High anti-cyclic citrullinated peptide levels and an algorithm of four variables predict radiographic progression in patients with rheumatoid arthritis: results from a 10-year longitudinal study

Abstract

Objectives: New effective therapies with particularly good effect on joint destruction have highlighted the need for reliable predictors of radiographic progression in rheumatoid arthritis (RA). Our objective was to assess the combined predictive role of a set of laboratory markers with regard to 10-year radiographic progression, and to examine the effect of anti-cyclic citrullinated peptide (anti-CCP) level.

Methods: A cohort of 238 patients with RA was followed longitudinally for 10 years with the collection of clinical data and serum samples. 125 patients with radiographs of the hands available at both baseline and after 10 years were included in this study. Radiographs were scored according to the van der Heijde modified Sharp score. Baseline sera were analysed for C-reactive protein, erythrocyte sedimentation rate (ESR), anti-CCP, IgA rheumatoid factor (RF) and IgM RF. Logistic regression analyses were used to identify predictors of radiographic progression and to examine the effect of anti-CCP level.

Results: Anti-CCP (OR 4.0; 95% CI 1.6 to 10.0) was the strongest independent predictor of radiographic progression. Female gender (OR 3.3; 95% CI 1.3 to 7.6), high ESR (OR 3.2; 95% CI 1.2 to 7.6) and a positive IgM RF (OR 3.1; 95% CI 1.2 to 7.9) were also independent predictors. Compared with the anti-CCP-negative patients, patients with low to moderate levels of anti-CCP (OR 2.6; 95% CI 0.9 to 7.2) and patients with high levels of anti-CCP (OR 9.9; 95% CI 2.7 to 36.7) were more likely to develop radiographic progression.

Conclusions: Anti-CCP, IgM RF, ESR and female gender were independent predictors of radiographic progression and could be combined into an algorithm for better prediction. Patients with high levels of anti-CCP were especially prone to radiographic progression, indicating that the anti-CCP level may add prognostic information.