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Models of disease behavior in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis is a diffuse parenchymal lung disease of unknown cause. The natural history of disease can vary considerably, making it difficult to predict the clinical trajectory for an individual patient. Accurate prognostication is desirable for clinical management as well as for c...

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Detalles Bibliográficos
Autores principales: Johannson, Kerri A., Ley, Brett, Collard, Harold R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4581470/
https://www.ncbi.nlm.nih.gov/pubmed/26400574
http://dx.doi.org/10.1186/s12916-015-0403-7
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author Johannson, Kerri A.
Ley, Brett
Collard, Harold R.
author_facet Johannson, Kerri A.
Ley, Brett
Collard, Harold R.
author_sort Johannson, Kerri A.
collection PubMed
description Idiopathic pulmonary fibrosis is a diffuse parenchymal lung disease of unknown cause. The natural history of disease can vary considerably, making it difficult to predict the clinical trajectory for an individual patient. Accurate prognostication is desirable for clinical management as well as for cohort enrichment in clinical trials of therapeutics. Clinical and biomarker models of disease behavior have been developed to improve prognostication in idiopathic pulmonary fibrosis, with moderate predictive capabilities. Integrated prediction models that combine both clinical and biomarker variables will improve prognostication for patients and improved cohort enrichment strategies for clinical trials. This goal may be best achieved through collaborative patient registries with prospectively collected biological samples that allow for characterization of disease behavior in idiopathic pulmonary fibrosis.
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spelling pubmed-45814702015-09-25 Models of disease behavior in idiopathic pulmonary fibrosis Johannson, Kerri A. Ley, Brett Collard, Harold R. BMC Med Commentary Idiopathic pulmonary fibrosis is a diffuse parenchymal lung disease of unknown cause. The natural history of disease can vary considerably, making it difficult to predict the clinical trajectory for an individual patient. Accurate prognostication is desirable for clinical management as well as for cohort enrichment in clinical trials of therapeutics. Clinical and biomarker models of disease behavior have been developed to improve prognostication in idiopathic pulmonary fibrosis, with moderate predictive capabilities. Integrated prediction models that combine both clinical and biomarker variables will improve prognostication for patients and improved cohort enrichment strategies for clinical trials. This goal may be best achieved through collaborative patient registries with prospectively collected biological samples that allow for characterization of disease behavior in idiopathic pulmonary fibrosis. BioMed Central 2015-09-24 /pmc/articles/PMC4581470/ /pubmed/26400574 http://dx.doi.org/10.1186/s12916-015-0403-7 Text en © Johannson et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Commentary
Johannson, Kerri A.
Ley, Brett
Collard, Harold R.
Models of disease behavior in idiopathic pulmonary fibrosis
title Models of disease behavior in idiopathic pulmonary fibrosis
title_full Models of disease behavior in idiopathic pulmonary fibrosis
title_fullStr Models of disease behavior in idiopathic pulmonary fibrosis
title_full_unstemmed Models of disease behavior in idiopathic pulmonary fibrosis
title_short Models of disease behavior in idiopathic pulmonary fibrosis
title_sort models of disease behavior in idiopathic pulmonary fibrosis
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4581470/
https://www.ncbi.nlm.nih.gov/pubmed/26400574
http://dx.doi.org/10.1186/s12916-015-0403-7
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