Article (Scientific journals)
Comprehensive Cluster Analysis for COPD Including Systemic and Airway Inflammatory Markers
Nekoee Zahraei, Halehsadat; GUISSARD, Françoise; Paulus, Virginie et al.
2020In COPD: Journal of Chronic Obstructive Pulmonary Disease, p. 1-12
 

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Keywords :
chronic obstructive pulmonary disease (COPD); Cluster analysis; Phenotype; Factor analysis of mixed data; Missing value
Abstract :
[en] Chronic obstructive pulmonary disease (COPD) is a complex, multidimensional and heterogeneous disease. The main purpose of the present study was to identify clinical phenotypes through cluster nalysis in adults suffering from COPD. A retrospective study was conducted on 178 COPD patients in stable state recruited from ambulatory care at University hospital of Liege. All patients were above 40 years, had a smoking history of more than 20 pack years, post bronchodilator FEV1/FVC <70% and denied any history of asthma before 40 years. In this study, the patients were described by a total of 84 mixed sets of variables with some missing values. Hierarchical clustering on principal components (HCPC) was applied on multiple imputation. In the final step, patients were classified into homogeneous distinct groups by consensus clustering. Three different clusters, which shared similar smoking history were found. Cluster 1 included men with moderate airway obstruction (n¼67) while cluster 2 comprised men who were exacerbation-prone, with severe airflow limitation and intense granulocytic airway and neutrophilic systemic inflammation (n¼56). Cluster 3 essentially included women with moderate airway obstruction (n¼55). All clusters had a low rate of bacterial colonization (5%), a low median FeNO value (<20 ppb) and a very low sensitization rate toward common aeroallergens (0-5%). CAT score did not differ between clusters. Including markers of systemic airway inflammation and atopy and applying a comprehensive cluster analysis we provide here evidence for 3 clusters markedly shaped by sex, airway obstruction and neutrophilic inflammation but not by symptoms and T2 biomarkers.
Disciplines :
Cardiovascular & respiratory systems
Author, co-author :
Nekoee Zahraei, Halehsadat ;  Université de Liège - ULiège > Département des sciences de la santé publique > Biostatistique
GUISSARD, Françoise ;  Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Clinique de l'asthme
Paulus, Virginie;  Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Clinique de l'asthme
HENKET, Monique ;  Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Clinique de l'asthme
Donneau, Anne-Françoise ;  Université de Liège - ULiège > Département des sciences de la santé publique > Biostatistique
Louis, Renaud ;  Centre Hospitalier Universitaire de Liège - CHU > Département des Services Logistiques > Centre Hospitalier Universitaire de Liège - CHU
Language :
English
Title :
Comprehensive Cluster Analysis for COPD Including Systemic and Airway Inflammatory Markers
Publication date :
01 October 2020
Journal title :
COPD: Journal of Chronic Obstructive Pulmonary Disease
ISSN :
1541-2555
eISSN :
1541-2563
Publisher :
Taylor & Francis, United Kingdom
Pages :
1-12
Available on ORBi :
since 19 December 2020

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