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基于 EUS 的预测胃肠道间质瘤恶性潜能的列线图的建立和验证。

Development and validation of an EUS-based nomogram for prediction of the malignant potential in gastrointestinal stromal tumors.

机构信息

Department of Gastroenterology, The Third People's Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.

The People's Hospital of Dujiangyan, Chengdu, China.

出版信息

Scand J Gastroenterol. 2023 Jul;58(7):830-837. doi: 10.1080/00365521.2023.2175179. Epub 2023 Feb 5.

Abstract

BACKGROUND

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors in the gastrointestinal (GI) tract that require different therapeutic interventions according to the malignancy. We aim to develop and validate a EUS (endoscopic ultrasonography)-based nomogram to predict malignant potential in patients with GIST.

METHODS

258 patients with pathological diagnosis of gastric GISTs were enrolled retrospectively in our hospital from June 2015 to October 2020. Patients were randomly divided into the development cohort (DC,  = 179) and the validation cohort (VC,  = 79). We established a nomogram using lasso regression based on DC data. The predictive effectiveness of the nomogram was evaluated by the area under the receiver operating characteristic curve (AUC). Through bootstrapping, a consistency index (C-index) and calibration chart are developed to evaluate the reliability and accuracy of the nomogram.

RESULTS

A total of 192 patients with low-malignant potential (very low and low-risk) GISTs and 66 patients with high-malignant potential (intermediate and high-risk) GISTs were included in this study. The nomogram was constructed with the following 6 EUS indicators: ulceration, hemorrhage, tumor shape, irregular border, transverse diameter, and necrosis. Internal and external validation showed that the nomogram had a good ability to predict the malignant potential of GISTs (AUC = 0.881 and 0.908, respectively). The calibration curve shows that the nomogram has a good agreement between predicted and actual probabilities for differentiating GISTs malignancy (C-index = 0.868 and 0.907, respectively).

CONCLUSIONS

This study developed and verified a EUS-based nomogram, which can effectively predict the malignant potential of patients with gastric GISTs.

摘要

背景

胃肠道间质瘤(GISTs)是胃肠道(GI)最常见的间叶性肿瘤,根据恶性程度需要不同的治疗干预。我们旨在开发和验证一种基于 EUS(内镜超声)的列线图,以预测 GIST 患者的恶性潜能。

方法

回顾性纳入 2015 年 6 月至 2020 年 10 月在我院经病理诊断为胃 GIST 的 258 例患者。患者被随机分为开发队列(DC,n=179)和验证队列(VC,n=79)。我们基于 DC 数据使用套索回归建立了一个列线图。通过受试者工作特征曲线(AUC)下面积评估列线图的预测效果。通过自举法,开发一致性指数(C 指数)和校准图来评估列线图的可靠性和准确性。

结果

本研究共纳入 192 例低恶性潜能(极低危和低危)GIST 患者和 66 例高恶性潜能(中危和高危)GIST 患者。该列线图由以下 6 个 EUS 指标构建而成:溃疡、出血、肿瘤形状、不规则边界、横径和坏死。内部和外部验证均表明,该列线图具有良好的预测 GIST 恶性潜能的能力(AUC 分别为 0.881 和 0.908)。校准曲线表明,该列线图在区分 GIST 恶性程度的预测概率和实际概率之间具有良好的一致性(C 指数分别为 0.868 和 0.907)。

结论

本研究开发并验证了一种基于 EUS 的列线图,可有效预测胃 GIST 患者的恶性潜能。

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