Estimating individualized treatment rules by optimizing the adjusted probability of a longer survival

Shixiao Zhang Co-Author
Alexion Pharma Canada Corp.
 
Michael LeBlanc Co-Author
Fred Hutchinson Cancer Research Center
 
Yingqi Zhao Speaker
Fred Hutchinson Cancer Research Center
 
Tuesday, Aug 8: 9:00 AM - 9:25 AM
Invited Paper Session 
Metro Toronto Convention Centre 
Individualized treatment rules (ITRs) inform tailored treatment decisions based on the patient's information, where the goal is to optimize clinical benefit for the population. When the clinical outcome of interest is survival time, most of current approaches typically aim to maximize the expected time of survival. We propose a new criterion for constructing ITRs that optimize the clinical benefit with survival outcomes, termed as the adjusted probability of a longer survival. This objective captures the likelihood of living longer with being on treatment, compared to the alternative, which provides a straightforward interpretation to communicate with clinicians and patients. We develop a new method to construct the optimal ITR by maximizing a nonparametric estimator of the adjusted probability of a longer survival for a decision rule. Simulation studies demonstrate the reliability of the proposed method across a range of different scenarios. We further perform data analysis using data collected from a randomized Phase III clinical trial (SWOG S0819).