Development Of A Prognostic Model For Glioblastoma Patients Based On SEER Database

Objective:Glioma is the most common malignant primary tumor of the central nervous system,and glioblastoma is the most common histological type of glioma.There is no cure or effective treatment for GB and patients with this deadly form of cancer have a high rate of mortality.In this study,we used the Surveillance,Epidemiology,and End Results(SEER)database to identify prognostic factors of patients with glioblastoma.The aim of the present study was to develop a prognostic model for patients with glioblastoma.Materials and methods:Data from patients diagnosed with glioblastoma were collected from the SEER database between 2006 and 2015.A total of 28746 patients were randomly divided into training group(n=8780)and validation group(n=3760)according to the proportion of 70%and 30%.The nomogram was constructed by the training cohort and corroborated by the validation cohort.The Kaplan-Meier(K-M)curve was used to describe overall survival.A Cox proportional hazards regression model was used for both univariate and multivariate analyses to identify independent factors with the prognosis of patients with glioblastoma.Based on the independent factors,a nomogram was developed by R studio software to predict the 1-year and 3-year overall survival in patients with glioblastoma.Harrell's concordance index(C-index)and calibration plots were formulated to evaluate the reliability and accuracy of the nomogram using bootstrapping according to the internal(training set)and external(validation set)validity.Result:The results of univariate analysis showed that age,marital status,tumor location,tumor size,radiotherapy,surgery,and chemotherapy were statistically significant in overall survival with patients.The above variables were included in the multivariate regression analysis.After screening,six independent prognostic factors were identified including age,marital status,tumor size,surgery,radiotherapy,and chemotherapy.R studio software was used to develop a nomogram based on these factors.The C-index of internal validation was 0.773(95%confidence internal,0.763?0.782)and 0.758(95%confidence internal,0.707?0.809),respectively.The calibration plots had a high degree of consistency between predicted survival probability and actual survival probability.Conclusion:(1)This study identified that age,marital status,tumor size,surgery,radiotherapy,and chemotherapy are independent prognostic factors for patients with glioblastoma.Gender,race,tumor site,and tumor side are not independent prognostic factors for patients with glioblastoma.(2)Based on the SEER database,the present study constructed a relatively complete and reliable nomogram for predicting the overall survival of patients with glioblastoma.The nomogram provides an accurate prediction of the individual prognosis in a more visual method and provides guidance for clinicians.