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Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time

BACKGROUND: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. METHODOLOGY/PRINCI...

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Autores principales: Frentz, Dineke, Boucher, Charles A. B., Assel, Matthias, De Luca, Andrea, Fabbiani, Massimiliano, Incardona, Francesca, Libin, Pieter, Manca, Nino, Müller, Viktor, Nualláin, Breanndán Ó., Paredes, Roger, Prosperi, Mattia, Quiros-Roldan, Eugenia, Ruiz, Lidia, Sloot, Peter M. A., Torti, Carlo, Vandamme, Anne-Mieke, Van Laethem, Kristel, Zazzi, Maurizio, van de Vijver, David A. M. C.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901338/
https://www.ncbi.nlm.nih.gov/pubmed/20634893
http://dx.doi.org/10.1371/journal.pone.0011505
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author Frentz, Dineke
Boucher, Charles A. B.
Assel, Matthias
De Luca, Andrea
Fabbiani, Massimiliano
Incardona, Francesca
Libin, Pieter
Manca, Nino
Müller, Viktor
Nualláin, Breanndán Ó.
Paredes, Roger
Prosperi, Mattia
Quiros-Roldan, Eugenia
Ruiz, Lidia
Sloot, Peter M. A.
Torti, Carlo
Vandamme, Anne-Mieke
Van Laethem, Kristel
Zazzi, Maurizio
van de Vijver, David A. M. C.
author_facet Frentz, Dineke
Boucher, Charles A. B.
Assel, Matthias
De Luca, Andrea
Fabbiani, Massimiliano
Incardona, Francesca
Libin, Pieter
Manca, Nino
Müller, Viktor
Nualláin, Breanndán Ó.
Paredes, Roger
Prosperi, Mattia
Quiros-Roldan, Eugenia
Ruiz, Lidia
Sloot, Peter M. A.
Torti, Carlo
Vandamme, Anne-Mieke
Van Laethem, Kristel
Zazzi, Maurizio
van de Vijver, David A. M. C.
author_sort Frentz, Dineke
collection PubMed
description BACKGROUND: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. METHODOLOGY/PRINCIPAL FINDINGS: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8–16) weeks (2152 TCEs), 24 (16–32) weeks (2570 TCEs), and 48 (44–52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5–1.7] for HIVdb, 1.7 [1.5–1.8] for ANRS, and 1.7 [1.9–1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9–2.1 at 24 weeks and 1.9–2.2 at 48 weeks). The Area under the curve of the ROC did not differ between the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48. CONCLUSIONS/SIGNIFICANCE: Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict virological response at 12, 24, and 48 weeks, after change of treatment to the same extent.
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spelling pubmed-29013382010-07-15 Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time Frentz, Dineke Boucher, Charles A. B. Assel, Matthias De Luca, Andrea Fabbiani, Massimiliano Incardona, Francesca Libin, Pieter Manca, Nino Müller, Viktor Nualláin, Breanndán Ó. Paredes, Roger Prosperi, Mattia Quiros-Roldan, Eugenia Ruiz, Lidia Sloot, Peter M. A. Torti, Carlo Vandamme, Anne-Mieke Van Laethem, Kristel Zazzi, Maurizio van de Vijver, David A. M. C. PLoS One Research Article BACKGROUND: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. METHODOLOGY/PRINCIPAL FINDINGS: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8–16) weeks (2152 TCEs), 24 (16–32) weeks (2570 TCEs), and 48 (44–52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5–1.7] for HIVdb, 1.7 [1.5–1.8] for ANRS, and 1.7 [1.9–1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9–2.1 at 24 weeks and 1.9–2.2 at 48 weeks). The Area under the curve of the ROC did not differ between the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48. CONCLUSIONS/SIGNIFICANCE: Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict virological response at 12, 24, and 48 weeks, after change of treatment to the same extent. Public Library of Science 2010-07-09 /pmc/articles/PMC2901338/ /pubmed/20634893 http://dx.doi.org/10.1371/journal.pone.0011505 Text en Frentz et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Frentz, Dineke
Boucher, Charles A. B.
Assel, Matthias
De Luca, Andrea
Fabbiani, Massimiliano
Incardona, Francesca
Libin, Pieter
Manca, Nino
Müller, Viktor
Nualláin, Breanndán Ó.
Paredes, Roger
Prosperi, Mattia
Quiros-Roldan, Eugenia
Ruiz, Lidia
Sloot, Peter M. A.
Torti, Carlo
Vandamme, Anne-Mieke
Van Laethem, Kristel
Zazzi, Maurizio
van de Vijver, David A. M. C.
Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title_full Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title_fullStr Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title_full_unstemmed Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title_short Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time
title_sort comparison of hiv-1 genotypic resistance test interpretation systems in predicting virological outcomes over time
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901338/
https://www.ncbi.nlm.nih.gov/pubmed/20634893
http://dx.doi.org/10.1371/journal.pone.0011505
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