1. Optimizing Treatment for Human Immunodeficiency Virus to Improve Clinical Outcomes Using Precision Medicine.
- Author
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Jetsupphasuk M, Hudgens MG, Lu H, Cole SR, Edwards JK, Adimora AA, Althoff KN, Silverberg MJ, Rebeiro PF, Lima VD, Marconi VC, Sterling TR, Horberg MA, Gill MJ, Kitahata MM, Moore RD, Lang R, Gebo K, Rabkin C, and Eron JJ
- Subjects
- Humans, HIV, Reverse Transcriptase Inhibitors therapeutic use, Precision Medicine, HIV Infections drug therapy, Acquired Immunodeficiency Syndrome drug therapy
- Abstract
In first-line antiretroviral therapy (ART) for human immunodeficiency virus (HIV) treatment, some subgroups of patients may respond better to an efavirenz-based regimen than an integrase strand transfer inhibitor (InSTI)-based regimen, or vice versa, due to patient characteristics modifying treatment effects. Using data based on nearly 16,000 patients from the North American AIDS Cohort Collaboration on Research and Design from 2009-2016, statistical methods for precision medicine were employed to estimate an optimal treatment rule that minimizes the 5-year risk of the composite outcome of acquired immune deficiency syndrome (AIDS)-defining illnesses, serious non-AIDS events, and all-cause mortality. The treatment rules considered were functions that recommend either an efavirenz- or InSTI-based regimen conditional on baseline patient characteristics such as demographic information, laboratory results, and health history. The estimated 5-year risk under the estimated optimal treatment rule was 10.0% (95% confidence interval (CI): 8.6, 11.3), corresponding to an absolute risk reduction of 2.3% (95% CI: 0.9, 3.8) when compared with recommending an efavirenz-based regimen for all patients and 2.6% (95% CI: 1.0, 4.2) when compared with recommending an InSTI-based regimen for all. Tailoring ART to individual patient characteristics may reduce 5-year risk of the composite outcome compared with assigning all patients the same drug regimen., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2023. This work is written by (a) US Government employee(s) and is in the public domain in the US.)
- Published
- 2023
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