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PLoS One. 2014 Jul 24;9(7):e102987. doi: 10.1371/journal.pone.0102987. eCollection 2014.

Statistical cluster analysis of the British Thoracic Society Severe refractory Asthma Registry: clinical outcomes and phenotype stability.

Author information

1
Department of Infection, Inflammation and Immunity, Institute for Lung Health, University of Leicester, Leicester, United Kingdom; Department of Health Sciences, University of Leicester, Leicester, United Kingdom.
2
Centre for Infection and Immunity, Queen's University of Belfast, Belfast, United Kingdom.
3
Royal Brompton Hospital, London, United Kingdom.
4
North West Lung Centre, University of Manchester, Manchester, United Kingdom.
5
Severe and Brittle Asthma Unit, Birmingham Heartlands Hospital, Birmingham, United Kingdom.
6
Department of Respiratory Medicine, Stobhill Hospital, Glasgow, United Kingdom.
7
Department of Respiratory Medicine, Division of Immunology, Infection and Inflammation, University of Glasgow and Gartnavel General, Glasgow, United Kingdom.
8
Department of Health Sciences, University of Leicester, Leicester, United Kingdom.
9
Department of Infection, Inflammation and Immunity, Institute for Lung Health, University of Leicester, Leicester, United Kingdom.

Abstract

BACKGROUND:

Severe refractory asthma is a heterogeneous disease. We sought to determine statistical clusters from the British Thoracic Society Severe refractory Asthma Registry and to examine cluster-specific outcomes and stability.

METHODS:

Factor analysis and statistical cluster modelling was undertaken to determine the number of clusters and their membership (N = 349). Cluster-specific outcomes were assessed after a median follow-up of 3 years. A classifier was programmed to determine cluster stability and was validated in an independent cohort of new patients recruited to the registry (n = 245).

FINDINGS:

Five clusters were identified. Cluster 1 (34%) were atopic with early onset disease, cluster 2 (21%) were obese with late onset disease, cluster 3 (15%) had the least severe disease, cluster 4 (15%) were the eosinophilic with late onset disease and cluster 5 (15%) had significant fixed airflow obstruction. At follow-up, the proportion of subjects treated with oral corticosteroids increased in all groups with an increase in body mass index. Exacerbation frequency decreased significantly in clusters 1, 2 and 4 and was associated with a significant fall in the peripheral blood eosinophil count in clusters 2 and 4. Stability of cluster membership at follow-up was 52% for the whole group with stability being best in cluster 2 (71%) and worst in cluster 4 (25%). In an independent validation cohort, the classifier identified the same 5 clusters with similar patient distribution and characteristics.

INTERPRETATION:

Statistical cluster analysis can identify distinct phenotypes with specific outcomes. Cluster membership can be determined using a classifier, but when treatment is optimised, cluster stability is poor.

PMID:
25058007
PMCID:
PMC4109965
DOI:
10.1371/journal.pone.0102987
[Indexed for MEDLINE]
Free PMC Article

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