Construction and external validation of a nomogram model for predicting the risk of esophageal stricture after endoscopic submucosal dissection: a multicenter case–control study

Esophageal stricture is a common complication after endoscopic submucosal dissection (ESD) for superficial esophageal cancer and precancerous lesions, we intend to investigate the independent risk factors of esophageal stricture after ESD by adding the data of included living habits, established a nomogram model to predict the risk of esophageal stricture, and verified it by external data. The clinical data and living habits of patients with early esophageal cancer and precancerous lesions who underwent ESD in the Affiliated Hospital of North Sichuan Medical College and Langzhong People's Hospital from March 2017 to August 2021 were retrospectively collected. The data collected from the two hospitals were used as the development group (n = 256) and the validation group (n = 105), respectively. Univariate and multivariate logistic regression analyses were used to determine independent risk factors for esophageal stricture after ESD and establish a nomogram model for the development group. The prediction performance of the nomogram model is internally and externally verified by calculating C-Index and plotting the receiver operating characteristic curve (ROC) and calibration curve, respectively. The results showed that Age, drinking water temperature, neutrophil–lymphocyte ratio, the extent of esophageal mucosal defect, longitudinal diameter of resected mucosa, and depth of tissue invasion (P < 0.05) were independent risk factors for esophageal stricture after ESD. The C-Index of the development group and validation group was 0.925 and 0.861, respectively. The ROC curve and area under the curve (AUC) of the two groups suggested that the discrimination and prediction performance of the model were good. The two groups of calibration curves are consistent and almost overlap with the ideal calibration curve, indicating that the predicted results of this model are in good agreement with the actual observed results. In conclusion, this nomogram model has a high accuracy for predicting the risk of esophageal stricture after ESD, providing a theoretical basis for reducing or avoiding esophageal stricture and guiding clinical practice.