Endoscopic ultrasound-based application system for predicting endoscopic resection-related outcomes and diagnosing subepithelial lesions: Multicenter prospective study.
endoscopic resection
endosonography
gastrointestinal stromal tumor
prediction
subepithelial lesion
Journal
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
ISSN: 1443-1661
Titre abrégé: Dig Endosc
Pays: Australia
ID NLM: 9101419
Informations de publication
Date de publication:
14 Apr 2023
14 Apr 2023
Historique:
received:
17
02
2023
accepted:
13
04
2023
pubmed:
15
4
2023
medline:
15
4
2023
entrez:
14
4
2023
Statut:
aheadofprint
Résumé
Subepithelial lesions (SELs) are associated with various endoscopic resection (ER) outcomes and diagnostic challenges. We aimed to establish a tool for predicting ER-related outcomes and diagnosing SELs and to investigate the predictive value of endoscopic ultrasound (EUS). Phase 1 (system development) was performed in a retrospective cohort (n = 837) who underwent EUS before ER for SELs at eight hospitals. Prediction models for five key outcomes were developed using logistic regression. Models with satisfactory internal validation performance were included in a mobile application system, SEL endoscopic resection predictor (SELERP). In Phase 2, the models were externally validated in a prospective cohort of 200 patients. An SELERP was developed using EUS characteristics, which included 10 models for five key outcomes: post-ER ulcer management, short procedure time, long hospital stay, high medication costs, and diagnosis of SELs. In Phase 1, 10 models were derived and validated (C-statistics, 0.67-0.99; calibration-in-the-large, -0.14-0.10; calibration slopes, 0.92-1.08). In Phase 2, the derived risk prediction models showed convincing discrimination (C-statistics, 0.64-0.73) and calibration (calibration-in-the-large, -0.02-0.05; calibration slopes, 1.01-1.09) in the prospective cohort. The sensitivities and specificities of the five diagnostic models were 68.3-95.7% and 64.1-83.3%, respectively. We developed and prospectively validated an application system for the prediction of ER outcomes and diagnosis of SELs, which could aid clinical decision-making and facilitate patient-physician consultation. EUS features significantly contributed to the prediction. Chinese Clinical Trial Registry, http://www.chictr.org.cn (ChiCTR2000040118).
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : China Scholarship Council
Organisme : National Key R&D Program of China
ID : 2021YFE0202000
Organisme : Shandong Provincial Key Research and Development Program (Major Scientific and Technological Innovation Project)
ID : 2021CXGC010506
Informations de copyright
© 2023 Japan Gastroenterological Endoscopy Society.
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