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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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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. |
format | Online Article Text |
id | pubmed-3439255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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