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Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes
Tuberculosis (TB) is a global health concern. Treatment is prolonged, and patients on anti-TB therapy (ATT) often experience treatment failure for various reasons. There is an urgent need to identify signatures for early detection of failure and initiation of a treatment switch. We investigated how...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347567/ https://www.ncbi.nlm.nih.gov/pubmed/32647325 http://dx.doi.org/10.1038/s42003-020-1087-x |
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author | Sivakumaran, Dhanasekaran Jenum, Synne Vaz, Mario Selvam, Sumithra Ottenhoff, Tom H. M. Haks, Marielle C. Malherbe, Stephanus T. Doherty, T. Mark Ritz, Christian Grewal, Harleen M. S. |
author_facet | Sivakumaran, Dhanasekaran Jenum, Synne Vaz, Mario Selvam, Sumithra Ottenhoff, Tom H. M. Haks, Marielle C. Malherbe, Stephanus T. Doherty, T. Mark Ritz, Christian Grewal, Harleen M. S. |
author_sort | Sivakumaran, Dhanasekaran |
collection | PubMed |
description | Tuberculosis (TB) is a global health concern. Treatment is prolonged, and patients on anti-TB therapy (ATT) often experience treatment failure for various reasons. There is an urgent need to identify signatures for early detection of failure and initiation of a treatment switch. We investigated how gene biomarkers and/or basic patient characteristics could be used to define signatures for treatment outcomes in Indian adult pulmonary-TB patients treated with standard ATT. Using blood samples at baseline, a 12-gene signature combined with information on gender, previously-diagnosed TB, severe thinness, smoking and alcohol consumption was highly predictive of treatment failure at 6 months. Likewise a 4-protein biomarker signature combined with the same patient characteristics was almost as highly predictive of treatment failure. Combining biomarkers and basic patient characteristics may be useful for predicting and hence identification of treatment failure at an early stage of TB therapy. |
format | Online Article Text |
id | pubmed-7347567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73475672020-07-13 Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes Sivakumaran, Dhanasekaran Jenum, Synne Vaz, Mario Selvam, Sumithra Ottenhoff, Tom H. M. Haks, Marielle C. Malherbe, Stephanus T. Doherty, T. Mark Ritz, Christian Grewal, Harleen M. S. Commun Biol Article Tuberculosis (TB) is a global health concern. Treatment is prolonged, and patients on anti-TB therapy (ATT) often experience treatment failure for various reasons. There is an urgent need to identify signatures for early detection of failure and initiation of a treatment switch. We investigated how gene biomarkers and/or basic patient characteristics could be used to define signatures for treatment outcomes in Indian adult pulmonary-TB patients treated with standard ATT. Using blood samples at baseline, a 12-gene signature combined with information on gender, previously-diagnosed TB, severe thinness, smoking and alcohol consumption was highly predictive of treatment failure at 6 months. Likewise a 4-protein biomarker signature combined with the same patient characteristics was almost as highly predictive of treatment failure. Combining biomarkers and basic patient characteristics may be useful for predicting and hence identification of treatment failure at an early stage of TB therapy. Nature Publishing Group UK 2020-07-09 /pmc/articles/PMC7347567/ /pubmed/32647325 http://dx.doi.org/10.1038/s42003-020-1087-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Sivakumaran, Dhanasekaran Jenum, Synne Vaz, Mario Selvam, Sumithra Ottenhoff, Tom H. M. Haks, Marielle C. Malherbe, Stephanus T. Doherty, T. Mark Ritz, Christian Grewal, Harleen M. S. Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title | Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title_full | Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title_fullStr | Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title_full_unstemmed | Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title_short | Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
title_sort | combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347567/ https://www.ncbi.nlm.nih.gov/pubmed/32647325 http://dx.doi.org/10.1038/s42003-020-1087-x |
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