Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis

Stephen I. Rennard, Nicholas Locantore, Bruno Delafont, Ruth Tal-Singer, Edwin K. Silverman, Jørgen Vestbo, Bruce E. Miller, Per Bakke, Bartolomé Celli, Peter M.A. Calverley, Harvey Coxson, Courtney Crim, Lisa D. Edwards, David A. Lomas, William Macnee, Emiel F.M. Wouters, Julie C. Yates, Ignacio Coca, Alvar Agustí

Research output: Contribution to journalArticle

67 Citations (Scopus)

Abstract

Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. Objectives: To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Methods: Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Measurements and Main Results: Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Conclusions: Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Original languageEnglish (US)
Pages (from-to)303-312
Number of pages10
JournalAnnals of the American Thoracic Society
Volume12
Issue number3
DOIs
StatePublished - Mar 1 2015

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Chronic Obstructive Pulmonary Disease
Cluster Analysis
Biomarkers
Emphysema
Hospitalization
Inflammation
Health Status
Statistical Factor Analysis
Comorbidity
Mortality
Population

Keywords

  • Chronic obstructive pulmonary disease
  • Cluster analysis
  • Longitudinal outcomes

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Cite this

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis. / Rennard, Stephen I.; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K.; Vestbo, Jørgen; Miller, Bruce E.; Bakke, Per; Celli, Bartolomé; Calverley, Peter M.A.; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D.; Lomas, David A.; Macnee, William; Wouters, Emiel F.M.; Yates, Julie C.; Coca, Ignacio; Agustí, Alvar.

In: Annals of the American Thoracic Society, Vol. 12, No. 3, 01.03.2015, p. 303-312.

Research output: Contribution to journalArticle

Rennard, SI, Locantore, N, Delafont, B, Tal-Singer, R, Silverman, EK, Vestbo, J, Miller, BE, Bakke, P, Celli, B, Calverley, PMA, Coxson, H, Crim, C, Edwards, LD, Lomas, DA, Macnee, W, Wouters, EFM, Yates, JC, Coca, I & Agustí, A 2015, 'Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis', Annals of the American Thoracic Society, vol. 12, no. 3, pp. 303-312. https://doi.org/10.1513/AnnalsATS.201403-125OC
Rennard, Stephen I. ; Locantore, Nicholas ; Delafont, Bruno ; Tal-Singer, Ruth ; Silverman, Edwin K. ; Vestbo, Jørgen ; Miller, Bruce E. ; Bakke, Per ; Celli, Bartolomé ; Calverley, Peter M.A. ; Coxson, Harvey ; Crim, Courtney ; Edwards, Lisa D. ; Lomas, David A. ; Macnee, William ; Wouters, Emiel F.M. ; Yates, Julie C. ; Coca, Ignacio ; Agustí, Alvar. / Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis. In: Annals of the American Thoracic Society. 2015 ; Vol. 12, No. 3. pp. 303-312.
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abstract = "Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. Objectives: To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Methods: Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Measurements and Main Results: Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Conclusions: Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.",
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T1 - Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis

AU - Rennard, Stephen I.

AU - Locantore, Nicholas

AU - Delafont, Bruno

AU - Tal-Singer, Ruth

AU - Silverman, Edwin K.

AU - Vestbo, Jørgen

AU - Miller, Bruce E.

AU - Bakke, Per

AU - Celli, Bartolomé

AU - Calverley, Peter M.A.

AU - Coxson, Harvey

AU - Crim, Courtney

AU - Edwards, Lisa D.

AU - Lomas, David A.

AU - Macnee, William

AU - Wouters, Emiel F.M.

AU - Yates, Julie C.

AU - Coca, Ignacio

AU - Agustí, Alvar

PY - 2015/3/1

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N2 - Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. Objectives: To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Methods: Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Measurements and Main Results: Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Conclusions: Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

AB - Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. Objectives: To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Methods: Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Measurements and Main Results: Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Conclusions: Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

KW - Chronic obstructive pulmonary disease

KW - Cluster analysis

KW - Longitudinal outcomes

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