Department of Oncology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China.
School of Science, Shanghai Institute of Technology, Shanghai 201418, China.
J Healthc Eng. 2021 Sep 24;2021:8605869. doi: 10.1155/2021/8605869. eCollection 2021.
The study was to develop and externally validate a prognostic nomogram to effectively predict the overall survival of patients with stomach cancer.
Demographic and clinical variables of patients with stomach cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2007-2016 were retrospectively collected. Patients were then divided into the Training Group ( = 4,456) for model development and the Testing Group ( = 4,541) for external validation. Univariate and multivariate Cox regressions were used to explore prognostic factors. The concordance index (C-index) and the Kolmogorov-Smirnov (KS) value were used to measure the discrimination, and the calibration curve was used to assess the calibration of the nomogram.
Prognostic factors including age, race, marital status, TNM stage, surgery, chemotherapy, grade, and the number of regional nodes positive were used to construct a nomogram. The C-index was 0.790 and the KS value was 0.45 for the Training Group, and the C-index was 0.789 for the Testing Group, all suggesting the good performance of the nomogram.
We have developed an effective nomogram with ten easily acquired prognostic factors. The nomogram could accurately predict the overall survival of patients with stomach cancer and performed well on external validation, which would help improve the individualized survival prediction and decision-making, thereby improving the outcome and survival of stomach cancer.
本研究旨在开发并验证一种预测胃癌患者总生存期的列线图。
回顾性收集 2007-2016 年监测、流行病学和最终结果(SEER)数据库中胃癌患者的人口统计学和临床变量。然后,将患者分为训练组(n=4456)进行模型开发和测试组(n=4541)进行外部验证。采用单因素和多因素 Cox 回归分析来探讨预后因素。采用一致性指数(C-index)和柯尔莫哥洛夫-斯米尔诺夫(KS)值来衡量区分度,校准曲线来评估列线图的校准度。
年龄、种族、婚姻状况、TNM 分期、手术、化疗、分级和阳性区域淋巴结数量等预后因素被用于构建列线图。训练组的 C-index 为 0.790,KS 值为 0.45,测试组的 C-index 为 0.789,均提示该列线图具有良好的性能。
我们已经开发了一种基于十个易于获取的预后因素的有效列线图。该列线图能够准确预测胃癌患者的总生存期,并且在外部验证中表现良好,这将有助于改善个体化生存预测和决策,从而改善胃癌的预后和生存。