Guo Chengcheng, Yao Dunchen, Lin Xiaoping, Huang He, Zhang Ji, Lin Fuhua, Mou Yonggao, Yang Qunying
Department of Neurosurgery/Neuro-Oncology, Sun Yat-Sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Guangzhou, China.
Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Guangzhou, China.
Front Pharmacol. 2020 Nov 11;11:590348. doi: 10.3389/fphar.2020.590348. eCollection 2020.
Medulloblastoma (MB) is one of the most malignant neuroepithelial tumors in the central nervous system. This study aimed to establish an effective prognostic nomogram and risk grouping system for predicting overall survival (OS) of patients with MB. The nomogram was constructed based on data from the database of Surveillance, Epidemiology, and End Results (SEER). This database consisted of 2,824 patients with medulloblastoma and was used as the training cohort. The data of another additional 161 patients treated at the Sun Yat-sen University Cancer Center (SYSUCC) were used as the external validation cohort. Cox regression analysis was used to select independent prognostic factors. Concordance index (C-index) and calibration curve were used to predict the prognostic effect of the nomogram for overall survival. In the training cohort, Cox regression analyses showed that the prognostic factors included histopathology, surgery, radiotherapy, chemotherapy, tumor size, dissemination, and age at diagnosis. The internal and external validated C-indexes were 0.681 and 0.644, respectively. Calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year OS for patients with MB precisely. Using the training cohort, a risk grouping system was built, which could perfectly classify patients into four risk nomogroups with a 5-year survival rate of 83.9%, 76.5%, 64.5%, and 46.8%, respectively. We built and validated a nomogram and risk grouping system that can provide individual prediction of OS and distinguish MB patients from different risk groups. This nomogram and risk grouping system could help clinicians making better treatment plan and prognostic assessment.
髓母细胞瘤(MB)是中枢神经系统中最恶性的神经上皮肿瘤之一。本研究旨在建立一种有效的预后列线图和风险分组系统,以预测MB患者的总生存期(OS)。该列线图基于监测、流行病学和最终结果(SEER)数据库的数据构建。该数据库包含2824例髓母细胞瘤患者,并用作训练队列。另外161例在中山大学肿瘤防治中心(SYSUCC)接受治疗的患者的数据用作外部验证队列。采用Cox回归分析选择独立预后因素。一致性指数(C-index)和校准曲线用于预测列线图对总生存期的预后效果。在训练队列中,Cox回归分析显示预后因素包括组织病理学、手术、放疗、化疗、肿瘤大小、播散和诊断时年龄。内部和外部验证的C-index分别为0.681和0.644。校准曲线显示,该列线图能够准确预测MB患者的1年、3年和5年总生存期。利用训练队列,建立了一个风险分组系统,该系统可以将患者完美地分为四个风险列线图组,5年生存率分别为83.9%、76.5%、64.5%和46.8%。我们构建并验证了一个列线图和风险分组系统,该系统可以提供总生存期的个体预测,并区分不同风险组的MB患者。该列线图和风险分组系统可以帮助临床医生制定更好的治疗方案和预后评估。