Zhejiang Chinese Medical University Affiliated Hangzhou First Hospital, Hangzhou First People's Hospital, Hangzhou 310006, Zhejiang, China.
Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou 310000, Zhejiang, China.
Aging (Albany NY). 2020 Mar 13;12(6):4896-4906. doi: 10.18632/aging.102915.
Cervical regional lymph node involvement (CRLNI) is common in papillary thyroid microcarcinoma (PTMC), but the way to deal with cervical lymph node involvement of clinically negative PTMC is controversial. We studied data of patients histologically confirmed PTMC in the Surveillance, Epidemiology, and End Results (SEER) Program and Department of Surgical Oncology in Hangzhou First People's Hospital (China). We screened 6 variables of demographic and clinicopathological characteristics as potential predictors and further constructed a lymph node involvement model based on the independent predictors including age, race, sex, extension, multifocality and tumor size. The model was validated by both the internal and the external testing sets, and the visual expression of the model was displayed by a nomogram. As a result, the C-index of this predictive model in the training set was 0.766, and the internal and external testing sets through cross-validation were 0.753 and 0.668, respectively. The area under the receiver operating characteristic curve (AUC) was 0.766 for the training set. We also performed a Decision Curve Analysis (DCA), which showed that predicting the cervical lymph node involvement risk applying this nomogram would be better than having all patients or none patients use this nomogram.
颈部区域淋巴结受累(CRLNI)在甲状腺微小乳头状癌(PTMC)中很常见,但对于临床阴性的 PTMC 颈部淋巴结受累的处理方式仍存在争议。我们研究了监测、流行病学和最终结果(SEER)计划以及杭州第一人民医院外科肿瘤学系中经组织学证实的 PTMC 患者的数据。我们筛选了 6 个与人口统计学和临床病理特征相关的变量作为潜在预测因子,并进一步构建了一个基于独立预测因子(包括年龄、种族、性别、延伸、多灶性和肿瘤大小)的淋巴结受累模型。该模型通过内部和外部测试集进行了验证,并通过列线图显示了该模型的可视化表达。结果显示,该预测模型在训练集中的 C 指数为 0.766,通过交叉验证在内部和外部测试集中分别为 0.753 和 0.668。训练集的受试者工作特征曲线下面积(AUC)为 0.766。我们还进行了决策曲线分析(DCA),结果表明,应用该列线图预测颈部淋巴结受累风险将优于让所有患者或无患者使用该列线图。