Objective: Matrix-based risk models have been proposed as a tool to predict rapid radiographic progression (RRP) in rheumatoid arthritis (RA), but the experience with such models is limited. We tested the performance of 3 risk models for RRP in an observational cohort.
Methods: Subjects from an observational RA cohort with hand radiographs and necessary predictor variables to be classified by the risk models were identified (n = 478). RRP was defined as a yearly change in the Sharp/van der Heijde score of ≥5 units. Patients were placed in the appropriate matrix categories, with a corresponding predicted risk of RRP. The mean predicted probability for cases and noncases, integrated discrimination improvement, Hosmer-Lemeshow statistics, and C statistics were calculated.
Results: The median age was 59 years (interquartile range [IQR] 50-66 years), the median disease duration was 12 years (IQR 4-23 years), the median swollen joint count was 6 (IQR 2-13), 84% were women, and 86% had erosions at baseline. Twelve percent of patients (32 of 271) treated with synthetic disease-modifying antirheumatic drugs (DMARDs) at baseline and 10% of patients (21 of 207) treated with biologic DMARDs experienced RRP. Most of the predictor variables had a skewed distribution in the population. All models had a suboptimal performance when applied to this cohort, with C statistics of 0.59 (model A), 0.65 (model B), and 0.57 (model C), and Hosmer-Lemeshow chi-square P values of 0.06 (model A), 0.005 (model B), and 0.05 (model C).
Conclusion: Matrix risk models developed in clinical trials of patients with early RA had limited ability to predict RRP in this observational cohort of RA patients.
Copyright © 2013 by the American College of Rheumatology.