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.

Time Trends in Glucocorticoid Use in Rheumatoid Arthritis During the Biologics Era: 1999-2018.

OBJECTIVES: To examine time trends in glucocorticoid (GC) use among patients diagnosed with rheumatoid arthritis (RA) during the biologic era. METHODS: A population-based inception cohort of RA patients diagnosed during 1999 - 2018 was followed longitudinally through their medical records until death, migration or 12/31/2020. All patients fulfilled 1987 American College of Rheumatology classification criteria for RA. GC start and stop dates were collected along with dosages in prednisone equivalents. The cumulative incidence of GC initiation and discontinuation adjusted for the competing risk of death was estimated. Cox models adjusted for age and sex were used to compare trends between time periods. RESULTS: The study population included 399 patients (71% female) diagnosed in 1999 - 2008 and 430 patients (67% female) diagnosed in 2009 - 2018. GC use was initiated within 6 months of meeting RA criteria in 67% of patients in 1999-2008 and 71% of patients in 2009-2018, corresponding to a 29% increase in hazard for initiation of GC in 2009-2018 (adjusted hazard ratio [HR]: 1.29; 95% confidence interval [CI]: 1.09-1.53). Among GC users, similar rates of GC discontinuation within 6 months after GC initiation were observed in patients with RA incidence in 1999 - 2008 and 2009 - 2018 (39.1% versus 42.9%, respectively), with no significant association in adjusted Cox models (HR: 1.11; 95% CI: 0.93-1.31). CONCLUSION: More patients are initiating GCs early in their disease course now compared to previously. The rates of GC discontinuation were similar, despite the availability of biologics.

Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity.

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.