Predictors of response to methotrexate in juvenile idiopathic arthritis
1 Centre of Paediatric Rheumatology, Department of General Paediatrics, Asklepios Klinik Sankt Augustin, Arnold-Janssen Str. 29, D-53757 Sankt Augustin, Germany
2 Institute of Medical Statistics, Informatics and Epidemiology, University of Cologne, Cologne, Germany
Pediatric Rheumatology 2014, 12:35 doi:10.1186/1546-0096-12-35Published: 13 August 2014
The response to methotrexate so far is unpredictable in patients with juvenile idiopathic arthritis. Thus such predictors have to be determined in a large patient cohort.
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.
The patient population consisted of 731 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 = 0.002), active joints (p < 0.001), concomitant use of NSAID (p = 0.027) 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 number of tender (p <0.001) but a higher number of active joints (p <0.001), a higher score of the parent’s evaluation of child’s pain (p =0.029), and the presence of morning stiffness (p =0.014).
Baseline parameters for minimal response after 3 months of treatment and strong response after 12 months of treatment could be identified. Beside parameters defining activity and severity of disease, the disease duration and the concomitant use of NSAID were influencing factors. Overall the model of prediction could support physicians in making treatment decisions.