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Thorax. 2017 Nov;72(11):998-1006. doi: 10.1136/thoraxjnl-2016-209846. Epub 2017 Jun 21.

Do COPD subtypes really exist? COPD heterogeneity and clustering in 10 independent cohorts.

Author information

1
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
2
Division of General Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, USA.
3
ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.
4
Universitat Pompeu Fabra (UPF), Barcelona, Spain.
5
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
6
COPD Program, Lovelace Respiratory Research Institute, Albuquerque, New Mexico, USA.
7
Center for Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA.
8
Department of Medicine, National Jewish Health, Denver, Colorado, USA.
9
Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
10
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
11
Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland.
12
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
13
Vesalius Research Center (VRC), VIB, Leuven, Belgium.
14
Laboratory for Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium.
15
Respiratory Division, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium.
16
Pulmonary and Critical Care Division, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
17
Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.
18
Clinical Discovery Unit, AstraZeneca, Cambridge, UK.
19
Department of Computer Science, Northeastern University, Boston, Massachusetts, USA.
20
Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
21
Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
22
Respiratory Institute, Hospital Clinic, University of Barcelona, IDIBAPS and CIBERES, Barcelona, Spain.

Abstract

BACKGROUND:

COPD is a heterogeneous disease, but there is little consensus on specific definitions for COPD subtypes. Unsupervised clustering offers the promise of 'unbiased' data-driven assessment of COPD heterogeneity. Multiple groups have identified COPD subtypes using cluster analysis, but there has been no systematic assessment of the reproducibility of these subtypes.

OBJECTIVE:

We performed clustering analyses across 10 cohorts in North America and Europe in order to assess the reproducibility of (1) correlation patterns of key COPD-related clinical characteristics and (2) clustering results.

METHODS:

We studied 17 146 individuals with COPD using identical methods and common COPD-related characteristics across cohorts (FEV1, FEV1/FVC, FVC, body mass index, Modified Medical Research Council score, asthma and cardiovascular comorbid disease). Correlation patterns between these clinical characteristics were assessed by principal components analysis (PCA). Cluster analysis was performed using k-medoids and hierarchical clustering, and concordance of clustering solutions was quantified with normalised mutual information (NMI), a metric that ranges from 0 to 1 with higher values indicating greater concordance.

RESULTS:

The reproducibility of COPD clustering subtypes across studies was modest (median NMI range 0.17-0.43). For methods that excluded individuals that did not clearly belong to any cluster, agreement was better but still suboptimal (median NMI range 0.32-0.60). Continuous representations of COPD clinical characteristics derived from PCA were much more consistent across studies.

CONCLUSIONS:

Identical clustering analyses across multiple COPD cohorts showed modest reproducibility. COPD heterogeneity is better characterised by continuous disease traits coexisting in varying degrees within the same individual, rather than by mutually exclusive COPD subtypes.

KEYWORDS:

COPD epidemiology

PMID:
28637835
PMCID:
PMC6013053
[Available on 2018-11-01]
DOI:
10.1136/thoraxjnl-2016-209846
[Indexed for MEDLINE]

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