Evidence map›Paper›PMID 41735518›Full record

ArticleScientific reports2026

A novel risk-scoring system based on endoscopic ultrasound and clinical characteristics for the preoperative diagnosis of small gastric gastrointestinal stromal tumors.

Luojie Liu, Yunfu Feng, Sijie Zheng, Bin He, Chao Ma, Zhibing Wang, Xiaodan Xu, Jian Chen, Ying Shi

Abstract read
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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Luojie LiuDepartment of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China. luojieliu@126.com.
Yunfu FengDepartment of Endoscopy Center, The First People's Hospital of Kunshan, Suzhou, China.
Sijie ZhengDepartment of Endoscopy Center, The First People's Hospital of Kunshan, Suzhou, China.
Bin HeDepartment of Gastroenterology, Zhangjiagang First People's Hospital, Suzhou, China.
Chao MaDepartment of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Zhibing WangDepartment of Gastroenterology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Xiaodan XuDepartment of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China.
Jian ChenDepartment of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China. szcsdocter@gmail.com.
Ying ShiDepartment of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China. shililian002@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The preoperative differentiation of small gastric gastrointestinal stromal tumors (GISTs) from other submucosal lesions remains clinically challenging due to overlapping endoscopic ultrasound (EUS) features. This study aimed to develop and validate a novel risk-scoring system integrating EUS imaging and clinical characteristics to improve preoperative diagnostic accuracy for small gastric GISTs versus non-GIST submucosal tumors. We retrospectively analyzed 1303 patients with gastric submucosal tumors (SMTs), who were divided into a training cohort (n = 670), an internal validation cohort (n = 287), and an external validation cohort (n = 346). Clinical and EUS characteristics were compared between small GISTs and non-GIST SMTs. Independent predictive factors identified through multivariate logistic regression were used to construct a risk-scoring model. The model’s diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV, NPV), and accuracy. Small gastric GISTs accounted for 614 cases (47.1%). Four independent predictors were identified: tumor location in the cardia/fundus (1 points), origin within the muscularis propria (2 points), hypoechoic echogenicity (1 point), and extraluminal growth pattern (2 points). The scoring system demonstrated strong discriminatory power, with AUCs of 0.776 (95%CI: 0.727–0.826) in the internal and 0.844 (95%CI: 0.805–0.884) in the external validation cohorts. Sensitivities were 0.867 (95%CI: 0.800–0.918) and 0.828 (95%CI: 0.767–0.878), and NPVs were 0.827 and 0.785, respectively. Risk stratification revealed that in the internal cohort, 17.3% of lesions were low-risk (0–2 points), 52.8% intermediate-risk (3–4 points), and 96.2% high-risk (5–6 points). Corresponding proportions in the external cohort were 21.5%, 73.9%, and 95.0%. The proposed EUS-based risk-scoring system shows robust performance in preoperatively diagnosing small gastric GISTs. It holds promise for improving clinical decision-making and optimizing treatment strategies by enabling non-invasive and accurate risk stratification.

Indexed as

EndosonographyGastrointestinal Stromal TumorsStomach NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveEndoscopic ultrasoundScoring systemSmall gastric gastrointestinal stromal tumors

Identifiers

PMID41735518
PMCPMC13031634

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.