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A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data
The combined therapy of pegylated interferon (IFN) plus ribavirin (RBV) has been for a long time the standard treatment for patients infected with hepatitis C virus (HCV). In the case of genotype 1, only 38%–48% of patients have a positive response to the combined treatment. In previous studies, vir...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4344356/ https://www.ncbi.nlm.nih.gov/pubmed/25780333 http://dx.doi.org/10.4137/EBO.S20853 |
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author | Amadoz, Alicia González-Candelas, Fernando |
author_facet | Amadoz, Alicia González-Candelas, Fernando |
author_sort | Amadoz, Alicia |
collection | PubMed |
description | The combined therapy of pegylated interferon (IFN) plus ribavirin (RBV) has been for a long time the standard treatment for patients infected with hepatitis C virus (HCV). In the case of genotype 1, only 38%–48% of patients have a positive response to the combined treatment. In previous studies, viral genetic information has been occasionally included as a predictor. Here, we consider viral genetic variation in addition to 11 clinical and 19 viral populations and evolutionary parameters to identify candidate baseline prognostic factors that could be involved in the treatment outcome. We obtained potential prognostic models for HCV subtypes la and lb in combination as well as separately. We also found that viral genetic information is relevant for the combined treatment assessment of patients, as the potential prognostic model of joint subtypes includes 9 viral-related variables out of 11. Our proposed methodology fully characterizes viral genetic information and finds a combination of positions that modulate inter-patient variability. |
format | Online Article Text |
id | pubmed-4344356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-43443562015-03-16 A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data Amadoz, Alicia González-Candelas, Fernando Evol Bioinform Online Methodology The combined therapy of pegylated interferon (IFN) plus ribavirin (RBV) has been for a long time the standard treatment for patients infected with hepatitis C virus (HCV). In the case of genotype 1, only 38%–48% of patients have a positive response to the combined treatment. In previous studies, viral genetic information has been occasionally included as a predictor. Here, we consider viral genetic variation in addition to 11 clinical and 19 viral populations and evolutionary parameters to identify candidate baseline prognostic factors that could be involved in the treatment outcome. We obtained potential prognostic models for HCV subtypes la and lb in combination as well as separately. We also found that viral genetic information is relevant for the combined treatment assessment of patients, as the potential prognostic model of joint subtypes includes 9 viral-related variables out of 11. Our proposed methodology fully characterizes viral genetic information and finds a combination of positions that modulate inter-patient variability. Libertas Academica 2015-02-23 /pmc/articles/PMC4344356/ /pubmed/25780333 http://dx.doi.org/10.4137/EBO.S20853 Text en © 2015 the author(s), publisher and licensee Libertas Academica Ltd. This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License. |
spellingShingle | Methodology Amadoz, Alicia González-Candelas, Fernando A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title | A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title_full | A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title_fullStr | A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title_full_unstemmed | A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title_short | A Novel Approach to Identify Candidate Prognostic Factors for Hepatitis C Treatment Response Integrating Clinical and Viral Genetic Data |
title_sort | novel approach to identify candidate prognostic factors for hepatitis c treatment response integrating clinical and viral genetic data |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4344356/ https://www.ncbi.nlm.nih.gov/pubmed/25780333 http://dx.doi.org/10.4137/EBO.S20853 |
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