Purpose

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 in years (HR: 0.83, 95% CI: 0.77 – 0.89), ANA status(0 = negative and 1 = positive, HR: 1.59, 95% CI: 1.06 – 2.38) and ILAR category (oligoarticular, psoriatic or undifferentiated arthritis = 1 and RF- polyarthritis = 0, HR: 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. The model formula for calculating the 7-year risk of uveitis is: 1 - 0.90^exp(0.46*ANA status - 0.19*age at JIA onset + 0.34*ILAR category + 0.71).

Conclusions

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.