The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Qilu Hospital of Shandong University, Shandong University, Jinan, 250355, Shandong Province, China.
Sci Rep. 2023 Jul 7;13(1):11032. doi: 10.1038/s41598-023-37318-3.
The liver is one of the most ordinary metastatic sites of gastroesophageal junction adenocarcinoma and significantly affects its prognosis. Therefore, this study tried to construct a nomogram that can be applied to predict the likelihood of liver metastases from gastroesophageal junction adenocarcinoma. 3001 eligible patients diagnosed with gastroesophageal junction adenocarcinoma between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were involved in the analysis. Patients were randomly divided into a training cohort and an internal validation cohort using R software, with an allocation ratio of 7:3. According to the consequences of univariate and multivariate logistic regression, we constructed a nomogram for predicting the risk of liver metastases. The discrimination and calibration ability of the nomogram was appraised by the C-index, ROC curve, calibration plots, and decision curve analysis (DCA). We also used Kaplan-Meier survival curves to compare differences in overall survival in patients with gastroesophageal junction adenocarcinoma with and without liver metastases. Liver metastases developed in 281 of 3001 eligible patients. The overall survival of patients with gastroesophageal junction adenocarcinoma with liver metastases before and after propensity score matching (PSM) was obviously lower than that of patients without liver metastases. Six risk factors were finally recognized by multivariate logistic regression, and a nomogram was constructed. The C-index was 0.816 in the training cohort and 0.771 in the validation cohort, demonstrating the good predictive capacity of the nomogram. The ROC curve, calibration curve, and decision curve analysis further demonstrated the good performance of the predictive model. The nomogram can accurately predict the likelihood of liver metastases in gastroesophageal junction adenocarcinoma patients.
肝脏是胃食管交界处腺癌最常见的转移部位之一，对其预后有重要影响。因此，本研究试图构建一个列线图，以预测胃食管交界处腺癌发生肝转移的可能性。本研究共纳入了 2010 年至 2015 年 SEER 数据库中 3001 例符合条件的胃食管交界处腺癌患者。采用 R 软件将患者随机分为训练队列和内部验证队列，分配比例为 7:3。根据单因素和多因素逻辑回归的结果，我们构建了一个预测肝转移风险的列线图。通过 C 指数、ROC 曲线、校准图和决策曲线分析（DCA）评估了列线图的判别和校准能力。我们还使用 Kaplan-Meier 生存曲线比较了有和无肝转移的胃食管交界处腺癌患者的总生存率差异。在 3001 例符合条件的患者中，有 281 例发生了肝转移。在倾向评分匹配（PSM）前后，有肝转移的胃食管交界处腺癌患者的总生存率明显低于无肝转移的患者。通过多因素逻辑回归最终确定了 6 个危险因素，并构建了一个列线图。该列线图在训练队列中的 C 指数为 0.816，在验证队列中的 C 指数为 0.771，表明该列线图具有良好的预测能力。ROC 曲线、校准曲线和决策曲线分析进一步证明了预测模型的良好性能。该列线图可以准确预测胃食管交界处腺癌患者发生肝转移的可能性。
