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Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study
  1. Marije F Bakker1,
  2. Guy Cavet2,
  3. Johannes WG Jacobs1,
  4. Johannes W J Bijlsma1,
  5. Douglas J Haney2,
  6. Yijing Shen2,
  7. Lyndal K Hesterberg3,
  8. Dustin R Smith3,
  9. Michael Centola3,
  10. Joel A G van Roon1,
  11. Floris P J G Lafeber1,
  12. Paco M J Welsing1,5
  1. 1Department of Rheumatology & Clinical Immunology, UMC Utrecht, Utrecht, The Netherlands
  2. 2Department of Informatics, Crescendo Bioscience, South San Francisco, California, USA
  3. 3Department of Development, Crescendo Bioscience, South San Francisco, California, USA
  4. 4Department of Microbiology and Immunology OMRF, Oklahoma City, Oklahoma, USA
  5. 5Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht, The Netherlands
  1. Correspondence to Marije F Bakker, UMC Utrecht, Department of Rheumatology & Clinical Immunology, Utrecht PO BOX 85500, The Netherlands; m.f.bakker-8{at}


Objectives To evaluate the performance of individual biomarkers and a multi-biomarker disease activity (MBDA) score in the early rheumatoid arthritis (RA) patient population from the computer assisted management in early rheumatoid arthritis (CAMERA) study.

Methods Twenty biomarkers were measured in the CAMERA cohort, in which patients were treated with either intensive or conventional methotrexate-based treatment strategies. The MBDA score was calculated using the concentrations of 12 biomarkers (SAA, IL-6, TNF-RI, VEGF-A, MMP-1, YKL-40, MMP-3, EGF, VCAM-1, leptin, resistin and CRP) according to a previously trained algorithm. The performance of the scores was evaluated relative to clinical disease activity assessments. Change in MBDA score over time was assessed by paired Wilcoxon rank sum test. Logistic regression was used to evaluate the ability of disease activity measures to predict radiographic progression.

Results The MBDA score had a significant correlation with the disease activity score based on 28 joints-C reactive protein (DAS28-CRP) (r=0.72; p<0.001) and an area under the receiver operating characteristic curve for distinguishing remission/low from moderate/high disease activity of 0.86 (p<0.001) using a DAS28-CRP cut-off of 2.7. In multivariate analysis the MBDA score, but not CRP, was an independent predictor of disease activity measures. Additionally, mean (SD) MBDA score decreased from 53 (18) at baseline to 39 (16) at 6 months in response to study therapy (p<0.0001). Neither MBDA score nor clinical variables were predictive of radiographic progression.

Conclusions This multi-biomarker test performed well in the assessment of disease activity in RA patients in the CAMERA study. Upon further validation, this test could be used to complement currently available disease activity measures and improve patient care and outcomes.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: and

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  • Funding Crescendo Bioscience.

  • Competing interests Cavet, Haney, Shen and Hesterberg are all employees of Crescendo Bioscience, the company performing the multi-biomarker score and all laboratory analyses. Centola received a consulting fee from Crescendo Bioscience for his contribution to this manuscript.

  • Ethics approval Approval provided by the Medical Ethics Committee of UMC Utrecht, The Netherlands.

  • Provenance and peer review Provenance and peer review Not commissioned; externally peer reviewed

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