首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab
Authors:Tamarah D de Jong  Saskia Vosslamber  Marjolein Blits  Gertjan Wolbink  Mike T Nurmohamed  Conny J van der Laken  Gerrit Jansen  Alexandre E Voskuyl  Cornelis L Verweij
Institution:Department of Pathology, VU University Medical Center, P.O. Box 7075, 1007 MB Amsterdam, The Netherlands ;Department of Rheumatology, VU University Medical Center, Amsterdam, The Netherlands ;Jan van Breemen Institute | Reade, Amsterdam, The Netherlands
Abstract:IntroductionElevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are highly variable among patients before rituximab treatment, the aim of this study was to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA.MethodsIn two independent cohorts of 32 and 182 biologic-free RA patients and a third cohort of 40 rituximab-starting RA patients, peripheral blood expression of selected IRGs was determined by microarray or quantitative real-time polymerase chain reaction (qPCR), 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) analysis in the rituximab cohort. Patients with a decrease in disease activity score (∆DAS28) >1.2 after 6 months of rituximab were considered responders.ResultsWe consistently observed suppression of IFN-score in prednisone users (PREDN+) compared to non-users (PREDN). In the rituximab cohort, analysis on PREDN patients (n = 13) alone revealed improved prediction of rituximab non-response based on baseline IFN-score, with an area under the curve (AUC) of 0.975 compared to 0.848 in all patients (n = 40). Using a group-specific IFN-score cut-off for all patients and PREDN patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity.ConclusionsBecause of prednisone-related suppression of IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN patients. These results suggest that the IFN-score-based rituximab response prediction model could be improved upon implementation of prednisone use.
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号