Clinical Characteristics and Overall Survival Prognostic Nomogram for Oligodendroglioma: A Surveillance, Epidemiology, and End Results Population-Based Analysis

OBJECTIVE: Oligodendroglioma is a rare primary malignant brain tumor that has highly variable clinical outcomes. The aim of this study was to investigate demographics, outcomes, and prognostic factors of all oligodendroglioma cases from the Surveillance, Epidemiology, and End Results database to build a clinical prognosis model to predict survival time of patients with oligodendroglioma. METHODS: Cases diagnosed between 1975 and 2016 were selected from the Surveillance, Epidemiology, and End Results database. Age, sex, race, insurance, year of diagnosis, marital status, tumor location, tumor size, summary stage, surgery method, and use of radiotherapy and chemotherapy were evaluated with respect to overall survival by univariate and multivariate analysis. A nomogram predicting 5-and 10-year survival probability for oligodendroglioma was constructed and validated. RESULTS: After data cleaning, 4568 patients with oligodendroglioma were included. At the time of last follow-up, mean survival times among grade II and grade III oligodendrogliomas were 74 and 39 months, respectively. In multivariate analysis, radiotherapy, age, tumor site, summary stage, and surgery demonstrated independent associations with survival in both cohorts. Race and radiotherapy demonstrated independent associations with survival in grade II oligodendroglioma. Sex and chemotherapy demonstrated independent associations with survival in grade III oligodendroglioma. Independent factors in & nbsp;either cohort were selected to build a clinical nomogram. The C-index for the nomogram was 0.738 (95% confidence interval 0.718-0.757). The calibration curves of 5-and 10-year survival rates showed good agreement between the nomogram predictions and actual observations. CONCLUSIONS: This study was the first to develop a nomogram for predicting overall survival of patients with oligodendroglioma to help clinicians predict patient prognosis accurately and conduct further treatment.