PDF(Pubmed)
Abstract：
OBJECTIVE: Cervical lymph node metastasis (CLNM) is considered a marker of papillar Fethicy thyroid cancer (PTC) progression and has a potential impact on the prognosis of PTC. The purpose of this study was to screen for predictors of CLNM in PTC and to construct a predictive model to guide the surgical approach in patients with PTC.
METHODS: This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves.
RESULTS: The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively.
CONCLUSIONS: The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.
METHODS: This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves.
RESULTS: The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively.
CONCLUSIONS: The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.
摘要：
目的：颈淋巴结转移（CLNM）被认为是乳头状遗传性甲状腺癌（PTC）进展的标志物，对PTC的预后具有潜在影响。这项研究的目的是筛选PTC中CLNM的预测因子，并构建预测模型以指导PTC患者的手术方法。
方法：这是一项回顾性研究。回顾性分析2019年7月至2023年4月间114例经病理证实的PTC患者的术前双能CT图像。双能量计算机断层扫描参数[碘浓度（IC），归一化碘浓度(NIC)，测量并计算静脉期癌灶的能谱曲线斜率(λHU)]。通过单因素和多因素logistic回归分析确定预测CLNM的独立影响因素,并构建了预测模型。使用决策曲线评估模型的临床益处，校正曲线,和接收器工作特性曲线。
结果：统计结果表明，NIC，衍生中性粒细胞与淋巴细胞比率(dNLR)，预后营养指数（PNI），性别,肿瘤直径是PTCCLNM的独立预测因子。列线图的AUC为.898（95%CI：.829-.966），校准曲线和决策曲线表明该预测模型具有良好的预测效果和临床获益,分别。
结论：基于双能CT参数和炎性预后指标构建的列线图对预测PTC患者CLNM具有较高的临床价值。
方法：这是一项回顾性研究。回顾性分析2019年7月至2023年4月间114例经病理证实的PTC患者的术前双能CT图像。双能量计算机断层扫描参数[碘浓度（IC），归一化碘浓度(NIC)，测量并计算静脉期癌灶的能谱曲线斜率(λHU)]。通过单因素和多因素logistic回归分析确定预测CLNM的独立影响因素,并构建了预测模型。使用决策曲线评估模型的临床益处，校正曲线,和接收器工作特性曲线。
结果：统计结果表明，NIC，衍生中性粒细胞与淋巴细胞比率(dNLR)，预后营养指数（PNI），性别,肿瘤直径是PTCCLNM的独立预测因子。列线图的AUC为.898（95%CI：.829-.966），校准曲线和决策曲线表明该预测模型具有良好的预测效果和临床获益,分别。
结论：基于双能CT参数和炎性预后指标构建的列线图对预测PTC患者CLNM具有较高的临床价值。
