FRI0104 Predictors for the response to anti-tnf therapy and the impact of smoking in rheumatoid arthritis- results on a group of patients in romania. (12th June 2018)

• Record Type: Journal Article
• Authors: Gavrila, B.I.; Ciofu, C.S.; Macovei, L.; Gheorghiu, A.M.; Sasu, M.; Mihai, C.; Stoica, V.; Ancuta, I.; Bojinca, M.
• Is Part Of: Annals of the rheumatic diseases. Volume 77(2018)Supplement 2
• Page Start: 596
• Page End: 597
• Publication Date: 2018-06-12
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2018-eular.5690
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: 20%–40% of the patients are declared nonresponders to at least one of the biologic agents. Objectives: to test the possible predictive role of RF type IgM and IgA, anti-CCP, anti-MCV, 14–3–3eta protein and COMP on a group of patients treated with anti-TNFα agents. We also followed the evolution of serum titres of these biomarkers under biologic therapy and the impact of smoking regarding response to treatment. Methods: prospective and observational study including 64 patients followed 12 months with active RA, uncontrolled by csDMARDs. Clinical assessment was performed at 0, 6 and 12 months according to ACR criteria and evaluation of treatment response according to EULAR criteria (good/moderate/nonresponder). Results: Following baseline immunological parameters titres and the response at 6 months, tests for identifying differences between the groups showed that lower titres of both RF isotypes, anti-CCP, 14–3–3eta protein and COMP had predictive value on achieving a good EULAR response at 6 months. Grouping patients in 2 categories (responders/nonresponders), just 14–3–3eta protein and anti-CCP maintained their predictive value for the response at 6 months. For the visit at 12 months, lower baseline titres for RF type IgM (92.93±120.22 U/ml, p=0.010) and IgA (49.96±98.08 U/ml, p=0.002) had predictive value for achieving a good response at 12 months. We didn't obtain other informations grouping patients in 2 categories. The status pretreatment influenced the good response for COMP at 6 months (p=0.001) and RF IgA at 12 months (p=0.004). Using multivariate logistic regression methods we obtained a statistical model for predicting the response at 6 months including normal values for 14–3–3eta protein, anti-CCP and COMP (Hosmer and Lemeshow according test λ²=5.795, p=0.670≥0.05 with a predictive response accuracy of 89.1%). Smoking had a negative impact on the EULAR response as well as on 2 groups respose at 6 months of treatment (p=0.017). Following the evolution of serum levels, we noticed a reduction for all biomarkers tested, statistically significant at 6 and/or 12 months from baseline. Conclusions: in the future a version using multiple biomarkers could increase accuracy for identifying pretreatment patients who will respond to anti-TNF therapy. Smoking has a negative impact on the response to biologic treatment. Disclosure of Interest: None declared