Abstract：
Aim: This research aimed to construct a clinical model for forecasting the likelihood of lung metastases in differentiated thyroid carcinoma (DTC) with intermediate- to high-risk. Methods: In this study, 375 DTC patients at intermediate to high risk were included. They were randomly divided into a training set (70%) and a validation set (30%). A nomogram was created using the training group and then validated in the validation set using calibration, decision curve analysis (DCA) and receiver operating characteristic (ROC) curve. Results: The calibration curves demonstrated excellent consistency between the predicted and the actual probability. ROC analysis showed that the area under the curve in the training cohort was 0.865 and 0.845 in the validation cohort. Also, the DCA curve indicated that this nomogram had good clinical utility. Conclusion: A user-friendly nomogram was constructed to predict the lung metastases probability with a high net benefit.
[Box: see text].
[Box: see text].
摘要：
目的：本研究旨在建立一个预测中高风险分化型甲状腺癌（DTC）肺转移可能性的临床模型。方法:在本研究中,包括375名处于中危至高危的DTC患者。他们被随机分为训练集（70％）和验证集（30％）。使用训练组创建列线图，然后使用校准在验证集中进行验证，决策曲线分析(DCA)和接受者工作特性曲线(ROC)。结果：校准曲线显示出预测概率和实际概率之间的良好一致性。ROC分析显示，训练队列的曲线下面积为0.865，验证队列为0.845。此外，DCA曲线表明该列线图具有良好的临床实用性.结论：构建了一个用户友好的列线图来预测具有高净效益的肺转移概率。
[方框：见正文]。
[方框：见正文]。
