Evaluating the use of generalized dynamic weighted ordinary least squares for individualized HIV treatment strategies

Abstract

A dynamic treatment regimes (DTR) represents a statistical paradigm in precision medicine which aims to optimize patient outcomes by individualizing treatments. At its simplest, a DTR may require only a single decision to be made; this special case is called an individualized treatment rule (ITR) and is often used to maximize short-term rewards. Generalized dynamic weighted ordinary least squares (G-dWOLS), a DTR estimation method that offers theoretical advantages such as double robustness of parameter estimators in the decision rules, has been recently extended to accommodate categorical treatments. In this work G-dWOLS is applied to longitudinal data to estimate an optimal ITR. This novel method is demonstrated in simulations and is then applied to a population affected by HIV, whereby an ITR for the administration of Interleukin 7 (IL-7) is devised to maximize the duration where the CD4 load is above a healthy threshold (500 cells/μL) while preventing the administration of unnecessary injections.