AB0950 Predictors of response to etanercept treatment depending on juvenile idiopathic arthritis category. (15th June 2017)

• Record Type: Journal Article
• Authors: Kashchenko, E; Alexeeva, E; Bzarova, T; Valieva, S; Denisova, R; Lomakina, O; Isaeva, K; Soloshenko, M; Karaseva, A
• Is Part Of: Annals of the rheumatic diseases. Volume 76(2017)Supplement 2
• Page Start: 1387
• Page End: 1387
• Publication Date: 2017-06-15
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2017-eular.3918
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Anti-TNF biologics are highly effective and widely used in clinical practice for the treatment of JIA. However, some children lack of response with few reliable predictors of a good or poor response to treatment found [1–3]. As clinical picture patterns are significantly differ for 7 JIA subclasses, we propose to found predictors of response to therapy for each of JIA category. Objectives: To identify clinical and laboratory parameters associated with response to etanercept treatment in 12 months in patients with different JIA category. Methods: Patients from four JIA categories (n=195) were divided to groups with excellent, intermediate and poor response after 12 month treatment with etanercept according to ACRPedi criteria, achieving inactive disease by Wallace criteria and JADAS-71 cut-off point. For each of JIA category univariate and multivariate logistic regression analysis was conducted to identify potential baseline factors associated with treatment response. Baseline factors included clinical, laboratory and anamnestic data. Results: From total cohort 91/90/85/68.5 percent of patients achieved ACR30/50/70/90 in one year etanercept treatment; 45.5% patients were considered excellent responders, 30% - intermediate responders, and 24.5% - poor responders. Highest efficacy of therapy was shown in persistent oligoarthritis patient, lowest – in enthesitis-related arthritis and polyarthritis patients. Potential baseline predictors of excellent and poor response which were significant are described in the table. Analysis showed that poor response in all JIA categories was mainly associated with demographic data (longer DD and older ADO). However, factors associated with excellent response significantly differed depending on JIA category (anamnestic factors, number of involved joints, laboratory factors, and demographic factors). Conclusions: Response to etanercept therapy is strongly associated with JIA category. Shorter disease duration and lower number of DMARDs used before start of etanercept, lower number of joints with LOM, and lower C-reactive protein at baseline are predictors of better response to etanercept. References: Otten MH, et al. JAMA 2011;306:2340–7. Kearsley-Fleet L, et al. Rheumatology (Oxford) 2016;55:840–7. Solari N, et al. J Rheumatol 2013;40:192–200. Disclosure of Interest: E. Kashchenko Grant/research support from: Novartis, E. Alexeeva Grant/research support from: Roche, Abbott, Pfizer, Bristol-Myers Squibb, Centocor, Novartis, Speakers bureau: Roche, Merck Sharp & Dohme, Abbott, Bristol-Myers Squibb, Medac, Novartis, Pfizer, T. Bzarova Grant/research support from: Roche, Pfizer, Novartis, Speakers bureau: Roche, Merck Sharp & Dohme, Abbott, Pfizer, S. Valieva Grant/research support from: Roche, Bristol-Myers Squibb, Speakers bureau: Roche, Merck Sharp & Dohme, Bristol-Myers Squibb, Medac, Novartis, R. Denisova Grant/research support from: Roche, Centocor, Novartis, Speakers bureau: Roche, Merck Sharp & Dohme, Abbott, Medac, O. Lomakina: None declared, K. Isaeva Grant/research support from: Roche, Novartis, M. Soloshenko: None declared, A. Karaseva: None declared