General Surgery, Affiliated Hospital of Yangzhou University, China.
General Surgery, Affiliated Hospital of Yangzhou University.
Rev Esp Enferm Dig. 2021 Jun;113(6):411-417. doi: 10.17235/reed.2020.7102/2020.
endoscopic submucosal dissection (ESD) has been widely recognized by patients and doctors due to its advantages in early gastric cancer (EGC). The accurate prediction of the risk of lymph node metastasis (LNM) in EGC is important to select suitable treatments with this procedure for patients. Unfortunately, the accuracy of endoscopic ultrasound and computed tomography in the diagnosis of EGC lymph node status is extremely limited. The purpose of the present study was to establish an LNM nomogram risk model of early gastric cancer patients based on clinical data, to guide treatment for clinicians.
a retrospective examination of the records of EGC patients undergoing radical gastrectomy from August 2012 to August 2019 in the Gastrointestinal Center of Subei People's Hospital was performed. The clinicopathological data were classified into a training set and validation set according to the time. Univariate and multivariate analyses were performed to identify risk factors related to LNM. A risk model for predicting the occurrence of LNM in EGC was established and validated.
of the 503 EGC patients, 78 (15.5 %) had lymph node metastasis. Logistic stepwise regression analysis showed that the predictive factors included sex, tumor location, tumor diameter, differentiation, ulcer and lymphatic vascular invasion. The discrimination of the LNM prediction model was satisfactory with an AUC of 0.8033 (internal validation) and 0.7353 (external validation). The correction effect of the calibration was satisfactory and the DCA decision curve analysis showed a strong clinical practicability.
the nomogram risk prediction model of LNM has been established for EGC patients to assist in formulating personalized treatment plans.
内镜黏膜下剥离术(ESD)因其在早期胃癌(EGC)中的优势而被患者和医生广泛认可。准确预测 EGC 淋巴结转移(LNM)的风险对于为患者选择合适的治疗方案至关重要。不幸的是,内镜超声和计算机断层扫描在诊断 EGC 淋巴结状态方面的准确性极其有限。本研究旨在建立基于临床数据的早期胃癌患者 LNM 列线图风险模型,为临床医生提供治疗指导。
回顾性分析 2012 年 8 月至 2019 年 8 月苏北人民医院胃肠中心接受根治性胃切除术的 EGC 患者的病历资料。根据时间将临床病理数据分为训练集和验证集。进行单因素和多因素分析,以确定与 LNM 相关的风险因素。建立并验证预测 EGC 患者 LNM 发生的风险模型。
503 例 EGC 患者中,78 例(15.5%)发生淋巴结转移。Logistic 逐步回归分析显示,预测因素包括性别、肿瘤部位、肿瘤直径、分化程度、溃疡和淋巴管侵犯。LNM 预测模型的区分度良好,AUC 分别为 0.8033(内部验证)和 0.7353(外部验证)。校准的校正效果令人满意,DCA 决策曲线分析显示出较强的临床实用性。
建立了 EGC 患者 LNM 列线图风险预测模型,以协助制定个性化治疗方案。