Severe Asthma Multimorbidity Clusters Across Europe; Findings From SHARP

<bold>Background:</bold> The nature and impact of multimorbidity (MM) in severe asthma (SA) is poorly defined. <bold>Aim:</bold> To better understand this issue we applied cluster analysis to create MM clusters in SA from comorbidities across the SHARP CRC. <bold>Methods:</bold> We analysed data from 2690 patients in 11 SHARP CRC countries spanning North, East, South and Western Europe. <bold>Results:</bold> Ten comorbidities had prevalence ≥5% in all regions. Three MM clusters (MMC) based on 6 conditions were consistently seen across Europe: MMC1) osteoporosis and steroid induced weight gain, MMC2) eczema and rhinitis, and MMC3) chronic sinusitis and nasal polyps. Obesity, bronchiectasis, gastro-oesophageal reflux and psychological comorbidities clustered variably by region (Fig. 1). <fig><object-id>erj;64/suppl_68/PA482/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig> Patients were categorised according to whether their comorbidity profile fell into none, 1, 2 or all 3 of these MMC groups (giving 8 possibilities; MMC0 through to MMC123). MMC3 (25%) was the commonest single group and had highest T2 traits. MMC0 (19%) had oldest asthma onset and was more likely to currently smoke. MMC1 (8%) had highest regular oral steroid use, worst lung function and highest BMI. Prevalence of the 8 MMC groups varied by country. <bold>Conclusion:</bold> We found 3 consistent MM clusters in SA across Europe, plus 4 comorbidities that varied in cluster assignment by region. MMC prevalence varied by country, but patients profiled in this way had consistent and distinct clinical traits.

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Journal
Epidemiology
Published
2024-09-14
DOI
https://doi.org/10.1183/13993003.congress-2024.pa482
Primary Topic
Asthma and respiratory diseases
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article
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article

Severe Asthma Multimorbidity Clusters Across Europe; Findings From SHARP

Florin Mihălţan, Piotr Kuna, Ramesh Kurukulaaratchy, Anneke Ten Brinke et al.
Epidemiology
Asthma and respiratory diseases
article

Severe Asthma Multimorbidity Clusters Across Europe; Findings From SHARP

Florin Mihălţan, Piotr Kuna, Ramesh Kurukulaaratchy, Anneke Ten Brinke, Bilun Gemicioğlu, Sabina Škrgat, Aruna T. Bansal, Florence Schleich, Betty Frankemölle, Εleftherios Ζervas, Zsuzsanna Csoma, Anna Freeman, Kristina Biekšienė, Barbro Dahlén, Svetlana Sergejeva, Saša Rink, Apostolos Bossios, Sonya Jacob, Valentyna Yasinska, Sanja Grle Popović, Sanja Hromiš, Mehar Singh, Ineta Grisle
article en

Abstract

<bold>Background:</bold> The nature and impact of multimorbidity (MM) in severe asthma (SA) is poorly defined. <bold>Aim:</bold> To better understand this issue we applied cluster analysis to create MM clusters in SA from comorbidities across the SHARP CRC. <bold>Methods:</bold> We analysed data from 2690 patients in 11 SHARP CRC countries spanning North, East, South and Western Europe. <bold>Results:</bold> Ten comorbidities had prevalence ≥5% in all regions. Three MM clusters (MMC) based on 6 conditions were consistently seen across Europe: MMC1) osteoporosis and steroid induced weight gain, MMC2) eczema and rhinitis, and MMC3) chronic sinusitis and nasal polyps. Obesity, bronchiectasis, gastro-oesophageal reflux and psychological comorbidities clustered variably by region (Fig. 1). <fig><object-id>erj;64/suppl_68/PA482/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig> Patients were categorised according to whether their comorbidity profile fell into none, 1, 2 or all 3 of these MMC groups (giving 8 possibilities; MMC0 through to MMC123). MMC3 (25%) was the commonest single group and had highest T2 traits. MMC0 (19%) had oldest asthma onset and was more likely to currently smoke. MMC1 (8%) had highest regular oral steroid use, worst lung function and highest BMI. Prevalence of the 8 MMC groups varied by country. <bold>Conclusion:</bold> We found 3 consistent MM clusters in SA across Europe, plus 4 comorbidities that varied in cluster assignment by region. MMC prevalence varied by country, but patients profiled in this way had consistent and distinct clinical traits.

Epidemiology
Leiden University (NL), Lithuanian University of Health Sciences (LT), University Hospital Centre Zagreb (HR), University of Liège (BE), Ljubljana University Medical Centre (SI), Medisch Centrum Leeuwarden (NL), Karolinska Institutet (SE), University of Łódź (PL), Chest Diseases Hospital (KW), Riga East University Hospital (LV), Svenska Örtmedicinska Institute (SE), Oclaro (United Kingdom) (GB), Istanbul University-Cerrahpaşa (TR), Netherlands Federation of University Medical Centres (NL), Clinica de Pneumologie Iaşi (RO), Medical University of Lodz (PL), Swedish Asthma and Allergy Association (SE), Institute for Pulmonary Diseases of Vojvodina (RS), Edelman (United Kingdom) (GB), Országos Korányi Tbc és Pulmonológiai Intézet (HU), University of Southampton (GB), University of Tartu (EE)
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Asthma and respiratory diseases
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