Albarouni, Mohamed Ayoub: Predictors of response to methotrexate in juvenile idiopathic arthritis patients. - Bonn, 2014. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
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author = {{Mohamed Ayoub Albarouni}},
title = {Predictors of response to methotrexate in juvenile idiopathic arthritis patients},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2014,
month = dec,

note = {Objectives. To determine predictors for response to treatment with methotrexate in juvenile idiopathic arthritis patients.
Methods. Demographic, clinical, articular and laboratory variables of patients newly treated with methotrexate were analysed by bivariate and logistic regression analysis to identify predictors of response to methotrexate. Minimal response was defined by the American College of Rheumatology pediatric (PedACR) 30 and strong response by the PedACR 70 criteria.
Results. The total patient population consisted of 915 patients. At month 3, 77.4% and at month 12 83.1% of patients were responders according to the PedACR 30 criteria, while 43.1% and 65.9% of patients had a PedACR 70 response at month 3 and at month 12. Thus minimal response was frequently already reached at month 3 while strong response to MTX treatment took usually longer to achieve.
In multivariate analysis the number of tender joints (p=0.003), active joints (p<0.001) and the parents evaluation of overall well-being (p<0.001) were significant baseline parameters for minimal response at month 3, while at month 12 the determinants for reaching PedACR 70 were a disease duration < 1 year (p =0.001), a lower age at MTX start (p <0.001), a lower number of tender (p =0.004) but a higher number of active joints (p <0.001), a higher score of the parent’s evaluation of child’s pain (p =0.037), a higher score of CRP value (p =0.018) and the presence of morning stiffness (p =0.016).
Conclusion. Baseline parameters for minimal response after 3 months of treatment and strong response after 12 months of treatment could be identified. The disease duration and parameters defining activity and severity of disease were influencing factors. Overall the model of prediction could support physicians in making treatment decisions.},

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