Background Elevated type I IFN response gene (IRG) expression has been described to be clinically relevant in predicting the non-response to rituximab in rheumatoid arthritis (RA) patients. Interference between glucocorticoids and type I IFN signalling has been demonstrated in vitro. Since the use and dose of oral GCs is highly variable among patients prior to the start of treatment with rituximab, we aimed to determine what the effect of GC usage is on the IRG expression in relation to the clinical response to rituximab.
Methods In two independently recruited cohorts of biologic-free RA patients (n = 32 and n = 182) and a third cohort of 40 RA patients that were candidates for rituximab therapy, peripheral blood gene expression of 8 IRGs was determined by microarray or multiplex quantitative (q)PCR, and an IFN-score was calculated. The baseline IFN-score was tested for its predictive value towards rituximab response in relation to GC use using Receiver Operating Characteristics (ROC) curve analysis in the rituximab cohort. All patients in the cohorts fulfilled the revised American College of Rheumatology (ACR) 1987 criteria for the diagnosis of RA. GC use consisted of oral prednisone in doses varying from 2.5–10 mg/day and occurred in 19%, 29% and 70% of the patients in the three cohorts, respectively. The clinical response to rituximab was determined after 6 months of therapy based on the change in 28 joints Disease Activity Score (∆DAS28); patients with ∆DAS28 > 1.2 were considered responders.
Results In all three cohorts, we consistently observed suppression of IRG expression in patients using prednisone compared to patients that were not using prednisone. The suppression appeared to be dose-dependent as it was most pronounced in the highest dose-range (>10 mg/day). In the rituximab cohort, separate ROC analysis on PREDN- patients alone revealed improved prediction of non-response to rituximab based on baseline IRG expression, with an AUC of 0.969 compared to 0.848 when analysed in all patients, whereas prednisone use itself had no predictive value in this cohort. Using a group-specific IFN-score-cutoff for all patients and PREDN- patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity.
Conclusion Because of prednisone-related suppression of the IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN- patients. These results suggest that the IFN-score-based rituximab response prediction modell could be improved upon implementation of prednisone use.
Disclosure CLV is an inventor on a patent wherein the predictive value of IFN type I response activity for the prediction of the clinical outcome of B cell depletion therapy via rituximab is claimed. CLV, SV and TdJ are inventors on a patent application wherein the use of the information on the interference of GCs to modulate the IFN system to improve outcome predictions on the use of biologics such as rituximab in chronic inflammatory and other conditions is claimed