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Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer

BACKGROUND: Endoscopic submucosal dissection (ESD) has been widely used in the treatment of early gastric cancer (EGC). A personalized and effective prediction method for ESD with EGC is urgently needed. AIM: To construct a risk prediction model for ulcers after ESD for EGC based on LASSO regression...

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Autores principales: Gong, San-Dong, Li, Huan, Xie, Yi-Bin, Wang, Xiao-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516647/
https://www.ncbi.nlm.nih.gov/pubmed/36187385
http://dx.doi.org/10.4251/wjgo.v14.i9.1823
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author Gong, San-Dong
Li, Huan
Xie, Yi-Bin
Wang, Xiao-Hui
author_facet Gong, San-Dong
Li, Huan
Xie, Yi-Bin
Wang, Xiao-Hui
author_sort Gong, San-Dong
collection PubMed
description BACKGROUND: Endoscopic submucosal dissection (ESD) has been widely used in the treatment of early gastric cancer (EGC). A personalized and effective prediction method for ESD with EGC is urgently needed. AIM: To construct a risk prediction model for ulcers after ESD for EGC based on LASSO regression. METHODS: A total of 196 patients with EGC who received ESD treatment were prospectively selected as the research subjects and followed up for one month. They were divided into an ulcer group and a non-ulcer group according to whether ulcers occurred. The general data, pathology, and endoscopic characteristics of the groups were compared, and the best risk predictor subsets were screened by LASSO regression and tenfold cross-validation. Multivariate logistic regression was applied to analyze the risk factors for ulcers after ESD in patients with EGC. A receiver operating characteristic (ROC) curve was used to estimate the predictive model performance. RESULTS: One month after the operation, no patient was lost to follow-up. The incidence of ulcers was 20.41% (40/196) (ulcer group), and the incidence of no ulcers was 79.59% (156/196) (non-ulcer group). There were statistically significant differences in the course of disease, Helicobacter pylori infection history, smoking history, tumor number, clopidogrel medication history, lesion diameter, infiltration depth, convergent folds, and mucosal discoloration between the groups. Gray's medication history, lesion diameter, convergent folds, and mucosal discoloration, which were the 4 nonzero regression coefficients, were screened by LASSO regression analysis. Further multivariate logistic analysis showed that lesion diameter [Odds ratios (OR) = 30.490, 95%CI: 8.584-108.294], convergent folds (OR = 3.860, 95%CI: 1.060-14.055), mucosal discoloration (OR = 3.191, 95%CI: 1.016-10.021), and history of clopidogrel (OR = 3.554, 95%CI: 1.009-12.515) were independent risk factors for ulcers after ESD in patients with EGC (P < 0.05). The ROC curve showed that the area under the curve of the risk prediction model for ulcers after ESD in patients with EGC was 0.944 (95%CI: 0.902-0.972). CONCLUSION: Clopidogrel medication history, lesion diameter, convergent folds, and mucosal discoloration can predict the occurrence of ulcers after ESD in patients with EGC.
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spelling pubmed-95166472022-09-29 Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer Gong, San-Dong Li, Huan Xie, Yi-Bin Wang, Xiao-Hui World J Gastrointest Oncol Observational Study BACKGROUND: Endoscopic submucosal dissection (ESD) has been widely used in the treatment of early gastric cancer (EGC). A personalized and effective prediction method for ESD with EGC is urgently needed. AIM: To construct a risk prediction model for ulcers after ESD for EGC based on LASSO regression. METHODS: A total of 196 patients with EGC who received ESD treatment were prospectively selected as the research subjects and followed up for one month. They were divided into an ulcer group and a non-ulcer group according to whether ulcers occurred. The general data, pathology, and endoscopic characteristics of the groups were compared, and the best risk predictor subsets were screened by LASSO regression and tenfold cross-validation. Multivariate logistic regression was applied to analyze the risk factors for ulcers after ESD in patients with EGC. A receiver operating characteristic (ROC) curve was used to estimate the predictive model performance. RESULTS: One month after the operation, no patient was lost to follow-up. The incidence of ulcers was 20.41% (40/196) (ulcer group), and the incidence of no ulcers was 79.59% (156/196) (non-ulcer group). There were statistically significant differences in the course of disease, Helicobacter pylori infection history, smoking history, tumor number, clopidogrel medication history, lesion diameter, infiltration depth, convergent folds, and mucosal discoloration between the groups. Gray's medication history, lesion diameter, convergent folds, and mucosal discoloration, which were the 4 nonzero regression coefficients, were screened by LASSO regression analysis. Further multivariate logistic analysis showed that lesion diameter [Odds ratios (OR) = 30.490, 95%CI: 8.584-108.294], convergent folds (OR = 3.860, 95%CI: 1.060-14.055), mucosal discoloration (OR = 3.191, 95%CI: 1.016-10.021), and history of clopidogrel (OR = 3.554, 95%CI: 1.009-12.515) were independent risk factors for ulcers after ESD in patients with EGC (P < 0.05). The ROC curve showed that the area under the curve of the risk prediction model for ulcers after ESD in patients with EGC was 0.944 (95%CI: 0.902-0.972). CONCLUSION: Clopidogrel medication history, lesion diameter, convergent folds, and mucosal discoloration can predict the occurrence of ulcers after ESD in patients with EGC. Baishideng Publishing Group Inc 2022-09-15 2022-09-15 /pmc/articles/PMC9516647/ /pubmed/36187385 http://dx.doi.org/10.4251/wjgo.v14.i9.1823 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/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/
spellingShingle Observational Study
Gong, San-Dong
Li, Huan
Xie, Yi-Bin
Wang, Xiao-Hui
Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title_full Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title_fullStr Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title_full_unstemmed Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title_short Construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
title_sort construction and analysis of an ulcer risk prediction model after endoscopic submucosal dissection for early gastric cancer
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516647/
https://www.ncbi.nlm.nih.gov/pubmed/36187385
http://dx.doi.org/10.4251/wjgo.v14.i9.1823
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