THU0140 Plasma Adiponectin Level and Body Mass Index (BMI) Predict Response to Treatment in Patients with Rheumatoid Arthritis

• Published in: Annals of the rheumatic diseases Vol. 72; no. Suppl 3; p. A210
• Main Authors: Xibille, D. X., Hernández Góngora, S. E., Bustos Bahena, C., Ortíz Panozo, E., Montiel Hernandez, J. L.
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd and European League Against Rheumatism 01.06.2013; BMJ Publishing Group LTD
• ISSN: 0003-4967; 1468-2060
• DOI: 10.1136/annrheumdis-2013-eular.668

Background Obesity is a low-grade inflammatory state and plays a role in several chronic inflammatory diseases. Elevated adiponectin levels, a white fatty tissue derived adipokine involved in metabolism and inflammation, has been associated with clinically effective DMARD treatment, increasing in patients under methotrexate treatment1. We have found higher adiponectin levels in patients with RA compared to healthy controls, independent of BMI2. Predictors of response to treatment in RA are important tools in profiling treatments to fit patient needs, following a treat to target strategy. Objectives To determine whether baseline levels of adipokines adiponectin and leptin and body mass index (BMI) predict short, medium and long response to DMARD treatment in patients with RA. Methods A cohort of patients with RA followed at the Rheumatology department were sampled at the baseline visit for leptin, adiponectin and ACPA and followed for two years. Demographic data such as age, gender, BMI, time since onset of disease, RF, CRP, ESR and DAS28, measured at each visit (every 3 months) was also collected as part of our RA database. All patients received prednisone (10 mg or less/day) and combination therapy with DMARD, mostly MTX). EULAR response criteria were used for outcome measurement3. Descriptive statistics where employed for demographic data and multinomial logistic regression were employed to determine predictive factors of response to treatment, defined using changes in DAS28 over time according to established criteria. A p<0.05 was considered statistically significant. Results Out of 213 active patients we followed 154 for 6 months (short term), 101 for one year (medium term and 61 for two years (long term). 97.2% of all patients included at baseline were women. Mean age was 46.1 years (18-70), mean time since onset of disease was 8.3 years (0-38) and mean BMI was 27.19 (16.5-46.6). 89.6% were RF positive and 71% were ACPA positive. Most of the patients received combination therapy, including at least 2 DMARDs (72.7%), methotrexate being the most commonly employed; 16,9% was receiving MTX monotherapy and 10.4% received only steroids and/or NSAID. No patient was receiving biologic therapy. Mean serum leptin was 0,57 ± 0,5 ng/ml and mean serum adiponectin was 140.5 ± 90,3 ng/ml. Logistical regression analysis showed that elevated baseline adiponetin predicted a positive short term (6 months) response to treatment; these patients were significantly (p 0.01) more likely to have a good response to treatment than patients with lower levels. Patients with higher BMI were significantly more likely to have a poor response to treatment in the long term (2 years). An elevated BMI correlated with poor long-term response to treatment (p = 0.03). Conclusions Elevated levels of adiponectin at baseline predicted a better response to treatment in the short term. A greater baseline body mass index was associated with a poor response to treatment after 2 years of follow up. References Laurberg, et al. 2009. J Rheum. 36:1885 Xibille-Friedmann, D. et al. 2010. Ann Rheum. Dis. 69:930 Van Gestel, et al. 1996. Arthritis Rheum. 39:31 Disclosure of Interest None Declared