Department of Cardiac Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Medicine (Baltimore). 2022 May 20;101(20):e29299. doi: 10.1097/MD.0000000000029299.
Endoscopic resection is increasingly used to treat patients with pathological T1 (pT1) esophageal squamous cell carcinoma (ESCC) because of its small surgical trauma. However, reports of the risk factors for lymph node metastasis (LNM) have been controversial. Therefore, we aim to build a nomogram to individually predict the risk of LNM in pT1 ESCC patients, to make an optimal balance between surgical trauma and surgical income.One hundred seventy patients with pT1 esophageal cancer in our hospital were analyzed retrospectively. Logistic proportional hazards models were conducted to find out the risk factor associated with LNM independently, and those were imported into R library "RMS" for analysis. A nomogram is generated based on the contribution weights of variables. Finally, decision analysis and clinical impact curve were used to determine the optimal decision point.Twenty-five (14.7%) of the 170 patients with pT1 ESCC exhibited LNM. Multivariable logistic regression analysis showed that smoking, carcinoembryonic antigen, vascular tumor thromboembolus, and tumor differentiation degree were independent risk factors for LNM. The nomogram had relatively high accuracy (C index of 0.869, 95% confidence interval: 0.794-0.914, P < .0001). The decision curve analysis provided the most significant clinical benefit for the entire included population, with scores falling just above the total score of 85 in the nomogram.Smoking, carcinoembryonic antigen, vascular tumor thromboembolus, and tumor differentiation degree may predict the risk of LNM in tumor 1 ESCC. The risk of LNM can be predicted by the nomogram.
内镜下切除越来越多地用于治疗病理 T1(pT1)食管鳞癌(ESCC)患者,因为其手术创伤较小。然而,关于淋巴结转移(LNM)风险因素的报告一直存在争议。因此,我们旨在建立一个列线图,以个体预测 pT1 ESCC 患者的 LNM 风险,在手术创伤和手术收益之间取得最佳平衡。
回顾性分析了我院 170 例 pT1 食管癌患者。通过逻辑比例风险模型找出与 LNM 相关的独立风险因素,并将这些因素导入 R 库“RMS”进行分析。根据变量的贡献权重生成列线图。最后,使用决策分析和临床影响曲线来确定最佳决策点。
170 例 pT1 ESCC 患者中,25 例(14.7%)出现 LNM。多变量逻辑回归分析显示,吸烟、癌胚抗原、血管肿瘤栓子和肿瘤分化程度是 LNM 的独立危险因素。列线图具有较高的准确性(C 指数为 0.869,95%置信区间:0.794-0.914,P<0.0001)。决策曲线分析为整个纳入人群提供了最大的临床获益,列线图的评分刚好高于总分 85 分。
吸烟、癌胚抗原、血管肿瘤栓子和肿瘤分化程度可能预测 T1 期 ESCC 的 LNM 风险。列线图可预测 LNM 风险。