Early Viral Dynamics Predict Human Immunodeficiency Virus Posttreatment Control After Analytic Treatment Interruption.

ABSTRACT:

Background

A key research priority for developing a human immunodeficiency virus (HIV) cure strategy is to define the viral dynamics and biomarkers associated with sustained posttreatment control. The ability to predict the likelihood of sustained posttreatment control or noncontrol could minimize the time off antiretroviral therapy (ART) for those destined to be controllers and anticipate longer periods off ART for those destined to be controllers.

Methods

Mathematical modeling and machine learning were used to characterize virologic predictors of long-term virologic control, using viral kinetics data from several studies in which participants interrupted ART. Predictors of post-ART outcomes were characterized using data accumulated from the time of treatment interruption,

SUBMITTER: Magombedze G 

PROVIDER: S-EPMC11841646 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature