Royal Wolverhampton NHS Trust Wolverhampton, United Kingdom
Disclosure information not submitted.
Marco Fornaro1, Vincenzo Venerito2, Florenzo Iannone3, Naveen R4, Elena Nikiphorou5, Mrudula Joshi6, Ai Lyn Tan7, Sreoshy Saha8, Samuel Shinjo9, Vishwesh Agarwal10, Nelly Ziade11, Tsvetelina Velikova12, Esha Kadam13, Marcin Milchert14, Ioannis Parodis15, Abraham Edgar Gracia-Ramos16, Lorenzo Cavagna17, Masataka Kuwana18, Johannes Knitza19, Ashima Makol20, Dey Dzifa21, CARLOS ENRIQUE TORO GUTIERREZ22, CARLO VINICIO CABALLERO23, Oliver Distler24, Jessica Day25, Hector Chinoy26, Vikas Agarwal4, Rohit Aggarwal27, Latika Gupta28 and COVAD Study Group29, 1University of Bari, Grottaglie, Italy, 2Rheumatology Department, Università degli Studi di Bari, Bari, Italy, 3Rheumatology Unit, Department of Precision and Regenerative Medicine and Ionian Area, University of Bari "Aldo Moro", Bari, Italy, 4Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Lucknow, India, 5King's College London, London, United Kingdom, 6Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India, 7University of Leeds, Leeds, United Kingdom, 8Mymensingh Medical College, Faridpur, Bangladesh, 9Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, Brazil, 10Mahatma Gandhi Missions Medical College, Lucknow, India, 11Saint-Joseph University, Beirut, Lebanon, 12Department of Clinical Immunology, Medical Faculty, University Hospital "Lozenetz", Sofia University St. Kliment Ohridski, Sofia, Bulgaria, 13Seth Gordhandhas Sunderdas Medical College and King Edwards Memorial Hospital, Mumbai, India, 14Department of Internal Medicine, Rheumatology, Diabetology, Geriatrics and Clinical Immunology, Pomeranian Medical University in Szczecin, Szczecin, Poland, 15Karolinska Institutet, Stockholm, Sweden, 16Department of Internal Medicine, General Hospital, National Medical Center "La Raza", Instituto Mexicano del Seguro Social, Av. Jacaranda S/N, Col. La Raza, Del. Azcapotzalco, C.P. 02990, Mexico City, Mexico, 17Fondazione IRCCS Policlinico San Matteo, Pavia, Italy, 18Nippon Medical School Graduate School of Medicine, Tokyo, Japan, 19Department of Internal Medicine 3 Rheumatology and Immunology, Friedrich-Alexander-University Erlangen-Nürnberg, University Hospital Erlangen, Erlangen, Germany, 20Mayo Clinic, Rochester, MN, Rochester, MN, 21Department of Medicine and Therapeutics, University of Ghana School of Medicine and Dentistry, College of Health Sciences, Korle-Bu, Accra, Ghana, 22Centro de Estudios de Reumatología y Dermatología SAS, Cali, Colombia, 23REUMACARIBE IPS, Barranquilla, Colombia, 24Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland, 25Walter and Eliza Hall Institute, Melbourne, Australia, 26The University of Manchester, Sale, United Kingdom, 27University of Pittsburgh, Pittsburgh, PA, 28Royal Wolverhampton Trust, Wolverhampton/University of Manchester, United Kingdom, 29-, -
Background/Purpose: Comorbidities have a profound impact on the quality of life (QoL), though global data on the burden of comorbidities and its impact on health outcomes and QoL in vulnerable groups such as Idiopathic inflammatory myopathies (IIMs) is scarce.
Methods: We studied the prevalence, distribution and clustering of comorbidities and multimorbidity among patients with IIM, AIRDs and healthy controls (HCs) and its impact on health outcomes, utilizing data from the COVAD 2 study, a global patient-reported e-survey consisting of 167 collaborators from 110 countries. Basic multimorbidity (BM) /Complex multimorbidity (CM) were defined as the co-occurrence of ≥2 non-rheumatic comorbidities & ≥3 non-rheumatic chronic conditions affecting ≥3 different organ systems1 respectively. Human Development Index (HDI) of their country was taken as a surrogate marker for socioeconomic status (SES). PROMIS global physical health (PGP), mental health (PGM), fatigue 4a (F4a) and physical function short form (SF10) were analysed using descriptive statistics and linear regression models. Hierarchical Clustering on Principal Components was performed to outline the grouping.
Results: Among 10740 respondents, 1558 IIMs (15.9%), 4591 other AIRDs (46.8%) and 3652 HCs (37.3%) were analysed. IIMs comprised mainly of DM (30.2%) and IBM (24.1%) whilst AIRDs comprised 2450 inflammatory arthritis (53.4%), 2050 CTDs (44.6%) and 235 systemic vasculitis (5.1%). Individuals with IIMs exhibited high burden of any comorbidity (OR: 1.62 vs AIRDs and 2.95 vs HCs,p < 0.01), BM (OR 1.66 vs AIRDs 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 AIRDs and 2.63 vs HCs,p < 0.01)(FIG 1A, global distribution depicted as FIG 2) IIM patients with comorbidities (and MHDs) had worse physical function (low PGP, PGM, SF10 and higher F4a scores, all *p < 0.001). Worse physical function (PGP, SF10a, F4a) and mental health (PGM) was predicted by age, active disease, BM, and MHDs. Worse SF10a and F4a scores were also associated with female gender and country HDI respectively. (FIG 1B) 4 distinct clusters were identified among IIMs: Cluster 0: lower comorbidity burden and good health status Cluster 1: older patients with higher comorbidity burden and poorer health status Cluster 2: patients with higher prevalence of MHDs, lower PGP, PGM and higher F4a scores Cluster 3: older patients with average comorbidity burden and good health status. DM, Anti-synthetase syndrome and necrotizing autoimmune myopathy were similarly represented in all clusters, while IBM and PM were more pre-dominant in clusters 1 (61.7% and 45.3%) and 3(36.4 and 34.6), while overlap myositis was more represented in clusters 2 (45.4%). (FIG 3)
Conclusion: Patients with IIMs have a higher burden of comorbidities with identifiable syndemic clusters that adversely impact physical and mental health, calling for optimized approaches for holistic patient management. References:
Harrison C, Britt H, Miller G, Henderson J. Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice. BMJ Open. 2014 Jul 1;4(7):e004694.
FIGURE 1: A: “Comorbidities in the COVAD cohort”: highlighting thier increased incidence in IIMs as compared to other AIRDs or HCs. B: Linear regression analysis (PGP, PGM, SF10a and F4a scores in BM, CM and MHDs)
FIGURE 2: A, B, C Distribution of basic multi-morbidity, complex multi-morbidity, and mental health disorders among patients with IIMs
FIGURE 3 A, B, C: Clusters in IIM C: Each superscript letter indicates a subset of the 4 groups analyzed for which the means or proportions showed no difference at a significance level of .05.