Joeri W van Straalen1, Gabriella Giancane2,3, Yasmine Amazrhar1, Nikolay Tzaribachev4, Calin Lazar5, Yosef Uziel6,7, Albena Telcharova-Mihaylovska8, Claudio A Len9, Angela Miniaci10, Alina L Boteanu11, Giovanni Filocamo12, Mariel V Mastri13, Thaschawee Arkachaisri14,15, Maria G Magnolia16, Esther Hoppenreijs17, Sytze de Roock1, Nico M Wulffraat1, Nicolino Ruperto2, Joost F Swart1. 1. Department of Pediatric Immunology and Rheumatology, Wilhelmina Children's Hospital, Utrecht, Netherlands. 2. Clinica Pediatrica e Reumatologia, IRCCS Istituto Giannina Gaslini, Genoa, Italy. 3. Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno-Infantili (DiNOGMI), Università degli Studi di Genova, Genoa, Italy. 4. Pediatric Rheumatology Research Institute, Bad Bramstedt, Germany. 5. Pediatrics, Spitalul Clinic de Urgenta pentru Copii, Cluj-Napoca, Romania. 6. Department of Pediatrics, Pediatric Rheumatology Unit, Meir Medical Center, Kfar Saba, Israel. 7. Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. 8. Department of Paediatric Rheumatology, University Children's Hospital, Sofia, Bulgaria. 9. Pediatrics Department, Universidade Federal de São Paulo, Sao Paulo, Brazil. 10. Salute della Donna, del Bambino e dell'Adolescente-Padiglione 16 Ambulatorio di reumatologia, Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna, Italy. 11. Pediatric Rheumatology Unit, University Hospital Ramón y Cajal, Madrid, Spain. 12. Pediatric Rheumatology, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milan, Italy. 13. Unidad de Reumatologia, Hospital Sor Maria Ludovica, La Plata, Argentina. 14. Rheumatology and Immunology Service, Department of Paediatric Subspecialties, KK Women's and Children's Hospital, Singapore. 15. Duke-NUS Medical School, Singapore. 16. Paediatrics, Santa Maria della Stella Hospital, Ciconia, Orvieto (TR), Italy. 17. Pediatric Rheumatology, Radboud University Medical Center/Sint Maartenskliniek, Nijmegen, Netherlands.
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.
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.
Authors: Mikhail M Kostik; Ekaterina V Gaidar; Lubov S Sorokina; Ilya S Avrusin; Tatiana N Nikitina; Eugenia A Isupova; Irina A Chikova; Yuri Yu Korin; Elizaveta D Orlova; Ludmila S Snegireva; Vera V Masalova; Margarita F Dubko; Olga V Kalashnikova; Vyacheslav G Chasnyk Journal: Front Pediatr Date: 2022-06-15 Impact factor: 3.569