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Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm
BACKGROUND: In resource-limited settings, where resistance testing is unavailable, confirmatory testing for patients with high viral loads (VL) delays antiretroviral therapy (ART) switches for persons with resistance. We developed a risk score algorithm to predict need for ART change by identifying...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4906700/ https://www.ncbi.nlm.nih.gov/pubmed/27296625 http://dx.doi.org/10.1186/s12879-016-1611-2 |
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author | Rutstein, Sarah E. Hosseinipour, Mina C. Weinberger, Morris Wheeler, Stephanie B. Biddle, Andrea K. Wallis, Carole L. Balakrishnan, Pachamuthu Mellors, John W. Morgado, Mariza Saravanan, Shanmugam Tripathy, Srikanth Vardhanabhuti, Saran Eron, Joseph J. Miller, William C. |
author_facet | Rutstein, Sarah E. Hosseinipour, Mina C. Weinberger, Morris Wheeler, Stephanie B. Biddle, Andrea K. Wallis, Carole L. Balakrishnan, Pachamuthu Mellors, John W. Morgado, Mariza Saravanan, Shanmugam Tripathy, Srikanth Vardhanabhuti, Saran Eron, Joseph J. Miller, William C. |
author_sort | Rutstein, Sarah E. |
collection | PubMed |
description | BACKGROUND: In resource-limited settings, where resistance testing is unavailable, confirmatory testing for patients with high viral loads (VL) delays antiretroviral therapy (ART) switches for persons with resistance. We developed a risk score algorithm to predict need for ART change by identifying resistance among persons with persistently elevated VL. METHODS: We analyzed data from a Phase IV open-label trial. Using logistic regression, we identified demographic and clinical characteristics predictive of need for ART change among participants with VLs ≥1000 copies/ml, and assigned model-derived scores to predictors. We designed three models, including only variables accessible in resource-limited settings. RESULTS: Among 290 participants with at least one VL ≥1000 copies/ml, 51 % (148/290) resuppressed and did not have resistance testing; among those who did not resuppress and had resistance testing, 47 % (67/142) did not have resistance and 53 % (75/142) had resistance (ART change needed for 25.9 % (75/290)). Need for ART change was directly associated with higher baseline VL and higher VL at time of elevated measure, and inversely associated with treatment duration. Other predictors included body mass index and adherence. Area under receiver operating characteristic curves ranged from 0.794 to 0.817. At a risk score ≥9, sensitivity was 14.7–28.0 % and specificity was 96.7–98.6 %. CONCLUSIONS: Our model performed reasonably well and may be a tool to quickly transition persons in need of ART change to more effective regimens when resistance testing is unavailable. Use of this algorithm may result in public health benefits and health system savings through reduced transmissions of resistant virus and costs on laboratory investigations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-016-1611-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4906700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49067002016-06-15 Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm Rutstein, Sarah E. Hosseinipour, Mina C. Weinberger, Morris Wheeler, Stephanie B. Biddle, Andrea K. Wallis, Carole L. Balakrishnan, Pachamuthu Mellors, John W. Morgado, Mariza Saravanan, Shanmugam Tripathy, Srikanth Vardhanabhuti, Saran Eron, Joseph J. Miller, William C. BMC Infect Dis Research Article BACKGROUND: In resource-limited settings, where resistance testing is unavailable, confirmatory testing for patients with high viral loads (VL) delays antiretroviral therapy (ART) switches for persons with resistance. We developed a risk score algorithm to predict need for ART change by identifying resistance among persons with persistently elevated VL. METHODS: We analyzed data from a Phase IV open-label trial. Using logistic regression, we identified demographic and clinical characteristics predictive of need for ART change among participants with VLs ≥1000 copies/ml, and assigned model-derived scores to predictors. We designed three models, including only variables accessible in resource-limited settings. RESULTS: Among 290 participants with at least one VL ≥1000 copies/ml, 51 % (148/290) resuppressed and did not have resistance testing; among those who did not resuppress and had resistance testing, 47 % (67/142) did not have resistance and 53 % (75/142) had resistance (ART change needed for 25.9 % (75/290)). Need for ART change was directly associated with higher baseline VL and higher VL at time of elevated measure, and inversely associated with treatment duration. Other predictors included body mass index and adherence. Area under receiver operating characteristic curves ranged from 0.794 to 0.817. At a risk score ≥9, sensitivity was 14.7–28.0 % and specificity was 96.7–98.6 %. CONCLUSIONS: Our model performed reasonably well and may be a tool to quickly transition persons in need of ART change to more effective regimens when resistance testing is unavailable. Use of this algorithm may result in public health benefits and health system savings through reduced transmissions of resistant virus and costs on laboratory investigations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-016-1611-2) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-13 /pmc/articles/PMC4906700/ /pubmed/27296625 http://dx.doi.org/10.1186/s12879-016-1611-2 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Rutstein, Sarah E. Hosseinipour, Mina C. Weinberger, Morris Wheeler, Stephanie B. Biddle, Andrea K. Wallis, Carole L. Balakrishnan, Pachamuthu Mellors, John W. Morgado, Mariza Saravanan, Shanmugam Tripathy, Srikanth Vardhanabhuti, Saran Eron, Joseph J. Miller, William C. Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title | Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title_full | Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title_fullStr | Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title_full_unstemmed | Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title_short | Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
title_sort | predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4906700/ https://www.ncbi.nlm.nih.gov/pubmed/27296625 http://dx.doi.org/10.1186/s12879-016-1611-2 |
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