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胃癌根治性切除术后淋巴结转移阳性的危险因素及预测模型的构建

Risk factors of positive lymph node metastasis after radical gastrectomy for gastric cancer and construction of prediction models.

作者信息

Dai Gang, Chen Ming-Gan, Zhu Deng-Feng, Cai Yi-Ting, Gao Ming

机构信息

Department of General Surgery, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences Shanghai 202150, China.

出版信息

Am J Cancer Res. 2024 Nov 15;14(11):5216-5229. doi: 10.62347/PEDV7297. eCollection 2024.

Abstract

Positive lymph node metastasis after radical gastrectomy for gastric cancer is a key factor affecting the prognosis of patients, and its mechanism is complex and multifactorial. The aim of this study is to identify the relevant risk factors for positive lymph node metastasis after radical gastrectomy for gastric cancer, and to construct corresponding predictive models. Through a retrospective analysis of clinical data of 316 gastric cancer patients who underwent radical surgery for gastric cancer, we found that age, maximum tumor diameter, degree of tumor differentiation, vascular invasion, depth of tumor infiltration, and CA199 were important factors affecting lymph node metastasis positivity in gastric cancer patients. Based on these factors, we constructed a Nomogram prediction model and found through internal validation that the model has good predictive performance. The area under the receiver operating characteristic curve (AUC) of the training and validation sets were 0.929 and 0.888, respectively. Clinical data of another 390 patients were collected for external verification. External validation results showed that the model had a predictive sensitivity of 75.76% (50/66), a specificity of 91.05% (295/324), and an accuracy of 88.46% (345/390). In addition, we also constructed a neural network prediction model and compared it with the Nomogram model. The results showed that the prediction performance of the Nomogram model was similar to that of the neural network model. The Nomogram model has been validated internally and externally, demonstrating high discrimination and accuracy, providing a convenient, intuitive, and personalized evaluation tool for clinicians, helping to optimize the postoperative management of gastric cancer patients and improve prognosis.

摘要

胃癌根治性切除术后发生阳性淋巴结转移是影响患者预后的关键因素,其机制复杂且具有多因素性。本研究旨在确定胃癌根治性切除术后阳性淋巴结转移的相关危险因素,并构建相应的预测模型。通过回顾性分析316例行胃癌根治性手术的胃癌患者的临床资料,我们发现年龄、肿瘤最大直径、肿瘤分化程度、血管侵犯、肿瘤浸润深度和CA199是影响胃癌患者淋巴结转移阳性的重要因素。基于这些因素,我们构建了列线图预测模型,并通过内部验证发现该模型具有良好的预测性能。训练集和验证集的受试者操作特征曲线下面积(AUC)分别为0.929和0.888。收集另外390例患者的临床资料进行外部验证。外部验证结果显示,该模型的预测敏感性为75.76%(50/66),特异性为91.05%(295/324),准确性为88.46%(345/390)。此外,我们还构建了神经网络预测模型,并将其与列线图模型进行比较。结果表明,列线图模型的预测性能与神经网络模型相似。列线图模型已通过内部和外部验证,显示出高辨别力和准确性,为临床医生提供了一种方便、直观且个性化的评估工具,有助于优化胃癌患者的术后管理并改善预后。

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[A nomogram for predicting lymph node metastasis in early gastric cancer].[一种预测早期胃癌淋巴结转移的列线图]
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