Abstract Details
Activity Number:
|
226
|
Type:
|
Topic Contributed
|
Date/Time:
|
Monday, August 5, 2013 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Biometrics Section
|
Abstract - #309674 |
Title:
|
Combination Dose-Finding for Targeted Agents: A Bayesian Case Study in Oncology
|
Author(s):
|
Suman Sen*+ and Meredith Goldwasser and Stuart Bailey
|
Companies:
|
Novartis Pharmaceuticals Corp and Novartis Pharmaceuticals Corp and Novartis Pharma AG
|
Keywords:
|
bayesian models ;
dose-escalation ;
oncology ;
prior ;
combination therapy
|
Abstract:
|
Within oncology there has been a paradigm shift moving from single agent therapies to combinations of drugs. In this setting there is no longer one maximum tolerated dose (MTD) but a range of dose pairs. A Bayesian model-based framework for phase I combination trials is presented in the context of a real case study. Critical aspects of the model and prior specifications are presented, along with the need to evaluate the uncertainty of estimated toxicity rates, which allows for risk monitoring. In addition, the importance of understanding the impact of combining two or more compounds on patient safety, and to define the toxicity profile interaction is highlighted. On-study discussions around dose escalation and determination of MTD are discussed as well, which underlines the importance of good statistical guidance and clinical/scientific expertise.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.