Fetuin-A and thyroxin binding globulin predict rituximab response in rheumatoid arthritis patients with insufficient response to anti-TNFα.

Objectives: Rheumatoid arthritis (RA) is a debilitating disease, but patient management and treatment have been revolutionized since the advent of bDMARDs. However, about one third of RA patients do not respond to specific bDMARD treatment without clear identified reasons. Different bDMARDs must be tried until the right drug is found. Here, we sought to identify a predictive protein signature to stratify patient responsiveness to rituximab (RTX) among patients with an insufficient response to a first anti-TNFα treatment.

Methods: Serum samples were collected at baseline before RTX initiation. A proteomics study comparing responders and nonresponders was conducted to identify and select potential predictive biomarkers whose concentration was measured by quantitative assays. Logistic regression was performed to determine the best biomarker combination to predict good or nonresponse to RTX (EULAR criteria after 6 months' treatment).

Results: Eleven biomarkers potentially discriminating between responders and nonresponders were selected following discovery proteomics. Quantitative immunoassays and univariate statistical analysis showed that fetuin-A and thyroxine binding globulin (TBG) presented a good capacity to discriminate between patient groups. A logistic regression analysis revealed that the combination of fetuin-A plus TBG could accurately predict a patient's responsiveness to RTX with an AUC of 0.86, sensitivity of 80%, and a specificity of 79%.

Conclusion: In RA patients for whom a first anti-TNFα treatment has failed, the serum abundance of fetuin-A and TBG before initiating RTX treatment is an indicator for their response status at 6 months. ClinicalTrials.gov identifier: NCT01000441. Key Points • Proteomic analysis revealed 11 putative predictive biomarkers to discriminate rituximab responder vs. nonresponder RA patients. • Fetuin-A and TBG are significantly differentially expressed at baseline in rituximab responder vs. nonresponder RA patients. • Algorithm combining fetuin-A and TBG accurately predicts response to rituximab in RA patients with insufficient response to TNFi.