Abstract
Endoscopic submucosal dissection (ESD) is a useful method for complete resection of early gastric cancer (EGC). However, there are still some patients who undergo additional gastrectomy after ESD because of non-curative resection. There is no model that can accurately predict non-curative resection of ESD. We aimed to create a model for predicting non-curative resection of ESD in patients with EGC. We reviewed the medical records, including all gross findings of EGC, of patients who underwent ESD for EGCs. We divided the patients into a non-curative resection group and a curative resection group. The clinicopathologic characteristics were compared between the groups to identify the risk factors for non-curative resection of ESD. We created a scoring system based on logistic regression modeling and bootstrap validation. Of 1639 patients who had undergone ESD for EGCs, 272 were identified as being treated non-curatively with ESD. A large tumor size (≥20mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with non-curative resection of ESD. Points of risk scores were assigned for these variables based on the β coefficient as follows: tumor size (≥20mm), 2 points; tumor location in the upper body of the stomach, 1 point; ulcer, 2 points; fusion of gastric folds, 2 points; absence of mucosal nodularity, 1 point; spontaneous bleeding, 1 point; and undifferentiated histology, 2 points. Our risk scoring model showed good discriminatory performance on internal validation (bootstrap-corrected area under the receiver operating characteristic curve, 0.7004; 95% confidence interval, 0.6655-0.7353). We developed a validated prediction model that can be used to identify patients who will undergo non-curative resection of ESD. Our prediction model can provide useful information for making decisions about the treatment of EGC before performing ESD.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.