The impact of multimorbidity on Quality of Life in inflammatory myopathies: A cluster analysis from the COVAD dataset
- on behalf of CoVAD Study Group,
- Marco Fornaro(Author),
- Vincenzo Venerito(Author),
- Maria Rosa Pellico(Author),
- Florenzo Iannone(Author),
- Mrudula Joshi(Author)
- University of Bari,
- Università degli Studi di Milano,
- Sassoon General Hospitals,
- Taichung Veterans General Hospital,
- University of Leeds, School of Medicine,
- NIHR Leeds Biomedical Research Centre
Open access
Publication Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 2133-2142 (10 pages)Journal (Volume, Issue Number)
Rheumatology (United Kingdom) (Volume 64, Issue 4)Publication milestones
- Published - 01/04/2025
Publication status
ISSN
1462-0324Publication IDs
- Scopus: 105002248724
- PubMed: 39324556
Abstract
Objective: The presence of comorbidities can substantially affect patients’ quality of life, but data regarding their impact on idiopathic inflammatory myopathies (IIMs) are limited. Methods: We examined the prevalence of comorbidities in IIM patients, other autoimmune rheumatic diseases (oAIRDs) and healthy controls (HCs), using data from the self-reported COVAD-2 survey. We defined basic multimorbidity (BM) as the presence of ≥2 non-rheumatic chronic conditions and complex multimorbidity (CM) as the presence of ≥3 non-rheumatic chronic conditions affecting ≥3 organ systems. Hierarchical clustering on principal components was performed for grouping. Results: Among the COVAD respondents, 1558 IIMs, 4591 oAIRDs and 3652 HCs were analysed. IIMs exhibited a high burden of comorbidities (odds ratio [OR]: 1.62 vs oAIRDs and 2.95 vs HCs, P<0.01), BM (OR: 1.66 vs oAIRDs and 3.52 vs HCs, P<0.01), CM (OR: 1.69 vs AIRDs and 6.23 vs HCs, P<0.01) and mental health disorders (MHDs) (OR: 1.33 vs oAIRDs and 2.63 vs HCs, P<0.01). Among the IIM patients, those with comorbidities or MHDs had lower PROMIS Global Physical (PGP), PROMIS Global Mental (PGM), and PROMIS Physical Function (SF10) scores, and higher fatigue (F4a) scores (all P<0.001). PGP, PGM, SF10a and F4a were influenced by age, active disease, BM and MHDs. Four distinct clusters were identified among the IIMs according to comorbidities and PROMIS scores. Conclusion: Patients with IIMs have a higher burden of comorbidities that influence physical and mental health, identifiable as clinical clusters for optimized and holistic management approaches.
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