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COPD subphenotypes in a population-based survey by factor and cluster analysis

Niki Fens, Annelot G.J. van Rossum, Pieter Zanen, Bram van Ginneken, Rob J. van Klaveren, Aeilko H. Zwinderman, Peter J. Sterk
European Respiratory Journal 2012 40: P553; DOI:
Niki Fens
1Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Netherlands
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Annelot G.J. van Rossum
1Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Netherlands
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Pieter Zanen
2Respiratory Medicine, University Medical Center, Utrecht, Netherlands
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Bram van Ginneken
3Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
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Rob J. van Klaveren
4Respiratory Medicine, Erasmus Medical Center, University of Rotterdam, Netherlands
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Aeilko H. Zwinderman
5Clinical Epidemiology and Biostatistics, Academic Medical Centre, University of Amsterdam, Netherlands
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Peter J. Sterk
1Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Netherlands
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Abstract

Background Classification of COPD is currently based on symptoms, airways obstruction and exacerbations. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers.

Methods Adults (50-75 yrs) with ≥15 packyears derived from a random population-based survey underwent pulmonary function testing, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor analysis followed by K-means cluster analysis was performed on subjects fulfilling the GOLD criteria for COPD with post-BD FEV1/FVC<0.70.

Results 157 of 300 subjects fulfilled the criteria for COPD. Factor analysis revealed 12 factors representing different domains of COPD including lung function, radiologic features, exhaled breath metabolomics, symptoms and quality of life. Four clusters were identified: cluster 1 (n=35; 22%): mild airways obstruction and no emphysema; cluster 2 (n=48; 31%): severe airways obstruction with emphysema and low diffusion capacity, chronic bronchitis, low quality of life and a distinct breath profile; cluster 3 (n=60; 38%): mild COPD with a close to normal lung function, but with radiologic signs of emphysema and a distinct breath profile; cluster 4 (n=14; 9%): highly symptomatic males with dyspnea and low quality of life with moderately impaired lung function.

Conclusions This unbiased taxonomy for COPD confirms and extends clusters found in previous studies and allows better phenotyping of COPD.

  • Breath test
  • COPD - diagnosis
  • Biomarkers
  • © 2012 ERS
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COPD subphenotypes in a population-based survey by factor and cluster analysis
Niki Fens, Annelot G.J. van Rossum, Pieter Zanen, Bram van Ginneken, Rob J. van Klaveren, Aeilko H. Zwinderman, Peter J. Sterk
European Respiratory Journal Sep 2012, 40 (Suppl 56) P553;

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COPD subphenotypes in a population-based survey by factor and cluster analysis
Niki Fens, Annelot G.J. van Rossum, Pieter Zanen, Bram van Ginneken, Rob J. van Klaveren, Aeilko H. Zwinderman, Peter J. Sterk
European Respiratory Journal Sep 2012, 40 (Suppl 56) P553;
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