Comorbidity clusters in patients with rheumatoid arthritis identify a patient phenotype with a favourable prognosis.

OBJECTIVES

We aimed to cluster patients with rheumatoid arthritis (RA) based on comorbidities and then examine the association between these clusters and RA disease activity and mortality.

METHODS

In this population-based study, residents of an eight-county region with prevalent RA on 1 January 2015 were identified. Patients were followed for vital status until death, last contact or 31 December 2021. Diagnostic codes for 5 years before the prevalence date were used to define 55 comorbidities. Latent class analysis was used to cluster patients based on comorbidity patterns. Standardised mortality ratios were used to assess mortality.

RESULTS

A total of 1643 patients with prevalent RA (72% female; 94% white; median age 64 years, median RA duration 7 years) were studied. Four clusters were identified. Cluster 1 (n=686) included patients with few comorbidities, and cluster 4 (n=134) included older patients with 10 or more comorbidities. Cluster 2 (n=200) included patients with five or more comorbidities and high prevalences of depression and obesity, while cluster 3 (n=623) included the remainder. RA disease activity and survival differed across the clusters, with cluster 1 demonstrating more remission and mortality comparable to the general population.

CONCLUSIONS

More than 40% of patients with prevalent RA did not experience worse mortality than their peers without RA. The cluster with the worst prognosis (<10% of patients with prevalent RA) was older, had more comorbidities and had less disease-modifying antirheumatic drug and biological use compared with the other clusters. Comorbidity patterns may hold the key to moving beyond a one-size-fits-all perspective of RA prognosis.