Toggle Main Menu Toggle Search

Open Access padlockePrints

Statistical cluster analysis of the british thoracic society severe refractory asthma registry: Clinical outcomes and phenotype stability

Lookup NU author(s): Professor Paul Burton

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


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. © 2014 Newby et al.


Publication metadata

Author(s): Newby C, Heaney LG, Menzies-Gow A, Niven RM, Mansur A, Bucknall C, Chaudhuri R, Thompson J, Burton P, Brightling C

Publication type: Article

Publication status: Published

Journal: PLoS ONE

Year: 2014

Volume: 9

Issue: 7

Online publication date: 24/07/2014

Acceptance date: 26/06/2014

ISSN (print): 1932-6203

Publisher: Public Library of Science

URL: https://doi.org/10.1371/journal.pone.0102987

DOI: 10.1371/journal.pone.0102987

PubMed id: 25058007


Altmetrics

Altmetrics provided by Altmetric


Actions

Find at Newcastle University icon    Link to this publication


Share