Development and external validation of a model predicting new-onset chronic uveitis at different disease durations in juvenile idiopathic arthritis

Objective
To develop and externally validate a prediction model for chronic uveitis in children with juvenile idiopathic arthritis (JIA) for clinical application.

Methods
Data from the international Pharmachild register were used to develop a multivariable Cox proportional hazards model. Predictors were selected by backward selection and missing values were handled by multiple imputation. The model was subsequently validated and recalibrated in two inception cohorts: the UK CAPS study and German ICON study. Model performance was evaluated by calibration plots and C-statistics for the 2, 4 and 7-year risk of uveitis. A diagram and digital risk calculator were created for use in clinical practice.

Results
5393 patients were included for model development and predictor variables were age at JIA onset (HR: 0.83, 95% CI: 0.77 – 0.89), ANA positivity (HR: 1.59, 95% CI: 1.06 – 2.38) and ILAR category (HR for oligoarticular, psoriatic and undifferentiated arthritis versus RF- polyarthritis: 1.40, 95% CI: 0.91 – 2.16). Performance of the recalibrated prediction model in the validation cohorts was acceptable: calibration plots indicated good calibration and C statistics for the 7-year risk of uveitis were 0.75 (95% CI: 0.72 – 0.79) for ICON and 0.70 (95% CI: 0.64 – 0.76) for CAPS.

Conclusion
We present for the first time a validated prognostic tool for easily obtaining individual chronic uveitis risks for JIA patients using common clinical parameters. This model could be used by clinicians to inform patients/parents and provide guidance in choice of uveitis screening frequency and arthritis drug therapy.