Clinical and demographic factors associated with change and maintenance of disease severity in a large registry of patients with rheumatoid arthritis

Abstract

Abstract Background We examined models to predict disease activity transitions from moderate to low or severe and associated factors in patients with rheumatoid arthritis (RA). Methods Data from RA patients enrolled in the Corrona registry (October 2001 to August 2014) were analyzed. Clinical Disease Activity Index (CDAI) definitions were used for low (≤10), moderate (>10 and ≤22), and severe (>22) disease activity states. A Markov model for repeated measures allowing for covariate dependence was used to model transitions between three (low, moderate, severe) states and estimate population transition probabilities. Mean sojourn times were calculated to compare length of time in particular states. Logistic regression models were used to examine impacts of covariates (time between visits, chronological year, disease duration, age) on disease states. Results Data from 29,853 patients (251,375 visits) and a sub-cohort of 9812 patients (46,534 visits) with regular visits (every 3–9 months) were analyzed. The probability of moving from moderate to low or severe disease by next visit was 47% and 18%, respectively. Patients stayed in moderate disease for mean 4.25 months (95% confidence interval: 4.18–4.32). Transition probabilities showed 20% of patients with low disease activity moved to moderate or severe disease within 6 months; >35% of patients with moderate disease remained in moderate disease after 6 months. Results were similar for the regular-visit sub-cohort. Significant interactions with prior disease state were seen with chronological year and disease duration. Conclusion A substantial proportion of patients remain in moderate disease, emphasizing the need for treat-to-target strategies for RA patients.

Keywords

• Rheumatoid arthritis
• Disease activity
• Prediction
• Markov model
• Clinical Disease Activity Index