Multimorbidity phenotypes and associated characteristics in severe asthma: an observational study of European severe asthma registries

Abstract

Background: the phenotypic nature of multimorbidity in severe asthma is poorly understood. Our aims in this study were to define multimorbidity phenotypes and their characteristics in severe asthma across Europe by identifying and characterising co-aggregation of comorbidities.

Methods: cross-sectional patient data were analysed from the pan-European Severe Heterogenous Asthma Research Collaboration: Patient Centred (SHARP) Central database of national severe asthma registries. Patients were grouped by four European regions (North, South, East, and West). Hierarchical clustering of comorbidities was applied to characterise the correlation structure of the ten commonest comorbidities within these geographical regions. Subsequent multimorbidity phenotypes (MMP) and their clinical features were then defined.

Findings: data were available for 2690 severe asthma patients and 23 comorbidities from 11 countries. Three comorbidity clusters were consistently seen across the four European regions: 1) osteoporosis plus steroid-induced weight gain, 2) eczema plus rhinitis, and 3) chronic sinusitis plus nasal polyps. Four further comorbidities (obesity, bronchiectasis, gastro-oesophageal reflux disease, psychological factors) showed variable clustering. Multimorbidity was ubiquitous. Patients were assigned multimorbidity phenotypes (MMP) according to comorbidity cluster alignment. MMP sn (sinonasal-associated) and MMP u (no specific cluster alignment) were commonest. MMP ster (steroid-associated multimorbidity) had highest maintenance oral steroid (m-OCS) use, and Body Mass Index, plus worst lung function, asthma control, and asthma exacerbation frequency. MMP max (maximal multimorbidity) showed high prevalence of variably assigned comorbidities, higher m-OCS and biologic treatment needs.

Interpretation: multimorbidity is common in severe asthma and can be classified into replicable novel phenotypes with characteristic clinical traits and outcomes. Recognising these phenotypes can guide better care of the ‘whole patient’ with severe asthma. Future clinical guidance should promote such understanding in order to support delivery of more effective personalised asthma care.

Funding: European Respiratory Society, pharmaceutical industry partners (Sanofi, TEVA, Novartis, GlaxoSmithKline, Chiesi).

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Identifiers

ORCID for Anna Freeman: orcid.org/0000-0003-3495-2520

ORCID for Ramesh Kurukulaaratchy: orcid.org/0000-0002-1588-2400

ORCID for Ben Ainsworth: orcid.org/0000-0002-5098-1092

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