Results from a recent study indicate that an IFN-score based model to predict the clinical outcome of rituximab treatment can be optimized with the employment of prednisone use. The study titled “Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab,” is published in the current issue of the journal Arthritis Research & Therapy.
Rheumatoid arthritis (RA) is a systemic autoimmune disease that causes chronic joint inflammation which may lead to cartilage and bone destruction. Patients with RA often receive immunosuppressive treatment with non-biologic disease modifying anti-rheumatic drugs (DMARDs) and/or glucocorticoids (GCs). However, when patients no longer benefit from the non-biologic therapy, they are usually prescribed with biologics, such as TNFα-blockers and B-cell depletion therapy using rituximab (RTX).
Elevated type I interferon (IFN) response gene (IRG) expression has been found to predict rituximab non-response in RA. Interference between glucocorticoids (GCs) and type I IFN signaling has also been determined in in vitro models. Because the use and dose of GC are inconstant in RA patients before they start treatment with rituximab, in order to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA, Tamarah de Jong from the Department of Pathology, VU University Medical Center in The Netherlands and colleagues examined three groups of RA patients: 182 and 32 biologic-free and 40 RA patients starting rituximab.
The researchers observed suppression of IFN-score in patients using prednisone (PREDN+ ) in comparison to non-users (PREDN− ). Results revealed that in the rituximab cohort, analysis of 13 PREDN− patients showed a improvement in the prediction of rituximab non-response based on baseline IFN-score of 0.975 compared to 0.848 in all patients under rituximab. The research team also found that using a group-specific IFN-score cut-off for all patients and PREDN− patients only, the sensitivity improved from 41% to 88%, respectively, with a specificity of 100%.
Based on the results, the researcher team indicated in their study that type I IFN activity in RA patients is suppressed in prednisone users. Findings strongly suggest that IFN-score based model to predict the clinical outcome of rituximab treatment can be optimized with the application of prednisone use.
