Comorbidity Patterns and Identification of Clusters in >1,000,000 Patients Diagnosed with Osteoarthritis in Four Different European Countries: A ComOA Study

Pineda-Moncusi, Marta; Kamps, Anne; Swain, Subhashisa; Dell'isola, Andrea; Turkiewicz, Aleksandra; Runhaar, Jos; Mallen, Christian; Kuo, Chang-Fu; Coupland, Carol; Doherty, Michael; Sarmanova, Aliya; Englund, Martin; Bierma-Zeinstra, Sita M.A.; Zhang, Weiya; Strauss, Victoria; Robinson, Danielle; Prieto-Alhambra, Daniel; Khalid, Sara

Abstract

Objectives: To identify comorbidity patterns at the time of diagnosis of osteoarthritis and to evaluate their risk of mortality at 10-years.

Methods: Data from 1,033,594 individuals with incident diagnosis of osteoarthritis were used from four European healthcare databases. Latent class analysis was used to identify clusters of comorbidities. Clusters were internally evaluated by their posterior probabilities and comorbidities prevalence, and externally validated by clinical characteristics not included in the clustering algorithm. Their association with age and sex adjusted ‘all-cause-mortality’ was assessed.

Results: We identified four consistent clusters across the four populations: "Relatively few morbidities/mild", "Musculoskeletal and mental health morbidities", "Cardiovascular morbidities" and "Multiple morbidities". The first cluster had the largest number of patients and the lowest median number of comorbidities (range 1 to 2) and was used as the reference in the mortality assessment. The second cluster had the highest proportion of women and an excess risk of mortality (ranging from 11% to 66%) compared to the referent cluster in three of the four populations. "Cardiovascular morbidities" had the highest proportion of men, whilst "Multiple morbidities" was the smallest cluster with the highest mean age and median of comorbidities (range 5 to 11). “Cardiovascular morbidities” and “Multiple morbidities” clusters had an excess mortality risk compared to the referent cluster in all populations (range 24% to 63% and 86% to 205%, respectively).

Conclusions: The consistent four clusters of comorbidities present in patients with osteoarthritis from different European populations may have a potential to inform patient care decision-making and healthcare resource allocation.

Funding: Foundation for Research in Rheumatology, The Swedish Research Council, Governmental funding of clinical research within the national health services (ALF), Österlund Foundation, Gustaf V 80-year Birthday Foundation, The Foundation for Individuals with Movement Disability in Skåne, The Swedish Rheumatism Association and Oxford NIHR Biomedical Research Centre.

Citation

Pineda-Moncusi, M., Kamps, A., Swain, S., Dell'isola, A., Turkiewicz, A., Runhaar, J., Mallen, C., Kuo, C.-F., Coupland, C., Doherty, M., Sarmanova, A., Englund, M., Bierma-Zeinstra, S. M., Zhang, W., Strauss, V., Robinson, D., Prieto-Alhambra, D., & Khalid, S. Comorbidity Patterns and Identification of Clusters in >1,000,000 Patients Diagnosed with Osteoarthritis in Four Different European Countries: A ComOA Study

• Working Paper Type: Preprint
• Deposit Date: Aug 19, 2025
• Publicly Available Date: Aug 19, 2025
• DOI: https://doi.org/10.2139/ssrn.4590910
• Public URL: https://keele-repository.worktribe.com/output/1367826
• Publisher URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4590910