Nomogram for predicting survival of patients with gastric cancer and multiple primary malignancies: a real-world retrospective analysis using the Surveillance, Epidemiology and End Results database

利用监测、流行病学和最终结果数据库构建预测胃癌合并多原发恶性肿瘤患者生存率的列线图:一项真实世界回顾性分析

阅读:2

Abstract

OBJECTIVES: Gastric cancer combined with multiple primary malignancies (GCM) is increasingly common. This study investigated GCM clinical features and survival time. METHODS: Patients with GCM and GC only (GCO) were selected from the Surveillance, Epidemiology and End Results (SEER) database. Survival was compared between GCM and GCO groups using propensity score matching. Then, the GCM group was divided into a training cohort and a validation cohort. These cohorts were used to establish a nomogram for survival prediction in patients with GCM. RESULTS: Survival time was significantly longer in the GCM group than in the GCO group. All-subsets regression was used to identify four variables for nomogram establishment: age, gastric cancer sequence, N stage, and surgery. The concordance index and time-dependent receiver operating characteristic curve indicated that the nomogram had favorable discriminative ability. Calibration plots of predicted and actual probabilities showed good consistency in both the training and validation cohorts. Decision curve analysis and risk stratification showed that the nomogram was clinically useful; it had favorable discriminative ability to recognize patients with different levels of risk. CONCLUSIONS: Compared with GCO, GCM is a relatively indolent malignancy. The nomogram developed in this study can help clinicians to assess GCM prognosis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。