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Activity Number: 493 - Bayesian Model-Based and Rule-Based Dose Escalation Designs in Oncology
Type: Topic Contributed
Date/Time: Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #323724
Title: Alternative Dose Escalation Rules for Dual Agent Designs
Author(s): Charles Liu* and Yannis Jemiai and Sam Hsiao and Hrishikesh Kulkarni
Companies: Cytel Inc. and Cytel Inc. and Cytel, Inc and Cytel Inc.
Keywords:
Abstract:

Dual-agent phase I trials are becoming more common, where the goal is to select one or more maximum tolerated dose (MTD) combinations to take forward. The product of independent beta probabilities dose escalation (PIPE) design has been recently proposed for such combination trials. PIPE provides a flexible framework for dual-agent dose escalation, particularly for novel-novel combinations with relatively few dose levels, where modeling the dose toxicity relationship may not be suitable. The framework offers a number of dose selection strategies that aim to maximize the information about the maximum tolerated contour (MTC), the line partitioning the dose combination space into toxicity risks above and below the target toxicity. However, escalation rules also need to make sense to clinicians: De-escalation when a dose combination is likely too toxic, cohort expansion if a dose combination is likely within an acceptable toxicity range, or escalation when the dose combination is sub-therapeutic. We explored alternative escalation rules for the PIPE design, and evaluated operating characteristics through simulations.


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