POS1124 EVALUATION OF COMORBIDITY PATTERNS AND IDENTIFICATION OF SUB-GROUPS IN PATIENTS DIAGNOSED WITH HIP OSTEOARTHRITIS IN 94,720 PATIENTS FROM SPAIN

Abstract

Background Osteoarthritis (OA) patients are more likely to have other comorbidities (Swain, Sarmanova et al. 2020). Improving the understanding of comorbidity profiles of OA patients may lead to improvement in their clinical care.

Objectives To identify sub-groups in patients diagnosed with hip OA using patterns of comorbidity.

Methods Routinely-collected data of individuals =18 years with an incident diagnosis of hip OA (baseline/time of diagnosis), with at least 1 year of follow-up in SIDIAP (Information System for Research in Primary Care, a primary case database from Spain) were collected from January 1st 2006 to June 31st 2020. Those with soft-tissue disorders or other bone/cartilage diseases at the same joint in the year prior/after baseline were excluded. Comorbidities associated with OA in the literature and present in =1% of the study population were included. Clusters of comorbidities were identified at baseline using latent class analysis (LCA), a soft clustering method that classifies individuals according to the distribution of their measured items. The number of clusters or sub-groups within the study population was decided by comparing goodness of fit parameters (CAIC, BIC, ABIC) and log-likelihood changes of models from 2 to 8 clusters. The selected model was externally evaluated by a survival analysis assessing 10 years mortality within each cluster, where the weight of the posterior probability was used as a probability of sampling weight.

Results We identified 94,720 individuals with an incident diagnosis of hip OA, 56.3% women and 43.7% men, with a mean age (SD) of 67.2 (13.1) years. We selected the LCA model with 5 clusters that could be described as: healthier (lower prevalence of all comorbidities than average in the cohort), multimorbidity (higher prevalence of all comorbidities, multiple comorbidities), back/neck pain plus mental health (B/N-mental), cardiovascular disease (CVD), and metabolic syndrome (MetS) (Figure 1). Cox regression (HR [95CI%]) showed higher mortality risk for multimorbidity (3.76 [3.70-3.83]), CVD (1.56 [1.53-1.59]) and MetS (4.56 [4.35-4.78]), compared to healthy. No difference was observed for B/N-mental cluster.