0546: Multimorbidity clusters in psoriatic arthritis, psoriasis, and axial spondyloarthritis and their association with healthcare utilization: A population-based study

Background/Purpose: Multimorbidity (≥ 2 chronic conditions) is common in inflammatory diseases such as psoriatic arthritis (PsA), psoriasis (PsO), and axial spondyloarthritis (AxSpA), increasing patient burden and healthcare costs. Understanding specific comorbidity clusters beyond simple counts is crucial for insights into disease heterogeneity and impact. The objective of this study was to identify and compare multimorbidity clusters in PsA, PsO, and AxSpA from a large population database, assess their stability, compare them with matched controls, and examine associations with healthcare utilization (HCU).

Methods: This population-based, retrospective cohort study from the UK THIN database included incident adult PsA (N=5,096), PsO (N=73,751), and AxSpA (N=2,413) patients (identified using validated Read Codes) with ≥1 year follow-up, alongside 1:5 matched controls. Morbidities chosen based on clinical relevance and prior reports were identified using Read codes. Optimal number of clusters was determined by evaluating the balance between within-cluster and between-cluster variance reduction for each level of the hierarchical clustering tree (tree method). K-median clustering identified multimorbidity clusters at 1 and 5 years post-diagnosis. Cluster stability and comparisons with control groups were assessed. Age- and sex-adjusted negative binomial regression were performed to examine the association of year 5 clusters to HCU (outpatient visits, hospitalizations, total prescriptions).

Results: Distinct and stable multimorbidity clusters were identified in each disease cohort at years 1 and 5 (Figure 1). PsA (N=5,096) clusters included Cardiometabolic, Low-Comorbidity, Chronic Pain, and Psychiatric. The Chronic Pain cluster was unique to PsA cases versus controls. PsO (N=73,751) clusters were Low Comorbidity, Allergy-Asthma, Back Pain, and Psychiatric. The Allergy-Asthma cluster was specific to PsO cases. AxSpA (N=2,413) clusters included Cardiovascular, Osteoarthritis, High Multimorbidity (characterized by severe cardiometabolic conditions, cancer, depression, COPD), and Low Comorbidity. Osteoarthritis cluster was unique to AxSpA cases. All identified multimorbidity clusters, as well as substantial multimorbidity (MM5+; ≥5 conditions), were associated with significantly higher HCU compared to respective Low-Comorbidity reference groups (Table 1).

Conclusion: Our study reveals that PsA, PsO, and AxSpA are characterized by distinct, stable multimorbidity clusters, featuring both shared background patterns (e.g., Low-Comorbidity, Psychiatric, Cardiometabolic components) and disease-specific architectures (e.g., PsA-Chronic Pain, PsO-Allergy-Asthma, AxSpA-Osteoarthritis). In terms of healthcare utilization, the findings indicate that the total number of concurrent chronic conditions is a more significant driver than the specific type of multimorbidity cluster. Consequently, while distinct clinical phenotypes are evident, addressing the overall burden of high morbidity (such as in patients with MM5+) is crucial for mitigating excessive healthcare utilization and guiding the development of effective management strategies in these populations.