Development and validation of a nomogram for preoperative prediction of lymph node metastasis in pathological T1 esophageal squamous cell carcinoma

Abstract

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.