Suppr超能文献

基于SEER数据库和外部验证队列的不同分级胃癌患者生存列线图

Survival nomogram for different grades of gastric cancer patients based on SEER database and external validation cohort.

作者信息

Hu Lei, Yang Kang, Chen Yue, Sun Chenyu, Wang Xu, Zhu Shaopu, Yang Shiyi, Cao Guodong, Xiong Maoming, Chen Bo

机构信息

Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Department of Clinical Medicine, School of the First Clinical Medicine, Anhui Medical University, Hefei, China.

出版信息

Front Oncol. 2022 Sep 16;12:951444. doi: 10.3389/fonc.2022.951444. eCollection 2022.

Abstract

BACKGROUND

Influencing factors varied among gastric cancer (GC) for different differentiation grades which affect the prognosis accordingly. This study aimed to develop a nomogram to effectively identify the overall survival (OS).

METHODS

Totally, 9,568 patients with GC were obtained from the SEER database as the training cohort and internal validation cohort. We then retrospectively enrolled patients diagnosed with GC to construct the external validation cohort from the First Affiliated Hospital of Anhui Medical University. The prognostic factors were integrated into the multivariate Cox regression to construct a nomogram. To test the accuracy of the model, we used the calibration curves, receiver operating characteristics (ROC) curves, C-index, and decision curve analysis (DCA).

RESULTS

Race chemotherapy, tumor size, and other four factors were significantly associated with the prognosis of Grade III GC Patients. On this basis, we developed a nomogram. The discrimination of the nomogram revealed good prognostic accuracy The results of the area under the curve (AUC) calculated by ROC for five-year survival were 0.828 and 0.758 in the training set and external validation cohort, higher than that of the TNM staging system. The calibration plot revealed that the estimated risk was close to the actual risk. DCA also suggested an excellent predictive value of the nomogram. Similar results were obtained in Grade-I and Grade-II GC patients.

CONCLUSIONS

The nomogram developed in this study and other findings could help individualize the treatment of GC patients and assist clinicians in their shared decision-making with patients.

摘要

背景

不同分化程度的胃癌(GC)影响因素各异,进而相应地影响预后。本研究旨在开发一种列线图以有效识别总生存期(OS)。

方法

总共从监测、流行病学与最终结果(SEER)数据库中获取9568例GC患者作为训练队列和内部验证队列。然后,我们回顾性纳入安徽医科大学第一附属医院确诊为GC的患者以构建外部验证队列。将预后因素纳入多变量Cox回归以构建列线图。为检验模型的准确性,我们使用了校准曲线、受试者操作特征(ROC)曲线、C指数和决策曲线分析(DCA)。

结果

种族、化疗、肿瘤大小和其他四个因素与Ⅲ级GC患者的预后显著相关。在此基础上,我们开发了一种列线图。列线图的辨别显示出良好的预后准确性。训练集和外部验证队列中通过ROC计算的五年生存率曲线下面积(AUC)结果分别为0.828和0.758,高于TNM分期系统。校准图显示估计风险接近实际风险。DCA也表明列线图具有出色的预测价值。Ⅰ级和Ⅱ级GC患者也获得了类似结果。

结论

本研究开发的列线图及其他发现有助于GC患者的个体化治疗,并协助临床医生与患者共同决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c833/9523147/2e209726f0f6/fonc-12-951444-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验