A clinical prediction model for estimating the risk of developing uveitis in patients with juvenile idiopathic arthritis

Abstract Objective To build a prediction model for uveitis in children with JIA for use in current clinical practice. Methods Data from the international observational Pharmachild registry were used. Adjusted risk factors as well as predictors for JIA-associated uveitis (JIA-U) were determined using...

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Published in:	Rheumatology (Oxford, England) Vol. 60; no. 6; pp. 2896 - 2905
Main Authors:	van Straalen, Joeri W, Giancane, Gabriella, Amazrhar, Yasmine, Tzaribachev, Nikolay, Lazar, Calin, Uziel, Yosef, Telcharova-Mihaylovska, Albena, Len, Claudio A, Miniaci, Angela, Boteanu, Alina L, Filocamo, Giovanni, Mastri, Mariel V, Arkachaisri, Thaschawee, Magnolia, Maria G, Hoppenreijs, Esther, de Roock, Sytze, Wulffraat, Nico M, Ruperto, Nicolino, Swart, Joost F
Format:	Journal Article
Language:	English
Published:	Oxford University Press 18-06-2021
Subjects:	Clinical Science risk factors JIA prediction model uveitis confounders
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Summary:	Abstract Objective To build a prediction model for uveitis in children with JIA for use in current clinical practice. Methods Data from the international observational Pharmachild registry were used. Adjusted risk factors as well as predictors for JIA-associated uveitis (JIA-U) were determined using multivariable logistic regression models. The prediction model was selected based on the Akaike information criterion. Bootstrap resampling was used to adjust the final prediction model for optimism. Results JIA-U occurred in 1102 of 5529 JIA patients (19.9%). The majority of patients that developed JIA-U were female (74.1%), ANA positive (66.0%) and had oligoarthritis (59.9%). JIA-U was rarely seen in patients with systemic arthritis (0.5%) and RF positive polyarthritis (0.2%). Independent risk factors for JIA-U were ANA positivity [odds ratio (OR): 1.88 (95% CI: 1.54, 2.30)] and HLA-B27 positivity [OR: 1.48 (95% CI: 1.12, 1.95)] while older age at JIA onset was an independent protective factor [OR: 0.84 (9%% CI: 0.81, 0.87)]. On multivariable analysis, the combination of age at JIA onset [OR: 0.84 (95% CI: 0.82, 0.86)], JIA category and ANA positivity [OR: 2.02 (95% CI: 1.73, 2.36)] had the highest discriminative power among the prediction models considered (optimism-adjusted area under the receiver operating characteristic curve = 0.75). Conclusion We developed an easy to read model for individual patients with JIA to inform patients/parents on the probability of developing uveitis.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Dr Joost F. Swart and Dr Nicolino Ruperto contributed equally to this paper.
ISSN:	1462-0324 1462-0332
DOI:	10.1093/rheumatology/keaa733