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基于临床与超声特征构建的列线图模型在超声医师修饰甲状腺中国(超声)甲状腺影像报告和数据系统分类结果中的应用价值

Application value of a Nomogram model established on clinical and ultrasound features in modifying classification results of the Chinese Thyroid Imaging Reporting and Data System by ultrasound physicians

    摘要
  • 摘要:
    目的 分析基于甲状腺临床与超声特征构建的列线图模型在超声医师修饰甲状腺中国(超声)甲状腺影像报告和数据系统(C-TI-RADS)分类结果中的应用价值。
    方法 回顾性分析2021年1月—2022年12月四川省人民医院(训练集, n=841)以及四川绵阳四0四医院(外部验证集, n=295)外科手术切除的甲状腺结节患者的临床病理及超声资料, 并利用术前甲状腺超声进行甲状腺结节C-TI-RADS分类。通过单因素及多因素Logistic回归分析在训练集中筛选独立预测因子并构建列线图模型，通过Bootstrap重抽样进行内部验证; 四川绵阳四0四医院超声医师根据构建的列线图模型进行外部验证。绘制受试者工作特征(ROC)曲线及校准曲线，评估模型效能及在超声医师修饰C-TI-RADS分类结果中的临床价值。
    结果 单因素及多因素Logistic回归分析结果显示，性别、年龄、结节最大径、结节数目、颈部淋巴结超声异常和C-TI-RADS分类是预测超声医师修饰C-TI-RADS分类结果的独立因素(P < 0.05)。基于上述因素构建的列线图模型的一致性指数为0.842(95%CI: 0.816~0.867), 曲线下面积(AUC)为0.842, 基于最佳截断值的敏感度为92.9%, 特异度为63.7%, 准确率为75.9%。在训练集和外部验证集中，构建的列线图模型的预测结果与实际情况均具有较好的一致性。
    结论 基于甲状腺临床与超声特征构建的列线图模型在超声医师修饰C-TI-RADS分类结果中显示出良好的预测准确性，具有潜在的临床应用价值。

     

    Abstract:
    Objective To analyze the application value of a Nomogram model established on clinical and ultrasound features of thyroid in modifying classification results of the Chinese Thyroid Imaging Reporting and Data System (C-TI-RADS) by ultrasound physicians.
    Methods The clinicopathological ultrasound materials of patients with surgical resection for thyroid nodules in Sichuan Provincial People's Hospital (training set, n=841) and Sichuan Mianyang 404 Hospital (external validation set, n=295) from January 2021 to December 2022 were retrospectively analyzed, and preoperative thyroid ultrasound was used to classify thyroid nodules by C-TI-RADS. Univariate and Multivariate Logistic regression analyses were used to screen independent predictors in the training set and a Nomogram model was constructed, and Bootstrap resampling was used for internal validation; ultrasound physicians in Sichuan Mianyang 404 Hospital were charged in external verification based on this Nomogram model. Receiver operating characteristic (ROC) curve and calibration curve were drawn to evaluate the efficacy of the model and its clinical value in modifying the classification results by C-TI-RADS.
    Results Univariate and Multivariate Logistic regression analyses showed that gender, age, maximum diameter of nodules, the number of nodules, ultrasound abnormalities of cervical lymph nodes and C-TI-RADS classification were the independent factors for predicting the modified classification results of C-TI-RADS by ultrasound physicians (P < 0.05). Consistency index of the Nomogram model constructed based on these factors was 0.842 (95%CI, 0.816 to 0.867), the area under the curve (AUC) was 0.842, sensitivity was 92.9%, specificity was 63.7%, and accuracy was 75.9%. The prediction results of the Nomogram model were in good agreement with the actual situation in both the training set and the external validation set.
    Conclusion Nomogram model based on clinical and ultrasound features of thyroid shows good predictive accuracy in modifying classification results of C-TI-RADS by ultrasound physicians, which has potential clinical application value.

     

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