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中高危分化型甲状腺癌患者肺转移预测列线图的开发与验证

Development and validation of a lung metastases-predicting nomogram for intermediate- to high-risk differentiated thyroid carcinoma patients.

作者信息

Ma Wenhui, Yu Feng, Chen Bowen, Yang Zhiping, Kang Fei, Li Xiang, Yang Weidong, Wang Jing

机构信息

Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, No. 127, Changle West Road, Xi'an, 710000, Shaanxi, China.

出版信息

Future Oncol. 2024;20(22):1575-1586. doi: 10.1080/14796694.2024.2354161. Epub 2024 Jun 13.

Abstract

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. 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. 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. A user-friendly nomogram was constructed to predict the lung metastases probability with a high net benefit.

摘要

本研究旨在构建一个临床模型,用于预测中高危分化型甲状腺癌(DTC)发生肺转移的可能性。本研究纳入了375例中高危DTC患者。他们被随机分为训练集(70%)和验证集(30%)。使用训练组创建了一个列线图,然后在验证集中使用校准、决策曲线分析(DCA)和受试者工作特征(ROC)曲线进行验证。校准曲线显示预测概率与实际概率之间具有极佳的一致性。ROC分析表明,训练队列中的曲线下面积为0.865,验证队列中的曲线下面积为0.845。此外,DCA曲线表明该列线图具有良好的临床实用性。构建了一个用户友好的列线图,以预测具有高净效益的肺转移概率。

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