Multivariate Kth-Order Markov Models for the Conditional Probability of Toxicity in Phase II Trials

• Activity Number: 408
• Type: Contributed
• Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Laura Fernandes*+ and Jeremy Michael George Taylor and Susan Murray
• Companies: University of Michigan and University of Michigan and University of Michigan
• Keywords: adaptive ; oncology ; clinical trial ; dose escalation

Abstract

Prior to designing a Phase II trial, a Phase I trial often has narrowed interest to two doses that will be moved forward. In addition to getting a preliminary idea of efficacy,an important goal of a phase II trial is to determine dose(s) that have an acceptable toxicity profile over repeated cycles. We model the conditional probability of toxicity during a cycle conditional on not seeing toxicity in any of the previous cycles; a kth-order Markov model where k is the number of previous cycles. Our model allows the conditional probability of toxicity to depend on randomized dose group, cumulative dose from prior cycles, a measure of how consistently a patient responds to the same dose exposure on subsequent cycles as well as individual risk factors influencing the ability to tolerate the treatment regimen. Simulations studying finite sample properties of the model are given. Finally, the approach is demonstrated in a phase II trial studying two dose levels of ifosfamide plus doxorubicin and granulocyte colony-stimulating factor in soft tissue sarcoma patients.