Biomarkers for the diagnosis and treatment of rheumatoid arthritis-a systematic review

Abstract

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 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 anti-rheumatic 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 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. 14-3-3η significantly correlated with inflammation, bone remodelling and osteoporosis in RA patients (p<0.05). 14 3 3η positively correlated with RA duration (p=0.003), disease activity 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). MBDA score was able to differentiate between small differences in disease activity and predicted remission over one year period. 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.

Commentary on Cohen et al.: Role of Clinical Factors in Precision Medicine Test to Predict Nonresponse to TNFi Therapies in Rheumatoid Arthritis

“…Patient global assessment-included in the MSRC feature setconsiders disease activity and complex underlying factors such as pain, depression, anxiety, and inability to participate in daily activities [34]. Numerous additional studies [35,36], a review of which are beyond the scope of this letter, evaluated the likelihood of treatment success with TNFi in RA, yet a clinically useful model predicting TNFi therapeutic outcomes from routine clinical assessments alone has not been achieved.…”