Phase I Dose-Finding in Cancer Trials Based on a Discrete Time Multistate Model

• Activity Number: 470
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Lin Yang*+ and Nebiyou Bekele and Donald Arthur Berry
• Companies: MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center
• Keywords: Toxicity severity level ; Average toxicity score ; Multistate

Abstract

Toxicities in phase I oncology trials are commonly categorized by grade. Standard phase I dose-finding designs address early toxicity of sufficiently high grade. It is not standard to use information about early lower toxicities though they may predict later higher toxicities. We propose a Bayesian dose-finding design based on a discrete time multistate model that accounts for two important factors: the toxicity severity levels and non-suspension between accrual cohorts. We estimate an Average Toxicity Score (ATS) based on the discrete time multistate transition probabilities. A Bayesian isotonic transformation is applied to induce an order-restricted posterior ATS. The operating characteristics are compared with those of a similar design by Bekele, Li and Ji (2009. We describe settings in which, under comparable power, the proposed design significantly shortens trial duration.