Abstract

BackgroundTreatment of ependymoma (EPN) is guided by associated tumor features, such as grade and location. However, the relationship between these features with treatments and overall survival in EPN patients remains uncharacterized. Here, we describe the change over time in treatment strategies and identify tumor characteristics that influence treatment and survival in EPN. Methods and materialsUsing the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) 18 Registries (1973–2016) database, we identified patients with EPN microscopically confirmed to be grade II (EPN-GII) or III (EPN-GIII) tumors between 2004−2016. Overall survival (OS) was analyzed using Kaplan-Meier survival estimates and multivariable Cox proportional hazard models. A sub-analysis was performed by tumor location (supratentorial, posterior fossa, and spine). Change over time in rates of gross total resection (GTR), radiotherapy (RT), and chemotherapy (CS) were analyzed using linear regression, and predictors of treatment were identified using multivariable logistic regression models. ResultsBetween 2004–2016, 1,671 patients were diagnosed with EPN, of which 1,234 (74 %) were EPN-GII and 437 (26 %) EPN-GIII. Over the study period, EPN-GII patients underwent a less aggressive treatment (48 % vs 27 %, GTR; 60 % vs 30 %, RT; 22 % vs 2%, CS; 2004 vs 2016; p < 0.01 for all). Age, tumor size, location, and grade were positive predictors of undergoing treatment. Univariate analysis revealed that tumor grade and location were significantly associated with OS (p < 0.0001 for both). In multivariable Cox regression, tumor grade was an independent predictor of OS among patients in the cohort (grade III, HR 3.89 [2.84−5.33]; p < 0.0001), with this finding remaining significant across all tumor locations. ConclusionsIn EPN, tumor grade and location are predictors of treatment and overall survival. These findings support the importance of histologic WHO grade and location in the decision-making for treatment and their role in individualizing treatment for different patient populations.

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