Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China.
Laboratory of Pathology, Hebei Cancer Institute, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China.
BMC Gastroenterol. 2022 Apr 3;22(1):163. doi: 10.1186/s12876-022-02243-8.
Estimates of cervical lymph node (LN) metastasis in patients with middle and lower thoracic esophageal squamous cell carcinoma (ESCC) are important. A nomogram is a useful tool for individualized prediction.
A total of 235 patients were enrolled in this study. Univariate and multivariate analyses were performed to screen for independent risk factors and construct a nomogram to predict the risk of cervical LN metastasis. The nomogram performance was assessed by discrimination, calibration, and clinical use.
Totally, four independent predictors, including the maximum diameter of tumor, paraesophageal lymph node status, recurrent laryngeal nerve lymph node status, and the CT-reported cervical LN status, were enrolled in the nomogram. The AUC of the nomogram model in the training and validation dataset were 0.833 (95% CI 0.762-0.905), 0.808 (95% CI 0.696-0.920), respectively. The calibration curve demonstrated a strong consistency between nomogram and clinical findings in predicting cervical LN metastasis. Decision curve analysis demonstrated that the nomogram was clinically useful.
We developed a nomogram that could be conveniently used to predict the individualized risk of cervical LN metastasis in patients with middle and lower thoracic ESCC.
中下段胸段食管鳞癌（ESCC）患者颈淋巴结（LN）转移的评估很重要。列线图是一种用于个体化预测的有用工具。
本研究共纳入 235 例患者。进行单因素和多因素分析，筛选出独立的危险因素，并构建列线图预测颈淋巴结转移的风险。通过区分度、校准度和临床实用性来评估列线图的性能。
总共有 4 个独立的预测因素，包括肿瘤的最大直径、食管旁淋巴结状态、喉返神经淋巴结状态和 CT 报告的颈部 LN 状态，被纳入列线图中。列线图模型在训练和验证数据集的 AUC 分别为 0.833（95%CI 0.762-0.905）和 0.808（95%CI 0.696-0.920）。校准曲线表明，列线图在预测颈淋巴结转移方面与临床发现具有很强的一致性。决策曲线分析表明该列线图具有临床实用性。
我们开发了一个列线图，可以方便地用于预测中下段胸段 ESCC 患者颈淋巴结转移的个体化风险。
