Literature DB >> 28637835

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

Peter J Castaldi1,2, Marta Benet3,4,5, Hans Petersen6, Nicholas Rafaels7, James Finigan8, Matteo Paoletti9, H Marike Boezen10, Judith M Vonk10, Russell Bowler8, Massimo Pistolesi9, Milo A Puhan11, Josep Anto3,5,4,12, Els Wauters13,14,15, Diether Lambrechts13,14, Wim Janssens15, Francesca Bigazzi9, Gianna Camiciottoli9, Michael H Cho1,16, Craig P Hersh1,16, Kathleen Barnes7, Stephen Rennard17,18, Meher Preethi Boorgula7, Jennifer Dy19, Nadia N Hansel20,21, James D Crapo8, Yohannes Tesfaigzi6, Alvar Agusti22, Edwin K Silverman1,17, Judith Garcia-Aymerich3,5,4.   

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. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  COPD epidemiology

Mesh:

Year:  2017        PMID: 28637835      PMCID: PMC6013053          DOI: 10.1136/thoraxjnl-2016-209846

Source DB:  PubMed          Journal:  Thorax        ISSN: 0040-6376            Impact factor:   9.139


  23 in total

1.  Characteristics of patients admitted for the first time for COPD exacerbation.

Authors:  Eva Balcells; Josep M Antó; Joaquim Gea; Federico P Gómez; Esther Rodríguez; Alicia Marin; Antoni Ferrer; Jordi de Batlle; Eva Farrero; Marta Benet; Mauricio Orozco-Levi; Jaume Ferrer; Alvar G Agustí; Juan B Gáldiz; José Belda; Judith Garcia-Aymerich
Journal:  Respir Med       Date:  2009-05-08       Impact factor: 3.415

2.  Identification and prospective validation of clinically relevant chronic obstructive pulmonary disease (COPD) subtypes.

Authors:  Judith Garcia-Aymerich; Federico P Gómez; Marta Benet; Eva Farrero; Xavier Basagaña; Àngel Gayete; Carles Paré; Xavier Freixa; Jaume Ferrer; Antoni Ferrer; Josep Roca; Juan B Gáldiz; Jaume Sauleda; Eduard Monsó; Joaquim Gea; Joan A Barberà; Àlvar Agustí; Josep M Antó
Journal:  Thorax       Date:  2010-12-21       Impact factor: 9.139

3.  Cohort Profile: LifeLines, a three-generation cohort study and biobank.

Authors:  Salome Scholtens; Nynke Smidt; Morris A Swertz; Stephan J L Bakker; Aafje Dotinga; Judith M Vonk; Freerk van Dijk; Sander K R van Zon; Cisca Wijmenga; Bruce H R Wolffenbuttel; Ronald P Stolk
Journal:  Int J Epidemiol       Date:  2014-12-14       Impact factor: 7.196

4.  Characteristics and outcomes of chronic obstructive pulmonary disease in never smokers in Denmark: a prospective population study.

Authors:  Mette Thomsen; Børge G Nordestgaard; Jørgen Vestbo; Peter Lange
Journal:  Lancet Respir Med       Date:  2013-07-29       Impact factor: 30.700

5.  Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation.

Authors:  Michael H Cho; George R Washko; Thomas J Hoffmann; Gerard J Criner; Eric A Hoffman; Fernando J Martinez; Nan Laird; John J Reilly; Edwin K Silverman
Journal:  Respir Res       Date:  2010-03-16

6.  A multivariate analysis of the risk in chronic obstructive lung disease (COLD).

Authors:  S Spinaci; M Bugiani; W Arossa; C Bucca; G Rolla
Journal:  J Chronic Dis       Date:  1985

7.  Explorative data analysis techniques and unsupervised clustering methods to support clinical assessment of Chronic Obstructive Pulmonary Disease (COPD) phenotypes.

Authors:  Matteo Paoletti; Gianna Camiciottoli; Eleonora Meoni; Francesca Bigazzi; Lucia Cestelli; Massimo Pistolesi; Carlo Marchesi
Journal:  J Biomed Inform       Date:  2009-06-06       Impact factor: 6.317

8.  Identification of a predominant COPD phenotype in clinical practice.

Authors:  Massimo Pistolesi; Gianna Camiciottoli; Matteo Paoletti; Cecilia Marmai; Federico Lavorini; Eleonora Meoni; Carlo Marchesi; Carlo Giuntini
Journal:  Respir Med       Date:  2008-01-08       Impact factor: 3.415

Review 9.  Identification of clinical phenotypes using cluster analyses in COPD patients with multiple comorbidities.

Authors:  Pierre-Régis Burgel; Jean-Louis Paillasseur; Nicolas Roche
Journal:  Biomed Res Int       Date:  2014-02-10       Impact factor: 3.411

10.  Treatable traits: toward precision medicine of chronic airway diseases.

Authors:  Alvar Agusti; Elisabeth Bel; Mike Thomas; Claus Vogelmeier; Guy Brusselle; Stephen Holgate; Marc Humbert; Paul Jones; Peter G Gibson; Jørgen Vestbo; Richard Beasley; Ian D Pavord
Journal:  Eur Respir J       Date:  2016-02       Impact factor: 16.671

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Review 2.  Phenotypic Subtypes of OSA: A Challenge and Opportunity for Precision Medicine.

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Journal:  Chest       Date:  2019-09-17       Impact factor: 9.410

3.  Lobar Emphysema Distribution Is Associated With 5-Year Radiological Disease Progression.

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4.  Turning subtypes into disease axes to improve prediction of COPD progression.

Authors:  Junxiang Chen; Michael Cho; Edwin K Silverman; John E Hokanson; Greg L Kinney; James D Crapo; Stephen Rennard; Jennifer Dy; Peter Castaldi
Journal:  Thorax       Date:  2019-06-12       Impact factor: 9.139

Review 5.  Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

Authors:  Peter J Castaldi; Adel Boueiz; Jeong Yun; Raul San Jose Estepar; James C Ross; George Washko; Michael H Cho; Craig P Hersh; Gregory L Kinney; Kendra A Young; Elizabeth A Regan; David A Lynch; Gerald J Criner; Jennifer G Dy; Stephen I Rennard; Richard Casaburi; Barry J Make; James Crapo; Edwin K Silverman; John E Hokanson
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6.  Early Endotyping: A Chance for Intervention in Chronic Obstructive Pulmonary Disease.

Authors:  Hans Petersen; Rodrigo Vazquez Guillamet; Paula Meek; Akshay Sood; Yohannes Tesfaigzi
Journal:  Am J Respir Cell Mol Biol       Date:  2018-07       Impact factor: 6.914

7.  A functional macrophage migration inhibitory factor promoter polymorphism is associated with reduced diffusing capacity.

Authors:  C Zhang; C Ramsey; A Berical; L Yu; L Leng; K A McGinnis; Y Song; H Michael; M C McCormack; H Allore; A Morris; K Crothers; R Bucala; P J Lee; M Sauler
Journal:  Am J Physiol Lung Cell Mol Physiol       Date:  2018-12-06       Impact factor: 5.464

8.  "High-Risk" Clinical and Inflammatory Clusters in COPD of Chinese Descent.

Authors:  Pei Yee Tiew; Fanny Wai San Ko; Jayanth Kumar Narayana; Mau Ern Poh; Huiying Xu; Han Yee Neo; Li-Cher Loh; Choo Khoon Ong; Micheál Mac Aogáin; Jessica Han Ying Tan; Nabilah Husna Kamaruddin; Gerald Jiong Hui Sim; Therese S Lapperre; Mariko Siyue Koh; David Shu Cheong Hui; John Arputhan Abisheganaden; Augustine Tee; Krasimira Tsaneva-Atanasova; Sanjay H Chotirmall
Journal:  Chest       Date:  2020-02-22       Impact factor: 9.410

9.  Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study.

Authors:  Gregory L Kinney; Stephanie A Santorico; Kendra A Young; Michael H Cho; Peter J Castaldi; Raul San José Estépar; James C Ross; Jennifer G Dy; Barry J Make; Elizabeth A Regan; David A Lynch; Douglas C Everett; Sharon M Lutz; Edwin K Silverman; George R Washko; James D Crapo; John E Hokanson
Journal:  Am J Epidemiol       Date:  2018-10-01       Impact factor: 4.897

10.  Subtypes of COPD Have Unique Distributions and Differential Risk of Mortality.

Authors:  Kendra A Young; Elizabeth A Regan; MeiLan K Han; Sharon M Lutz; Margaret Ragland; Peter J Castaldi; George R Washko; Michael H Cho; Mathew Strand; Douglas Curran-Everett; Terri H Beaty; Russell P Bowler; Emily S Wan; David A Lynch; Barry J Make; Edwin K Silverman; James D Crapo; John E Hokanson; Gregory L Kinney
Journal:  Chronic Obstr Pulm Dis       Date:  2019-11
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