four parameters in the Dose-Toxicity Model. Extensive simulations were conducted to evaluate the accuracy, safety, therapeutic effect, and trial efficiency of EWOC-NETS-COM under different scenarios using the EWOC as a reference. The results demonstrate that EWOC-NETSCOM not only estimates the MTD contour of multiple drugs more reliably but also provides a better therapeutic effect by reducing the probability of underdosing patient treatments while fully utilizing all toxicity information to improve trial efficiency.

Table of Contents

1. Introduction .................................................................................................... - 1 -

2. Methods .......................................................................................................... - 5 -

2.1 EWOC-NETS-COM Design for Drug Combinations ................................................. - 5 -

2.2 Prior and Posterior Distribution of Parameters for EWOC-NETS-COM Design ........ - 7 -

2.3 EWOC-COM Design for Drug Combinations ............................................................ - 9 -

2.4 Prior and Posterior Distribution for Parameters of EWOC Design ........................... - 10 -

2.5 Trial Design ............................................................................................................. - 11 -

2.5.1 Pre-stopping Rule ................................................................................................... - 11 -

2.5.2 Procedure for a Trial .............................................................................................. - 11 -

3. Simulation Studies ........................................................................................ - 13 -

3.1 Simulation Setup and Scenarios ............................................................................... - 13 -

3.2 Performance Criteria for Trial Designs .................................................................... - 15 -

4. Results .......................................................................................................... - 17 -

5. Discussion ..................................................................................................... - 19 -

6. References ..................................................................................................... - 21 -

7. Acknowledgement ........................................................................................ - 22 -

8. Appendix ...................................................................................................... - 23 -

About this Master's Thesis

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School	Rollins School of Public Health
Department	Biostatistics
Degree	M.S.P.H.
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health
关键词	Adaptive Bayesian Design Phase I clinical trial Continuous dose level Drug combination
Committee Chair / Thesis Advisor	Chen, Zhengjia(Nelson), Emory University
Committee Members	Kutner, Michael, Emory University
Partnering Agencies	Does not apply (no collaborating organization)

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