Department seminar by Ruitao Lin, The University of Texas MD Anderson Cancer Center Export this event to calendar

Tuesday, January 8, 2019 — 4:00 PM EST

Nonparametric Overdose Control in Phase I Dose-Finding Clinical Trials


The primary objective of phase I oncology trials is to assess the safety of the new drug. Under the framework of Bayesian model selection, we propose a nonparametric overdose control (NOC) design for dose finding in phase I clinical trials. Each dose assignment is guided via a feasibility bound, which thereby can control the number of patients allocated to excessively toxic dose levels. We further develop a fractional NOC (fNOC) design in conjunction with a so-called fractional imputation approach, to account for late-onset toxicity outcomes. Extensive simulation studies have been conducted to show that both the NOC and fNOC designs have robust and satisfactory finite-sample performance compared with the existing dose-finding designs. The proposed methods also possess several desirable properties: treating patients more safely and also neutralizing the aggressive escalation to overly toxic doses when the toxicity outcomes are late-onset. We also generalize the NOC design to handle drug-combination trials and phase I/II trials. 

Bio:

Ruitao Lin received his Ph.D. degree from the Department of Statistics & Actuarial Science at the University of Hong Kong. He is currently a postdoctoral fellow in the Department of Biostatistics at the University of Texas MD Anderson Cancer Center. His research interests are focused on Bayesian adaptive design, Bayesian modeling, clinical trials, as well as causal and high-dimensional inference.

Location 
M3 - Mathematics 3
Room: 3127
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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