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Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities

Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation, the severity of which is assessed using forced expiratory volume in 1 sec (FEV(1), % predicted). Cohort studies have confirmed that COPD patients with similar levels of airflow limitation showed marked he...

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Autores principales: Burgel, Pierre-Régis, Paillasseur, Jean-Louis, Roche, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3934315/
https://www.ncbi.nlm.nih.gov/pubmed/24683548
http://dx.doi.org/10.1155/2014/420134
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author Burgel, Pierre-Régis
Paillasseur, Jean-Louis
Roche, Nicolas
author_facet Burgel, Pierre-Régis
Paillasseur, Jean-Louis
Roche, Nicolas
author_sort Burgel, Pierre-Régis
collection PubMed
description Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation, the severity of which is assessed using forced expiratory volume in 1 sec (FEV(1), % predicted). Cohort studies have confirmed that COPD patients with similar levels of airflow limitation showed marked heterogeneity in clinical manifestations and outcomes. Chronic coexisting diseases, also called comorbidities, are highly prevalent in COPD patients and likely contribute to this heterogeneity. In recent years, investigators have used innovative statistical methods (e.g., cluster analyses) to examine the hypothesis that subgroups of COPD patients sharing clinically relevant characteristics (phenotypes) can be identified. The objectives of the present paper are to review recent studies that have used cluster analyses for defining phenotypes in observational cohorts of COPD patients. Strengths and weaknesses of these statistical approaches are briefly described. Description of the phenotypes that were reasonably reproducible across studies and received prospective validation in at least one study is provided, with a special focus on differences in age and comorbidities (including cardiovascular diseases). Finally, gaps in current knowledge are described, leading to proposals for future studies.
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spelling pubmed-39343152014-03-30 Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities Burgel, Pierre-Régis Paillasseur, Jean-Louis Roche, Nicolas Biomed Res Int Review Article Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation, the severity of which is assessed using forced expiratory volume in 1 sec (FEV(1), % predicted). Cohort studies have confirmed that COPD patients with similar levels of airflow limitation showed marked heterogeneity in clinical manifestations and outcomes. Chronic coexisting diseases, also called comorbidities, are highly prevalent in COPD patients and likely contribute to this heterogeneity. In recent years, investigators have used innovative statistical methods (e.g., cluster analyses) to examine the hypothesis that subgroups of COPD patients sharing clinically relevant characteristics (phenotypes) can be identified. The objectives of the present paper are to review recent studies that have used cluster analyses for defining phenotypes in observational cohorts of COPD patients. Strengths and weaknesses of these statistical approaches are briefly described. Description of the phenotypes that were reasonably reproducible across studies and received prospective validation in at least one study is provided, with a special focus on differences in age and comorbidities (including cardiovascular diseases). Finally, gaps in current knowledge are described, leading to proposals for future studies. Hindawi Publishing Corporation 2014 2014-02-10 /pmc/articles/PMC3934315/ /pubmed/24683548 http://dx.doi.org/10.1155/2014/420134 Text en Copyright © 2014 Pierre-Régis Burgel et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Burgel, Pierre-Régis
Paillasseur, Jean-Louis
Roche, Nicolas
Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title_full Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title_fullStr Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title_full_unstemmed Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title_short Identification of Clinical Phenotypes Using Cluster Analyses in COPD Patients with Multiple Comorbidities
title_sort identification of clinical phenotypes using cluster analyses in copd patients with multiple comorbidities
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3934315/
https://www.ncbi.nlm.nih.gov/pubmed/24683548
http://dx.doi.org/10.1155/2014/420134
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