Volume 11 Supplement 2
PReS-FINAL-2162: Development of a risk model to predict methotrexate intolerance in juvenile idiopathic arthritis
© Van Dijkhuizen et al.; licensee BioMed Central Ltd. 2013
Published: 5 December 2013
Methotrexate (MTX) is a cornerstone and safe disease-modifying anti-rheumatic drug (DMARD) in the treatment of juvenile idiopathic arthritis (JIA). Despite its safety, MTX intolerance occurs frequently, leading to non-compliance, thus hampering efficacy and potentially leading to early discontinuation.
The aim of this study was to construct a risk model to predict MTX intolerance.
In a large, prospective JIA cohort, potential predictors (clinical variables and single nucleotide polymorphisms) were determined at the time of MTX start. The Methotrexate Intolerance Severity Score was employed to measure MTX intolerance in the first year of treatment. MTX intolerance was most prevalent at 6 or 12 months after MTX start. This was defined as the outcome for the prediction model. The model was developed in 152 patients using multivariate logistic regression analysis. It was subsequently internally validated using bootstrapping.
The prediction model included the following predictors: JIA subtype, antinuclear antibody, parent/patient assessment of pain, Juvenile Arthritis Disease Activity Score-27, thrombocytes, alanine aminotransferase and creatinine. The model classified 77.5% of patients correctly, changing to 66.7% after internal validation by bootstrapping. The prediction model was transformed into a risk score (range 0-17). At an optimal cut-off of ≥6, sensitivity was 82.0%, specificity 56.1%, positive predictive value was 58.7% and negative predictive value 80.4%.
The prediction model combined routine clinical variables and showed good predictive power to detect MTX intolerance. This easy-to-use tool could assist clinicians in identifying patients at risk to develop MTX intolerance. Consequently, clinicians can monitor them closely and intervene timely before MTX intolerance hampers MTX efficacy.
Disclosure of interest
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.