A nomogram for predicting liver metastasis in patients with gastric gastrointestinal stromal tumor

被引:0
|
作者
Ruan, Jinqiu [1 ]
He, Yinfu [2 ]
Li, Qingwan [1 ]
Jiang, Zhaojuan [1 ]
Liu, Shaoyou [3 ]
Ai, Jing [1 ]
Mao, Keyu [1 ]
Dong, Xingxiang [1 ]
Zhang, Dafu [1 ]
Yang, Guangjun [1 ]
Gao, Depei [1 ]
Li, Zhenhui [1 ]
机构
[1] Kunming Med Univ, Affiliated Hosp 3, Yunnan Canc Hosp, Yunnan Canc Ctr,Dept Radiol, Kunming, Peoples R China
[2] Third Peoples Hosp Honghe Hani & Yi Autonomous Pre, Dept Radiol, Gejiu, Peoples R China
[3] Kunming Med Univ, Affiliated Hosp 3, Yunnan Canc Hosp, Yunnan Canc Ctr,Dept Oncol Surg, Kunming, Peoples R China
基金
中国国家自然科学基金;
关键词
Gastric gastrointestinal stromal tumor; Liver metastasis; Nomogram; Surveillance; Epidemiology; End Results; MANAGEMENT;
D O I
10.1016/j.gassur.2024.02.025
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Background: Liver metastasis (LIM) is an important factor in the diagnosis, treatment, follow-up, and prognosis of patients with gastric gastrointestinal stromal tumor (GIST). There is no simple tool to assess the risk of LIM in patients with gastric GIST. Our aim was to develop and validate a nomogram to identify patients with gastric GIST at high risk of LIM. Methods: Patient data diagnosed as having gastric GIST between 2010 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training cohort and internal validation cohort in a 7:3 ratio. For external validation, retrospective data collection was performed on patients diagnosed as having gastric GIST at Yunnan Cancer Center (YNCC) between January 2015 and May 2023. Univariate and multivariate logistic regression analyses were used to identify independent risk factors associated with LIM in patients with gastric GIST. An individualized LIM nomogram specific for gastric GIST was formulated based on the multivariate logistic model; its discriminative performance, calibration, and clinical utility were evaluated. Results: In the SEER database, a cohort of 2341 patients with gastric GIST was analyzed, of which 173 cases (7.39%) were found to have LIM; 239 patients with gastric GIST from the YNCC database were included, of which 25 (10.46%) had LIM. Multivariate analysis showed tumor size, tumor site, and sex were independent risk factors for LIM (P < .05). The nomogram based on the basic clinical characteristics of tumor size, tumor site, sex, and age demonstrated significant discrimination, with an area under the curve of 0.753 (95% CI, 0.692-0.814) and 0.836 (95% CI, 0.743-0.930) in the internal and external validation cohort, respectively. The Hosmer-Lemeshow test showed that the nomogram was well calibrated, whereas the decision curve analysis and the clinical impact plot demonstrated its clinical utility. Conclusion: Tumor size, tumor subsite, and sex were significantly correlated with the risk of LIM in gastric GIST. The nomogram for patients with GIST can effectively predict the individualized risk of LIM and contribute to the planning and decision making related to metastasis management in clinical practice. (c) 2024 Society for Surgery of the Alimentary Tract. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:710 / 718
页数:9
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