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External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer
BACKGROUND: Delayed bleeding is an important adverse event after gastric endoscopic submucosal dissection (ESD). We aimed to externally validate the Bleeding after ESD Trend from Japan (BEST-J) score and subsequently develop a risk prediction model for bleeding in Chinese patients with early gastric...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022319/ https://www.ncbi.nlm.nih.gov/pubmed/35443628 http://dx.doi.org/10.1186/s12876-022-02273-2 |
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author | Wang, Jiaxu Wu, Shanshan Xing, Jie Li, Peng Zhang, Shutian Sun, Xiujing |
author_facet | Wang, Jiaxu Wu, Shanshan Xing, Jie Li, Peng Zhang, Shutian Sun, Xiujing |
author_sort | Wang, Jiaxu |
collection | PubMed |
description | BACKGROUND: Delayed bleeding is an important adverse event after gastric endoscopic submucosal dissection (ESD). We aimed to externally validate the Bleeding after ESD Trend from Japan (BEST-J) score and subsequently develop a risk prediction model for bleeding in Chinese patients with early gastric cancer (EGC) after ESD. METHODS: The clinical data of patients who underwent ESD for EGC in Beijing Friendship Hospital from June 2013 to December 2019 were collected retrospectively. The BEST-J score was evaluated according to the clinical data. Through univariate and multivariate logistic regression analyses of the clinical data, the factors affecting delayed bleeding were identified, and a new risk prediction model for bleeding was established. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the two prediction models. RESULTS: A total of 444 patients with EGC undergoing ESD were included, of whom 27 patients had delayed bleeding (6.1%). Multivariate logistic regression analysis showed that a history of smoking (P = 0.029), tumor size > 20 mm (P = 0.022), intraoperative use of hemoclips (P = 0.025), resection of multiple tumors (P = 0.027), and prolongation of activated partial thromboplastin time (APTT) (P = 0.020) were independent influencing factors for delayed bleeding. ROC curve analysis showed that the areas under the curves (AUCs) were different between the BEST-J score and the newly built prediction model (0.624 vs. 0.749, P = 0.012). CONCLUSIONS: The BEST-J score has moderately good discrimination for Chinese patients with EGC. However, for patients with EGC without severe comorbidities, the new risk prediction model may predict delayed bleeding better than the BEST-J score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02273-2. |
format | Online Article Text |
id | pubmed-9022319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90223192022-04-22 External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer Wang, Jiaxu Wu, Shanshan Xing, Jie Li, Peng Zhang, Shutian Sun, Xiujing BMC Gastroenterol Research BACKGROUND: Delayed bleeding is an important adverse event after gastric endoscopic submucosal dissection (ESD). We aimed to externally validate the Bleeding after ESD Trend from Japan (BEST-J) score and subsequently develop a risk prediction model for bleeding in Chinese patients with early gastric cancer (EGC) after ESD. METHODS: The clinical data of patients who underwent ESD for EGC in Beijing Friendship Hospital from June 2013 to December 2019 were collected retrospectively. The BEST-J score was evaluated according to the clinical data. Through univariate and multivariate logistic regression analyses of the clinical data, the factors affecting delayed bleeding were identified, and a new risk prediction model for bleeding was established. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the two prediction models. RESULTS: A total of 444 patients with EGC undergoing ESD were included, of whom 27 patients had delayed bleeding (6.1%). Multivariate logistic regression analysis showed that a history of smoking (P = 0.029), tumor size > 20 mm (P = 0.022), intraoperative use of hemoclips (P = 0.025), resection of multiple tumors (P = 0.027), and prolongation of activated partial thromboplastin time (APTT) (P = 0.020) were independent influencing factors for delayed bleeding. ROC curve analysis showed that the areas under the curves (AUCs) were different between the BEST-J score and the newly built prediction model (0.624 vs. 0.749, P = 0.012). CONCLUSIONS: The BEST-J score has moderately good discrimination for Chinese patients with EGC. However, for patients with EGC without severe comorbidities, the new risk prediction model may predict delayed bleeding better than the BEST-J score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02273-2. BioMed Central 2022-04-20 /pmc/articles/PMC9022319/ /pubmed/35443628 http://dx.doi.org/10.1186/s12876-022-02273-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Jiaxu Wu, Shanshan Xing, Jie Li, Peng Zhang, Shutian Sun, Xiujing External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title | External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title_full | External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title_fullStr | External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title_full_unstemmed | External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title_short | External validation of the BEST-J score and a new risk prediction model for ESD delayed bleeding in patients with early gastric cancer |
title_sort | external validation of the best-j score and a new risk prediction model for esd delayed bleeding in patients with early gastric cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022319/ https://www.ncbi.nlm.nih.gov/pubmed/35443628 http://dx.doi.org/10.1186/s12876-022-02273-2 |
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