Abstract
Purpose In our study, we aimed to screen the risk factors that affect overall survival (OS) and cancer-specific survival (CSS) in adult glioma patients and to develop and evaluate nomograms. Methods Primary high-grade gliomas patients being retrieved from the surveillance, epidemiology and end results (SEER) database, between 2004 and 2015, then they randomly assigned to a training group and a validation group. Univariate and multivariate Cox analysis models were used to choose the variables significantly correlated with the prognosis of high-grade glioma patients. And these variables were used to construct the nomograms. Next, concordance index (C-index), calibration plot and receiver operating characteristics (ROCs) curve were used to evaluate the accuracy of the nomogram model. In addition, the decision curve analysis (DCA) was used to analyze the benefit of nomogram and prognostic indicators commonly used in clinical practice. Results A total of 6395 confirmed glioma patients were selected from the SEER database, divided into training set (n =3166) and validation set (n =3229). Age at diagnosis, tumor grade, tumor size, histological type, surgical type, radiotherapy and chemotherapy were screened out by Cox analysis model. For OS nomogram, the C-index of the training set was 0.741 (95% CI: 0.751-0.731), and the validation set was 0.738 (95% CI: 0.748-0.728). For CSS nomogram, the C-index of the training set was 0.739 (95% CI: 0.749-0.729), and the validation set was 0.738 (95% CI: 0.748-0.728). The net benefit and net reduction in inverventions of nomograms in the decision curve analysis (DCA) was higher than histological type. Conclusions We developed nomograms to predict 3- and 5-year OS rates and 3- and 5-year CSS rates in adult high-grade glioma patients. Both the training set and the validation set showed good calibration and validation, indicating the clinical applicability of the nomogram and good predictive results.
Highlights
Among adults, gliomas are the most common primary brain tumors, accounting for more than 70% of primary malignant brain tumors [1,2,3]
Many studies explored the factors influencing the prognosis of gliomas, including age at diagnosis, histological type, tumor volume, tumor grade, molecular markers (1p19q-codeletion, isocitrate dehydrogenase (IDH) state, p53 state, etc.) and the extent of surgical resection
All data used in our study came from the SEER database, which has been approved for public use by the local ethics committee
Summary
Gliomas are the most common primary brain tumors, accounting for more than 70% of primary malignant brain tumors [1,2,3]. The high-grade gliomas are difficult to treat due to their easy invasion of surrounding parenchyma, presenting high mortality and poor prognosis. Many studies explored the factors influencing the prognosis of gliomas, including age at diagnosis, histological type, tumor volume, tumor grade, molecular markers (1p19q-codeletion, IDH state, p53 state, etc.) and the extent of surgical resection. Relevant studies indicated that the survival time of low-grade glioma was long, and the survival time decreased gradually with the increase of tumor grade; besides, the effect of surgical resection on the prognosis was controversial. Some studies concluded that the extension of surgical resection could effectively improve the prognosis [5,6,7,8,9,10].
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