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Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes

BACKGROUND: To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often...

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Autores principales: Rhee, Soo-Yon, Blanco, Jose Luis, Liu, Tommy F, Pere, Iñaki, Kaiser, Rolf, Zazzi, Maurizio, Incardona, Francesca, Towner, William, Gatell, Josep Maria, De Luca, Andrea, Fessel, W Jeffrey, Shafer, Robert W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3439255/
https://www.ncbi.nlm.nih.gov/pubmed/22554313
http://dx.doi.org/10.1186/1742-6405-9-13
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author Rhee, Soo-Yon
Blanco, Jose Luis
Liu, Tommy F
Pere, Iñaki
Kaiser, Rolf
Zazzi, Maurizio
Incardona, Francesca
Towner, William
Gatell, Josep Maria
De Luca, Andrea
Fessel, W Jeffrey
Shafer, Robert W
author_facet Rhee, Soo-Yon
Blanco, Jose Luis
Liu, Tommy F
Pere, Iñaki
Kaiser, Rolf
Zazzi, Maurizio
Incardona, Francesca
Towner, William
Gatell, Josep Maria
De Luca, Andrea
Fessel, W Jeffrey
Shafer, Robert W
author_sort Rhee, Soo-Yon
collection PubMed
description BACKGROUND: To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often differ in their inclusion and virological response criteria making direct comparisons of study results problematic. Moreover, the absence of a standard method for representing the data comprising a TCE makes it difficult to apply uniform criteria in the analysis of published studies of TCEs. RESULTS: To facilitate data sharing for TCE analyses, we developed an XML (Extensible Markup Language) Schema that represents the temporal relationship between plasma HIV-1 RNA levels, CD4 counts and genotypic drug resistance data surrounding an ARV treatment change. To demonstrate the adaptability of the TCE XML Schema to different clinical environments, we collaborate with four clinics to create a public repository of about 1,500 TCEs. Despite the nascent state of this TCE XML Repository, we were able to perform an analysis that generated a novel hypothesis pertaining to the optimal use of second-line therapies in resource-limited settings. We also developed an online program (TCE Finder) for searching the TCE XML Repository and another program (TCE Viewer) for generating a graphical depiction of a TCE from a TCE XML Schema document. CONCLUSIONS: The TCE Suite of applications – the XML Schema, Viewer, Finder, and Repository – addresses several major needs in the analysis of the predictors of virological response to ARV therapy. The TCE XML Schema and Viewer facilitate sharing data comprising a TCE. The TCE Repository, the only publicly available collection of TCEs, and the TCE Finder can be used for testing the predictive value of genotypic resistance interpretation systems and potentially for generating and testing novel hypotheses pertaining to the optimal use of salvage ARV therapy.
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spelling pubmed-34392552012-09-12 Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes Rhee, Soo-Yon Blanco, Jose Luis Liu, Tommy F Pere, Iñaki Kaiser, Rolf Zazzi, Maurizio Incardona, Francesca Towner, William Gatell, Josep Maria De Luca, Andrea Fessel, W Jeffrey Shafer, Robert W AIDS Res Ther Methodology BACKGROUND: To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often differ in their inclusion and virological response criteria making direct comparisons of study results problematic. Moreover, the absence of a standard method for representing the data comprising a TCE makes it difficult to apply uniform criteria in the analysis of published studies of TCEs. RESULTS: To facilitate data sharing for TCE analyses, we developed an XML (Extensible Markup Language) Schema that represents the temporal relationship between plasma HIV-1 RNA levels, CD4 counts and genotypic drug resistance data surrounding an ARV treatment change. To demonstrate the adaptability of the TCE XML Schema to different clinical environments, we collaborate with four clinics to create a public repository of about 1,500 TCEs. Despite the nascent state of this TCE XML Repository, we were able to perform an analysis that generated a novel hypothesis pertaining to the optimal use of second-line therapies in resource-limited settings. We also developed an online program (TCE Finder) for searching the TCE XML Repository and another program (TCE Viewer) for generating a graphical depiction of a TCE from a TCE XML Schema document. CONCLUSIONS: The TCE Suite of applications – the XML Schema, Viewer, Finder, and Repository – addresses several major needs in the analysis of the predictors of virological response to ARV therapy. The TCE XML Schema and Viewer facilitate sharing data comprising a TCE. The TCE Repository, the only publicly available collection of TCEs, and the TCE Finder can be used for testing the predictive value of genotypic resistance interpretation systems and potentially for generating and testing novel hypotheses pertaining to the optimal use of salvage ARV therapy. BioMed Central 2012-05-03 /pmc/articles/PMC3439255/ /pubmed/22554313 http://dx.doi.org/10.1186/1742-6405-9-13 Text en Copyright ©2012 Rhee et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Rhee, Soo-Yon
Blanco, Jose Luis
Liu, Tommy F
Pere, Iñaki
Kaiser, Rolf
Zazzi, Maurizio
Incardona, Francesca
Towner, William
Gatell, Josep Maria
De Luca, Andrea
Fessel, W Jeffrey
Shafer, Robert W
Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title_full Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title_fullStr Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title_full_unstemmed Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title_short Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
title_sort standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3439255/
https://www.ncbi.nlm.nih.gov/pubmed/22554313
http://dx.doi.org/10.1186/1742-6405-9-13
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