Open Access Research article

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

Marije F Bakker1*, Suzanne MM Verstappen1, Paco MJ Welsing12, Johannes WG Jacobs1, Zalima N Jahangier3, Maaike J van der Veen4, Johannes WJ Bijlsma1, Floris PJG Lafeber1 and the Utrecht Arthritis Cohort study group

Author Affiliations

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

2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands

3 Department of Rheumatology, Tergooi Hospital, P.O. Box 10016, 1201 DA Hilversum, The Netherlands

4 Department of Rheumatology, St. Jansdal Hospital, P.O. Box 138, 3840 AC Harderwijk, The Netherlands

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Arthritis Research & Therapy 2011, 13:R70  doi:10.1186/ar3331

Published: 8 May 2011

Abstract

Introduction

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).

Methods

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.

Results

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.

Conclusions

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.