Prediction of lymph node metastatic status in superficial esophageal squamous cell carcinoma using an assessment model combining clinical characteristics and pathologic results: A retrospective cohort study

Abstract

Background: It is important to identify the risk of lymph node metastasis (LNM) in patients with superficial esophageal squamous carcinoma (SESC) who have received endoscopic resection (ER). We aimed to develop a risk-predicting model for metastasis of SESC to lymph nodes using clinicopathological features and pathological results.

Methods: Clinical data on 539 consecutive patients who underwent esophagectomy for SESC in our hospital were collected. Their post-surgical pathological results were assessed and analyzed. Multivariate logistic regression was used to identify all independent risk factors associated with LNM that then were incorporated into the prediction model.

Results: LNM was identified in 53 of 366 patients and 30 of 173 patients by positive histopathological results in the training and validation cohorts. The risk factors associated with LNM were large tumor size, poor tumor grade, deep invasion, and presence of angiolymphatic invasion. The model achieved good discriminatory ability of 0.80 (95%CI, 0.74-0.86) and 0.81 (95%CI, 0.75-0.86) in predicting LNM in the training and validation cohorts respectively. A LNM-predicting nomogram was formed with an area under curve of 0.80 (95% CI, 0.74-0.86), which had well-fitted calibration curves.

Conclusions: A prediction model was constructed to generates 3 categories for estimated LNM risk in SESC patients. It provides a practical way of estimation of LNM risk in SESC patients who had received ER.

Keywords: Lymph node metastasis; Prediction model; Superficial esophageal squamous cell carcinoma.