SAT0628 VALIDATION OF METHODS FOR PREDICTING LONG-TERM OUTCOME IN JUVENILE IDIOPATHIC ARTHRITIS: RESULTS FOR CANADIAN AND NORDIC PREDICTION MODELS IN THE NORDIC COHORT
Authors: Veronika Rypdal, Jaime Guzman, Andrew Henrey, Thomas Loughin, Mia Glerup, Anders Fasth, Ellen Dalen Arnstad, Lillemor Berntson, Susan Nielsen, Marek Zak, Marite Rygg, Kristiina Aalto, Troels Herlin, Martin Rypdal, Ellen Nordal
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background</h3> Models predicting outcome in juvenile idiopathic arthritis (JIA) have recently been proposed by Guzman <i>et al</i><i>.</i><sup>1</sup> and Rypdal <i>et al.</i><sup>2</sup> Guzman <i>et al</i><i>.</i> constructed a model for predicting severe disease course derived from the ReACCh-Out study, and Rypdal <i>et al</i><i>.</i> constructed models for prediction of non-remission, functional disability and joint damage. <h3>Objectives</h3> To validate methods for prediction of long-term outcome in JIA by testing the ability of Guzman’s model and Rypdal’s model to predict severe disease course (the ReACCh-Out outcome) in the Nordic cohort. <h3>Methods</h3> The Nordic cohort is a prospective longitudinal multicenter cohort from defined geographical areas of 4 Nordic countries. Children with a baseline and an 8-year study visit were included. Missing data were imputed using low rank matrix factorization<sup>3</sup>, and a K-medoids algorithm<sup>4</sup> was used to identify clusters corresponding to severe disease course in the ReACCh-Out study. With this outcome, the prediction model of Guzman <i>et al</i><i>.</i> was tested with no re-estimation of parameters. A Receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were computed. For the same outcome, prediction models were built using the method of Rypdal <i>et al</i><i>.</i> on randomly sampled training sets, and tested on disjoint validation sets. <h3>Results</h3> In the Nordic cohort 98/440 (22%) patients were identified with a severe disease course. This ratio is similar to the 125/610 (20%) found in the ReACCh-Out study. Characteristics of groups of patients with severe and non-severe disease course are similar in the two cohorts. The model of Guzman <i>et al</i><i>.</i> had an AUC of 0.85 for prediction of severe disease course and an AUC of 0.66 for predicting remission off medication. In repeated cross-validations, the model of Rypdal <i>et al</i><i>.</i> had a median AUC of 0.90 (IQR 0.86-0.92) for prediction of severe disease course, and a median AUC of 0.78 (IQR 0.72–0.82) for remission off medication. <h3>Conclusion</h3> Tests in the Nordic cohort validate the ability of the model of Guzman <i>et al</i><i>.</i> to predict severe disease course. Repeated cross-validations of the model of Rypdal <i>et al</i><i>.</i> indicate that validation results are highly dependent of the chosen outcome, and that prediction of long-term remission status is more challenging than prediction of a severe disease course. <h3>References</h3> [1] Guzman, J. et al., Predicting Which Children with Juvenile Idiopathic Arthritis Will Have a Severe Disease Course: Results from the ReACCh-Out Cohort, J Rheumatol, 44, 230-240, 2017. [2] Rypdal, V. et al., Predicting unfavorable long-term outcome in juvenile idiopathic arthritis: results from the Nordic cohort study, Arthritis Res Ther, 20, 91, 2018. [3] Liu, G. et al., Robust subspace segmentation by low-rank representation, Proceedings of the 27th International Conference on International Conference on Machine Learning, 663-670, 2010. [4] Park, H.-S. et al., A simple and fast algorithm for K-medoids clustering, Expert Systems with Applications, 36, 3336-3341, 2009. <h3>Disclosure of Interests</h3> Veronika Rypdal: None declared, Jaime Guzman: None declared, Andrew Henrey: None declared, Thomas Loughin: None declared, Mia Glerup: None declared, Anders Fasth: None declared, Ellen Dalen Arnstad: None declared, Lillemor Berntson Consultant for: AbbVie, Speakers bureau: AbbVie, Susan Nielsen: None declared, Marek Zak: None declared, Marite Rygg: None declared, Kristiina Aalto: None declared, Troels Herlin: None declared, Martin Rypdal: None declared, Ellen Nordal: None declared