A Nomogram Model Based on the Risk of Lymph Node Metastasis to Evaluate the Prognosis of Gastric Cancer

语思 覃,Yiju Xia, Li Liu,Y Chen, Bin Xiao, Xiaofeng Feng, Hongbo Wu, Rong Fan, Jing Dai, Guiyong Peng

Research Square (Research Square)(2023)

引用 0|浏览0
暂无评分
摘要
Abstract Background: Gastric cancer is one of the most common malignancies that pose a serious risk to human health worldwide. Lymph node metastasis may serve as an important prognostic factor for gastric cancer. However, the use of lymph nodes as a prognostic indicator for gastric cancer may lead to stage migration. The aim of this study is to establish a nomogram model to increase the prognostic accuracy of gastric cancer by validating the prognostic role of lymph node metastatic risk. Methods: A total of 3716 patients with gastric cancer were included in this study based on information from the SEER database. The risk factors for lymph node metastasis were analyzed correlatively. Prognostic factors were analyzed by COX regression, on which nomograms were constructed. The model was validated with ROC and C-indices, and Kaplan-Meier curves were evaluated and analyzed for each prognostic factor. Results: Age, sex, T-stage, N-stage, M-stage, tumor size and lymph node ratios all served as independent prognostic factors for gastric cancer. lymph node metastasis ratio is a prognostic factor in gastric cancer that is superior to lymph node number. The nomogram model has 3- and 5-year AUC values of 0.797 and 0.817 respectively, with a C-index of 0.730. Conclusion: As a prognostic factor of gastric cancer, lymph node metastasis ratio can reduce stage migration, and its inclusion in the nomogram model is superior to the TNM staging system to evaluate the prognosis of gastric cancer. The nomogram model we have developed has high reliability and accuracy and thus can inform personalized clinical treatment for gastric cancer patients.
更多
查看译文
关键词
gastric cancer,lymph node metastasis,nomogram model,prognosis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要