■外侧淋巴结转移(LLNM)在甲状腺髓样癌(MTC)中非常常见,但是关于如何处理颈外侧淋巴结仍然存在争议,特别是临床阴性MTC。本研究的目的是开发和验证用于预测MTC中LLNM风险的列线图。
■回顾性研究了来自两家医院的234例患者,根据病理将其分为LLNM阳性组和LLNM阴性组。通过单变量和多变量logistic回归分析评估LLNM与术前临床和超声变量之间的相关性。列线图用于预测MTC患者的LLNM风险,由外部数据集验证,并根据歧视进行评估,校准,和临床有用性。
■训练,内部,外部验证数据集包括152、51和31名MTC患者,分别。根据多变量Logistic回归分析,性别(男性),在训练数据集中,与甲状腺包膜和血清降钙素的关系与LLNM独立相关.用上述变量开发的预测列线图模型在估计LLNM风险方面表现良好,训练数据集中的ROC曲线下面积(AUC)为0.826,内部验证数据集中的0.816,和外部验证数据集中的0.846。
■我们开发并验证了一个名为MTC列线图的模型,利用可用的术前变量来预测MTC患者LLNM的概率。此列线图对指导MTC患者的临床诊断和治疗过程具有重要价值。
UNASSIGNED: Lateral lymph node metastasis (LLNM) is very common in medullary thyroid carcinoma (MTC), but there is still controversy about how to manage cervical lateral lymph nodes, especially for clinically negative MTC. The aim of this study is to develop and validate a nomogram for predicting LLNM risk in MTC.
UNASSIGNED: A total of 234 patients from two hospitals were retrospectively enrolled in this study and divided into LLNM positive group and LLNM negative group based on the pathology. The correlation between LLNM and preoperative clinical and ultrasound variables were evaluated by univariable and multivariable logistic regression analysis. A nomogram was generated to predict the risk of the LLNM of MTC patients, validated by external dataset, and evaluated in terms of discrimination, calibration, and clinical usefulness.
UNASSIGNED: The training, internal, and external validation datasets included 152, 51, and 31 MTC patients, respectively. According to the multivariable logistic regression analysis, gender (male), relationship to thyroid capsule and serum calcitonin were independently associated with LLNM in the training dataset. The predictive nomogram model developed with the aforementioned variables showed favorable performance in estimating risk of LLNM, with the area under the ROC curve (AUC) of 0.826 in the training dataset, 0.816 in the internal validation dataset, and 0.846 in the external validation dataset.
UNASSIGNED: We developed and validated a model named MTC nomogram, utilizing available preoperative variables to predict the probability of LLNM in patients with MTC. This nomogram will be of great value for guiding the clinical diagnosis and treatment process of MTC patients.