1. Predicting virological decay in patients starting combination antiretroviral therapy
- Author
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Mark Gompels, Martin Fisherg, Jonathan A C Sterne, Rachael A. Hughes, Sophie Jose, Fabiola Martin, John P. Walsh, Jane Anderson, Mark T. Nelson, Adrian Palfreeman, Phillip Hay, Roy Trevelion, David Dunn, Caroline A. Sabin, Clifford Leen, Teresa Hill, Richard Gilson, Margaret A. Johnson, Jonathan Ainsworth, Kate Tilling, Stephen Kegg, Chloe Orkin, and Frank A. Post
- Subjects
0301 basic medicine ,Male ,Time Factors ,Sustained Virologic Response ,CD4 cell count ,HIV Infections ,0302 clinical medicine ,BASE-LINE FACTORS ,Antiretroviral Therapy, Highly Active ,INFECTION ,EQUAL ACCESS ,Immunology and Allergy ,Medicine ,030212 general & internal medicine ,Prospective Studies ,Prospective cohort study ,IN-VIVO ,CD4+ cell count ,Middle Aged ,Viral Load ,Random effects model ,3. Good health ,viral load ,PROSTATE-CANCER ,Infectious Diseases ,Anti-Retroviral Agents ,Cohort ,combination antiretroviral therapy ,Female ,Viral load ,Cohort study ,Cart ,Adult ,medicine.medical_specialty ,CD4(+) cell count ,Epidemiology and Social ,Immunology ,predicted virological suppression ,03 medical and health sciences ,Internal medicine ,Humans ,Protease inhibitor (pharmacology) ,COHORT ,LOAD ,VIRAL DYNAMICS ,Models, Statistical ,business.industry ,030112 virology ,United Kingdom ,treatment switch ,HIV-1 RNA DYNAMICS ,Diagnostic odds ratio ,HIV-1 ,business ,RESPONSES - Abstract
Objective: Model trajectories of viral load measurements from time of starting combination antiretroviral therapy (cART), and use the model to predict whether patients will achieve suppressed viral load (Design: Prospective cohort study including HIV-positive adults (UK Collaborative HIV Cohort Study).Methods: Eligible patients were antiretroviral naive and started cART after 1997. Random effects models were used to estimate viral load trends. Patients were randomly selected to form a validation dataset with those remaining used to fit the model. We evaluated predictions of suppression using indices of diagnostic test performance.Results: Of 9562 eligible patients 6435 were used to fit the model and 3127 for validation. Mean log(10) viral load trajectories declined rapidly during the first 2 weeks post-cART, moderately between 2 weeks and 3 months, and more slowly thereafter. Higher pretreatment viral load predicted steeper declines, whereas older age, white ethnicity, and boosted protease inhibitor/non-nucleoside reverse transcriptase inhibitors based cART-regimen predicted a steeper decline from 3 months onwards. Specificity of predictions and the diagnostic odds ratio substantially improved when predictions were based on viral load measurements up to the 4-month visit compared with the 2 or 3-month visits. Diagnostic performance improved when suppression was defined by two consecutive suppressed viral loads compared with one.Conclusions: Viral load measurements can be used to predict if a patient will be suppressed by 6-month post-cART. Graphical presentations of this information could help clinicians decide the optimum time to switch treatment regimen during the first months of cART. Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.
- Published
- 2016