Objective: Autoantibodies such as rheumatoid factor (RF) and anti-citrullinated protein autoantibodies (ACPAs) determined by testing with second-generation anti-cyclic citrullinated peptide (anti-CCP-2) are frequently measured in clinical practice because of their association with disease outcome in undifferentiated arthritis (UA) and rheumatoid arthritis (RA). Recently, 2 new ACPA tests were developed: third-generation anti-CCP (anti-CCP-3) and anti-modified citrullinated vimentin (anti-MCV) autoantibody tests. To facilitate the decision on which autoantibody to test in daily practice, this study evaluated the capability of these autoantibodies and combinations of them to predict 3 outcome measures: progression from UA to RA, the rate of joint destruction in RA, and the chance of achieving sustained disease-modifying antirheumatic drug (DMARD)-free remission in RA.
Methods: Patients with UA (n=625) were studied for whether UA progressed to RA after 1 year. Patients with RA (n=687) were studied for whether sustained DMARD-free remission was achieved and for the rate of joint destruction during a median followup of 5 years. Positive predictive values (PPVs) for RA development and for associations with the disease course in RA were compared between single tests (anti-CCP-2, anti-CCP-3, anti-MCV, and RF) and between combinations of these tests.
Results: Among the single tests performed in patients with UA, anti-CCP-2 tended to have the highest PPV for RA development (67.1%), but the 95% confidence intervals of the other tests overlapped. Among the single tests in patients with RA, all 4 tests showed comparable associations with the rate of joint destruction and with the achievement of remission. In both ACPA-positive and ACPA-negative RA, the presence of RF was not associated with more joint destruction. For all outcome measures, performing combinations of 2 or 3 autoantibody tests did not increase the predictive accuracy compared with performing a single test.
Conclusion: For clinical practice, a single autoantibody test is sufficient for risk estimation in UA and RA.