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

• 成果类型: Article
• 署名作者: Dong, Larry; Moodie, Erica E. M.; Villain, Laura; Thiebaut, Rodolphe
• 署名单位: McGill University; Institut National de la Sante et de la Recherche Medicale (Inserm); Universite de Bordeaux
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/22-AOAS1726
• 发表日期: 2023
• 页码: 2432-2451
• 关键词: recombinant human interleukin-7; quality-adjusted survival; infected patients; treatment rules; propensity score; repeated cycles; il-7; expansion; models; cells

摘要

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.