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Vectra DA Test Predicts Risk of Joint Damage Progression in Rheumatoid Arthritis

Joint inflammation and damage are important determinants of disability in patients with rheumatoid arthritis (RA). The multi-biomarker disease activity (MBDA) test (Vectra DA) analyzes 12 serum protein biomarkers and uses a validated algorithm to generate a score that represents
the level of RA disease activity on a scale of 1 to 100 with categories of low (<30), moderate (30−44), and high (>44).

Information about the level of disease activity allows doctors to monitor the response to treatment and to adjust treatment as needed. Commonly used measures of disease activity are the DAS28 (Disease Activity Score with 28 joint counts), the erythrocyte sedimentation rate (ESR) and levels of C-reactive protein (CRP).  The DAS28 involves a count of tender and swollen joints, your own assessment of your health, and lab tests to identify inflammation.

The Vectra DA test allows doctors to test for several biological markers (or biomarkers) of RA simultaneously. Vectra DA measures the levels of 12 proteins in the blood—biomarkers that have been linked to RA disease activity—and then combines them into a single score (between 1 and 100) that classifies your current level of RA disease activity as “low”, “moderate”, or “high”.

The Vectra DA score has previously been found to be associated with identifying a risk for radiographic progression of disease in patients with RA.  Doctors recently reported the results of a clinical study evaluating data collected from 6 groups of individuals with RA to see if a large sample size collectively evaluated could establish a relationship between a Vectra DA score and the risk for radiographic progression of RA.(1-10)

The study revealed that a high Vectra DA score was associated with an increased risk for radiographic progression of RA and that a high Vectra DA score was more predictive of progression that a high CRP or DAS39-CRP, two other commonly used measures of disease activity.

References:

  1. Li W, et al. Rheumatology 2016;55:357-66
  2. van der Helm-van Mil AH, et al. Rheumatology 2013;52:839-46.
  3. Brahe CH, et al. Abstract presented at ACR, 2016
  4. Hambardzumyan K, et al. Ann Rheum Dis 2015;74:1102-9.
  5. Hambardzumyan K, et al. RMD Open 2016;2:e000197.
  6. Curtis JR, et al. Arthritis Rheumatol 2017;69:863-5.
  7. Fleischmann R, et al. Arthritis Rheumatol 2016;68:2083-9.
  8. Fleischmann R, et al. Arthritis Rheumatol 2017;69:867-8.
  9. Weinblatt ME, et al. Arthritis Rheum 2013;65:28-38.
  10. Schiff M, et al. Ann Rheum Dis 2014;73:86-94.
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