Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

ABSTRACT: Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification

SUBMITTER: Hager R 

PROVIDER: S-EPMC6240504 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature