Construction of a novel predictive nomogram for difficult procedure of endoscopic submucosal dissection for
1Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Objectives:
To determine the predictors of difficult colorectal endoscopic submucosal dissection (ESD) and to develop a preoperative predictive model for difficult colorectal ESD procedures.
Methods:
Colorectal neoplasms intended to be resected by ESD in our center between August 2013 and February 2019 were retrospectively enrolled. An ESD procedure which took more than 30 min, failed to remove the lesions en bloc or converted to surgery was defined as difficulty. Logistic regression analysis was conducted to find out the predictors of difficult ESD. A nomogram integrating independent predictors was developed and validated with respect to its discrimination, calibration and clinical application, using the receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA), respectively.
Results:
A total of 368 colorectal neoplasms in 355 patients were included. The independent predictors for difficult colorectal ESD were size ≥2 cm (odds ratio [OR] = 6.102, p < .001), positive non-lifting sign (OR = 6.569, p = .005), lesions located in left colon (OR = 2.475, p = .036) or rectum (OR = 2.183, p = .048), laterally spreading tumors (LSTs) (OR = 2.501, p = .008) and less colorectal ESD experience (≤20 cases) (OR = 2.3091, p = .028). The nomogram model incorporating the above predictors performed well in both of the training and validation sets (area under the cure [AUC] = 0.786 and 0.784, respectively). DCA demonstrated the clinical benefit of the nomogram was superior to that of each independent predictor alone.
Conclusions:
The nomogram incorporating tumor size, location, morphology, non-lifting sign and ESD experience of operator can be conveniently used to facilitate the preoperative prediction of difficult colorectal ESD.
