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 dis...
BACKGROUND: Asthma is a disease of varying severity and differing disease mechanisms. To date, studi...
ADEPT (Airways Disease Endotyping for Personalized Therapeutics) and U-BIOPRED (Unbiased Biomarkers ...
<div><h3>Rationale</h3><p>Identification and characterization of asthma phenotypes are challenging d...
Severe refractory asthma is a heterogeneous disease. We sought to determine statistical clusters fro...
BACKGROUND Severe refractory asthma is a heterogeneous disease. We sought to determine statistica...
Background Severe refractory asthma is a heterogeneous disease. We sought to determine statistica...
International audienceBackground: Cross-sectional severe asthma cluster analysis identified differen...
editorial reviewedIntroduction Eosinophilic asthma is well recognized asthma phenotype associated w...
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) a...
Background: Treatment responsiveness, an important consideration in asthma management is different f...
International audienceBACKGROUND: In France, data regarding epidemiology and management of severe as...
Identification and characterization of asthma phenotypes are challenging due to disease complexity a...
Abstract Background Although the heterogeneous nature...
Rationale: Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asth...
Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristi...
BACKGROUND: Asthma is a disease of varying severity and differing disease mechanisms. To date, studi...
ADEPT (Airways Disease Endotyping for Personalized Therapeutics) and U-BIOPRED (Unbiased Biomarkers ...
<div><h3>Rationale</h3><p>Identification and characterization of asthma phenotypes are challenging d...
Severe refractory asthma is a heterogeneous disease. We sought to determine statistical clusters fro...
BACKGROUND Severe refractory asthma is a heterogeneous disease. We sought to determine statistica...
Background Severe refractory asthma is a heterogeneous disease. We sought to determine statistica...
International audienceBackground: Cross-sectional severe asthma cluster analysis identified differen...
editorial reviewedIntroduction Eosinophilic asthma is well recognized asthma phenotype associated w...
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) a...
Background: Treatment responsiveness, an important consideration in asthma management is different f...
International audienceBACKGROUND: In France, data regarding epidemiology and management of severe as...
Identification and characterization of asthma phenotypes are challenging due to disease complexity a...
Abstract Background Although the heterogeneous nature...
Rationale: Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asth...
Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristi...
BACKGROUND: Asthma is a disease of varying severity and differing disease mechanisms. To date, studi...
ADEPT (Airways Disease Endotyping for Personalized Therapeutics) and U-BIOPRED (Unbiased Biomarkers ...
<div><h3>Rationale</h3><p>Identification and characterization of asthma phenotypes are challenging d...