Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study

Abstract

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.

Figure 1

MBDA score algorithm The MBDA score algorithm uses the same equation as the DAS28-CRP, with biomarkers used to predict the Swollen Joint Count (SJC28), Tender Joint Count (TJC28), and general health (VAS-GH) components of the equation. (PTJC= predicted TJC, PSJC= predicted SJC; PVAS-GH= predicted VAS-GH). The Venn diagram lists the MBDA score biomarkers used to predict each MBDA score component. This algorithm provides an MBDA score between 1 and 100.

Figure 2

A-B. Performance of MBDA score relative to DAS28-CRP Figure 2A represents the Pearson correlation and AUROC for distinguishing remission/low from moderate/high DAS28-CRP. Figure 2B represents the ROC Curve for distinguishing remission/low DAS28-CRP from moderate/high DAS28-CRP.

Figure 3

MBDA scores by treatment arm and time point For each treatment strategy (i.e. intensive tight control MTX-based and conventional MTX-based treatment strategy) the results of the MBDA score are shown at baseline and after 6 months of treatment. Only results of patients with MBDA score at baseline and 6 months are shown.