Background: Rheumatoid arthritis (RA) is an autoimmune disease, symmetrically affecting the small joints. Biomarkers are tools that can be used in the diagnosis and monitoring of RA.
Aim: To systematically explore the role of the biomarkers: C-reactive protein (CRP), rheumatoid factor (RF), anti-cyclic citrullinated protein (Anti-CCP), 14-3-3η protein, and the multi-biomarker disease activity (MBDA) score for the diagnosis and treatment of RA.
Methods: A systematic review of the English literature using four different databases was carried out.
Results: CRP >7.1 mg/L predicted poor conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) outcome in RA. Anti-CCP, CRP ≥0.3 mg/dL, and RF predicted bone erosion and cartilage destruction. Combination of high 14-3-3η protein with RF and CRP improved the prediction of rapid erosion progression (REP). Anti-CCP was not associated with disease activity but was associated with increased radiographic damage (r = 0.46, p = 0.048). RF was not associated with joint damage but correlated with ultrasound-detected bone erosion. The 14-3-3η protein significantly correlated with inflammation, bone rremodeling, and osteoporosis in RA patients (p < 0.05). In addition, the 14-3-3η protein positively correlated with RA duration (p = 0.003), disease aactivity, and positive RF (p = 0.025) and it distinguished early from established RA. Early MBDA scores correlated with later response in disease activity after 6 and 12 weeks of treatment (p < 0.05). The MBDA score was able to differentiate between small differences in disease activity, predicted remission over 1-year pperiod, and was a strong predictor of radiographic progression of RA.
Conclusion: The investigated biomarkers are helpful tools in clinical practice for diagnosis, monitoring of treatment, and predicting prognosis in RA patients. However, further research is still required to investigate novel biomarkers for the pre-treatment selection of potentially responsive patients before starting therapy for a precision medicine in this area.
Keywords: Rheumatoid arthritis; biomarkers; diagnosis; management.