基于超声的甲状腺乳头状微癌中心淋巴结转移预测提名图。

Xiaochen Zhang, Jianing Zhu, Xin Ai, Meizheng Dang, Pintong Huang
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引用次数: 0

摘要

目的:对淋巴结转移临床阴性的甲状腺乳头状微癌(PTMC)患者进行预防性中央淋巴结清扫仍存在争议--并非所有PTMC患者都适合接受主动监测。因此,我们旨在建立一个基于超声特征的提名图,用于预测PTMC的CLNM:这项回顾性研究纳入了 636 例经病理证实为 CLNM 的 PTMC 患者。通过单变量和多变量回归分析筛选出与CLNM相关的风险因素。然后,建立了一个CLNM预测模型,并使用接收者操作特征、校准和决策曲线分析来评估该模型的性能:结果:包括年龄、性别、合并 CLNM 状态、肿瘤大小和囊侵犯在内的五个变量被纳入提名图。训练数据集和验证数据集的接收者操作特征曲线下面积值分别为 0.720(95% 置信区间 [CI],0.649-0.791)和 0.704(95% CI,0.622-0.786):结论:成功建立了基于超声的提名图,其中的预测模型显示出卓越的预测性能,可用于评估 PTMC 中 CLNM 的状况。因此,应考虑对提名图评分较高的患者进行预防性颈部中央切除术。
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An ultrasound-based nomogram for predicting central lymph node metastasis in papillary thyroid microcarcinoma.

Aims: Performing prophylactic central lymph node dissection for papillary thyroid microcarcinoma (PTMC) patients with clinically negative lymph node metastasis remains controversial - not all patients with PTMC are suitable for active surveillance. Therefore, we aimed to establish a nomogram based on ultrasound features for predicting CLNM in PTMC.

Material and methods: This retrospective study included 636 patients with PTMC, in which the CLNM status was pathologically confirmed. Univariate and multivariate regression analyses were conducted to screen for risk factors associated with CLNM. Then, a CLNM prediction model was established, receiver operating characteristic, calibration, and decision curve analyses were used to assess the model's performance.

Results: Five variables, including age, sex, combined CLNM status, tumor size, and capsule invasion, were included in the nomogram. The values of the area under the receiver operating characteristic curve in the training and validation datasets were 0.720 (95% confidence interval [CI], 0.649-0.791) and 0.704 (95% CI, 0.622-0.786), respectively.

Conclusions: An ultrasound-based nomogram was successfully established, of which the predictive model shows excellent predictive performance and can be used to evaluate the status of CLNM in PTMC. Thus, patients with high nomogram scores should be considered for prophylactic central neck dissection.

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