EVALUATING THE USE OF GENERALIZED DYNAMIC WEIGHTED ORDINARY LEAST SQUARES FOR INDIVIDUALIZED HIV TREATMENT STRATEGIES

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/mu L) while preventing the administration of unnecessary injections.

Automated summary

A dynamic treatment regime is a statistical approach in precision medicine that aims to optimize patient outcomes through individualized treatment. This study applies the generalized dynamic weighted ordinary least squares method to longitudinal data to estimate an optimal individualized treatment rule (ITR).