External Validation of a Nomogram and Risk Grouping System for Predicting Individual Prognosis of Patients With Medulloblastoma - Guo, Chengcheng; Yao, Dunchen; Lin, Xiaoping; Huang, He; Zhang, Ji; Lin, Fuhua; Mou, Yonggao; Yang, Qunying (Frontiers in Pharmacology, 2020)
Background. 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 MB. Methods and materials. The nomogram was constructed based on data from the Surveillance, Epidemiology, and End Results (SEER) database, comprising of 2824 MB patients, as the training cohort. 161 additional patients treated at the Sun Yat-sen University Cancer Center (SYSUCC) were included 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 effects of the nomogram for OS. Results. Cox regression analyses showed that the prognostic factors for the training cohort were histopathology, surgery, radiotherapy, chemotherapy, 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-, 5- year OS rate for patients with MB precisely. In the training cohort, a risk grouping system was built that could perfectly classified into four risk nomogroups with a 5-year survival rate of 83.9%, 76.5%, 64.5%, and 46.8%, respectively. Conclusions. 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 to better make treatment plan and prognosis assessment.