Observational Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Sep 15, 2022; 14(9): 1823-1832
Published online Sep 15, 2022. doi: 10.4251/wjgo.v14.i9.1823
Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
San-Dong Gong, Huan Li, Yi-Bin Xie, Xiao-Hui Wang
San-Dong Gong, Xiao-Hui Wang, Department of Gastroenterology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, Hainan Province, China
Huan Li, Xiao-Hui Wang, Department of Gastroenterology, Sixth Medical Center of Chinese PLA General Hospital, Beijing 100048, China
Yi-Bin Xie, Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Author contributions: Gong SD and Wang XH designed the study; Gong SD and Li H performed the research; Gong SD, Li H, Xie YB and Wang XH analyzed the date; Gong SD wrote the paper; Wang XH revised the manuscript for final submission; Gong SD and Li H contributed equally to this study; Xie YB and Wang XH are the corresponding authors; and all authors read and approved the final version.
Supported by The CAMS Initiative for Innovative Medicine, No. 2016-I2M-1-007.
Institutional review board statement: The study was reviewed and approved by the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.
Informed consent statement: Written informed consent was exempted, because all patients had already signed the informed consents before treatment according to the institutional guideline, and all the information used in present study were obtained the raw data documented in the database.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: No additional data are declared to be shared.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xiao-Hui Wang, MD, Associate Chief Physician, Doctor, Department of Gastroenterology, Sixth Medical Center of Chinese PLA General Hospital, No. 6 Fucheng Road, Haidian District, Beijing 100048, China. wangxiaohui9727@sohu.com
Received: April 19, 2022
Peer-review started: April 19, 2022
First decision: May 11, 2022
Revised: May 14, 2022
Accepted: August 14, 2022
Article in press: August 14, 2022
Published online: September 15, 2022
Processing time: 143 Days and 2.4 Hours
ARTICLE HIGHLIGHTS
Research background

With the development of endoscopic techniques, endoscopic submucosal dissection (ESD) has been widely used in the treatment of early gastric cancer (EGC); however, due to the wide range of ESD peeling, deep lesion peeling, difficult operations, and relatively high risk of complications such as bleeding and perforation, a personal predictive model of the outcome is necessary.

Research motivation

A personalized and effective prediction method of the outcomes of ESD for EGC is urgently needed in clinical practice.

Research objectives

This study aimed to build a personalized prediction model that may provide a theoretical basis for the prevention of ulcers among EGC patients after ESD.

Research methods

A total of 196 EGC patients who received ESD treatment in our hospital from March 2019 to March 2021 were enrolled in our study. The general information of the patients, pathological features and endoscopic features were analyzed, and multivariate logistic regression analysis was performed to evaluate their predictive value.

Research results

After LASSO regression analysis and validation, clopidogrel medication history, lesion diameter, convergent folds, and mucosal discoloration were the 4 independent variables that predicted postoperative ulceration. Receiver operating characteristic curve analysis showed that the AUC of the risk prediction model for ulcers after ESD in patients with EGC was 0.916 (95%CI 0.865-0.967). Compared to each of the four indicators alone, their combined prediction model should have significantly increased accuracy for the prediction of ulcer occurrence after ESD for EGC patients.

Research conclusions

A LASSO regression-based ulcer risk prediction model that included clopidogrel medication history, lesion diameter, convergent folds, and mucosal discoloration was built for EGC.

Research perspectives

A large sample size should be used to validate the prediction model in future studies.