Models to predict disease course and long-term outcome based on clinical characteristics at disease onset may guide early treatment strategies in juvenile idiopathic arthritis (JIA). Before a prediction model can be recommended for use in clinical practice, it needs to be validated in a different cohort than the one used for building the model. The aim of the current study was to validate the predictive performance of the Canadian prediction model developed by Guzman et al. and the Nordic model derived from Rypdal et al. to predict severe disease course and non-achievement of remission in Nordic patients with JIA. The Canadian and Nordic multivariable logistic regression models were evaluated in the Nordic JIA cohort for prediction of non-achievement of remission, and the data-driven outcome denoted severe disease course. A total of 440 patients in the Nordic cohort with a baseline visit and an 8-year visit were included. The Canadian prediction model was first externally validated exactly as published. Both the Nordic and Canadian models were subsequently evaluated with repeated fine-tuning of model coefficients in training sets and testing in disjoint validation sets. The predictive performances of the models were assessed with receiver operating characteristic curves and C-indices. A model with a C-index above 0.7 was considered useful for clinical prediction. The Canadian prediction model had excellent predictive ability and was comparable in performance to the Nordic model in predicting severe disease course in the Nordic JIA cohort. The Canadian model yielded a C-index of 0.85 (IQR 0.83–0.87) for prediction of severe disease course and a C-index of 0.66 (0.63–0.68) for prediction of non-achievement of remission when applied directly. The median C-indices after fine-tuning were 0.85 (0.80–0.89) and 0.69 (0.65–0.73), respectively. Internal validation of the Nordic model for prediction of severe disease course resulted in a median C-index of 0.90 (0.86–0.92). External validation of the Canadian model and internal validation of the Nordic model with severe disease course as outcome confirm their predictive abilities. Our findings suggest that predicting long-term remission is more challenging than predicting severe disease course.

中文翻译：

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幼年特发性关节炎的严重疾病进程和未实现缓解的预测模型的验证：北欧队列中加拿大模型的第1部分结果。

基于疾病发作时的临床特征预测疾病进程和长期结果的模型可指导青少年特发性关节炎（JIA）的早期治疗策略。在将推荐模型推荐用于临床实践之前，需要在与用于构建模型的模型不同的队列中对其进行验证。本研究的目的是验证Guzman等人开发的加拿大预测模型的预测性能。和来自Rypdal等人的北欧模型。预测北欧JIA患者的严重病程和未实现缓解。在北欧JIA队列中评估了加拿大和北欧多变量logistic回归模型，以预测未实现缓解，并且数据驱动的结果表明病情严重。北欧队列中总共有440名患者进行了基线访视和8年访视。加拿大的预测模型首先在外部完全按照公布的方式进行了验证。随后对北欧和加拿大模型进行了评估，对训练集中的模型系数进行了反复的微调，并在不相交的验证集中进行了测试。使用接收器工作特性曲线和C指标评估模型的预测性能。C指数高于0.7的模型被认为可用于临床预测。加拿大的预测模型具有出色的预测能力，在预测北欧JIA队列中的严重病程方面，其性能可与北欧模型相媲美。加拿大模型的C指数为0.85（IQR 0.83–0.87），用于预测严重病程，C指数为0.66（0。63–0.68）预测直接应用时未实现的缓解。微调后的C指数中位数分别为0.85（0.80-0.89）和0.69（0.65-0.73）。北欧模型对严重疾病进程的预测的内部验证导致中位C指数为0.90（0.86-0.92）。加拿大模型的外部验证和北欧模型的内部验证具有严重的病程，因为结局证实了其预测能力。我们的发现表明，预测长期缓解远比预测严重疾病进程更具挑战性。北欧模型对严重疾病进程的预测的内部验证导致中位C指数为0.90（0.86-0.92）。加拿大模型的外部验证和北欧模型的内部验证具有严重的病程，因为结局证实了其预测能力。我们的发现表明，预测长期缓解远比预测严重疾病进程更具挑战性。北欧模型对严重疾病进程的预测的内部验证导致中位C指数为0.90（0.86-0.92）。加拿大模型的外部验证和北欧模型的内部验证具有严重的病程，因为结局证实了其预测能力。我们的发现表明，预测长期缓解远比预测严重疾病进程更具挑战性。