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Arthritis Res Ther. 2011 May 8;13(3):R70. doi: 10.1186/ar3331.

The relation between cartilage biomarkers (C2C, C1,2C, CS846, and CPII) and the long-term outcome of rheumatoid arthritis patients within the CAMERA trial.

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Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands.



The aim of this study was to investigate whether serum biomarker levels of C2C, C1,2C, CS846, and CPII can predict the long-term course of disease activity and radiographic progression early in the disease course of rheumatoid arthritis (RA).


In patients in the CAMERA trial, levels of biomarkers were evaluated at baseline and after 1 year of treatment. Relations of (changes in) biomarker values with the mean yearly radiographic progression rate and mean disease activity over a 5-year period were evaluated by using regression analysis. The added predictive value of biomarkers over established predictors for long-term outcome was analyzed by multiple linear regression analysis.


Of 133 patients, serum samples were available at baseline and after 1 year of treatment. In the regression analysis C1,2C at baseline, the change in C2C, C1,2C, and the sum of the standardized changes in C2C + C1,2C scores were statistically significantly associated with the mean yearly radiographic progression rate; the change in CPII was associated with the mean disease activity over 5 years of treatment. In the multiple linear regression analysis, only the change in C1,2C was of added predictive value (P = 0.004) for radiographic progression. Explained variances of models for radiographic progression and disease activity were low (0.28 and 0.34, respectively), and the biomarkers only marginally improved the explained variance.


The change in C1,2C in the first year after onset of RA has a small added predictive value for disease severity over a 5-year period, but the predictive value of this biomarker combined with current predictive factors is too small to be of use for individual patients.

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