Xia Yuhan, Liao Weixin, Huang Shaozhuo, Liu Zhicheng, Huang Xiaowen, Yang Chen, Ye Chao, Jiang Yingjie, Wang Jun
Basic Medical College, Southern Medical University, Guangdong, China.
Turk Neurosurg. 2020;30(1):48-59. doi: 10.5137/1019-5149.JTN.26131-19.2.
To predict the overall survival (OS) and the cancer-specific survival (CSS) of patients with high-grade glioma (HGG) using nomograms and the surveillance, epidemiology, and end results (SEER) database (2000-2013).
A total of 3706 patients with high-grade glioma were identified by the SEER database (2000-2013). Based on the relevant information of these patients, we divided the primary cohort into a training cohort (n=3336) and a validation cohort (n=370). The nomograms were constructed by the training cohort and corroborated by the validation cohort.
According to the multivariate analysis of the training cohort, the nomograms of OS and CSS indicated that patient age at diagnosis, laterality, radiation, and the extent of resection are significantly correlated with the survival rate. The c-indexes of the nomograms of OS and CSS of the training cohort are 0.682 [95% confidence interval (CI): 0.671-0.693] and 0.678 (95%CI: 0.666- 0.690), respectively. The calibration curve plots of 1- and 3-year OS and CSS showed that the nomogram predictions are consistent with the observed outcomes for both the training and validation cohorts.
Based on the data obtained, we established a scoring model to predict the OS and the CSS of patients with HGG. All calibration curves showed high consistency between the predicted and actual survival.
使用列线图和监测、流行病学及最终结果（SEER）数据库（2000 - 2013年）预测高级别胶质瘤（HGG）患者的总生存期（OS）和癌症特异性生存期（CSS）。
通过SEER数据库（2000 - 2013年）识别出3706例高级别胶质瘤患者。根据这些患者的相关信息，我们将原始队列分为训练队列（n = 3336）和验证队列（n = 370）。列线图由训练队列构建，并经验证队列证实。
根据训练队列的多因素分析，OS和CSS的列线图显示诊断时患者年龄、病变侧别、放疗及切除范围与生存率显著相关。训练队列中OS和CSS列线图的c指数分别为0.682 [95%置信区间（CI）：0.671 - 0.693]和0.678（95%CI：0.666 - 0.690）。1年和3年OS及CSS的校准曲线表明，列线图预测与训练队列和验证队列的观察结果一致。
基于所获得的数据，我们建立了一个评分模型来预测HGG患者的OS和CSS。所有校准曲线显示预测生存与实际生存之间具有高度一致性。
