1. Early Viral Dynamics Predict HIV Post-Treatment Control After Analytic Treatment Interruption.
- Author
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Magombedze G, Vendrame E, SenGupta D, Geleziunas R, Little S, Smith D, Walker B, Routy JP, Hecht FM, Chun TW, Sneller M, Li JZ, Deeks SG, and Peluso MJ
- Abstract
Background: A key research priority for developing an HIV cure strategy is to define the viral dynamics and biomarkers associated with sustained post-treatment control. The ability to predict the likelihood of sustained post-treatment control or non-control could minimize the time off antiretroviral therapy (ART) for those destined to not control and anticipate longer periods off ART for those destined to control., 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, replicating real-time data collection in a clinical study, and classifying outcomes as either post-treatment control (plasma viremia ≤400 copies/mL at 2 of 3 time points for ≥24 weeks) or non-control., Results: Potential predictors of virologic control were the time to rebound, the rate of initial rebound, and the peak plasma viremia. We found that people destined to be non-controllers could be identified within 3 weeks of rebound (prediction scores: accuracy, 80%; sensitivity, 82%; specificity, 71%)., Conclusions: Given the widespread use of analytic treatment interruption in cure-related trials, these predictors may be useful to increase the safety of analytic treatment interruption through the early identification of people who are unlikely to become post-treatment controllers., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)
- Published
- 2024
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