Background: Oligodendrogliomas represent about 12% of all brain tumors. Our goal was to compare the demographic factors of patients diagnosed with oligodendroglioma from 2004-2014 identified in the National Cancer Database (NCDB). We also examined the survival of patients based off of the number of their comorbidities.
Methods: We identified 7525 patients diagnosed with oligodendroglioma in the NCDB diagnosed between 2004-2014. Many demographic factors were examined such as age, gender, race, facility treated at, comorbidities, and surgery type. Between-insurance survival differences were estimated by the Kaplan-Meier method and associated log-rank tests; Tukey-Kramer adjusted P < .05 indicated statistical significance.
Results: More men were diagnosed with the tumor than females (55% vs 45%). Average age of patients at diagnosis was 43.5 years old. 66% of patients had private insurance, while 7% of patients were uninsured. 88.9% of patients were white, while 5.5% of patients were black. Patients that were treated at an academic/ research program were 32% of the sample size. 17% of the sample size were treated at a comprehensive community cancer program. Those with no comorbidities had the highest mean survival time of 111 months, those with one comorbidity had a mean survival time of 97 months, and those with two comorbidities had the lowest mean survival time of 75 months. 12.8% of patients had radical, total gross resection of tumor, lesion, or mass in their brain and 10% of patients had less than half of the lobe involved with the tumor resection. 20.1% of patients had systemic therapy after surgery. 59% of patients had no systemic therapy or surgery.
Conclusion: Our study shows men were affected more than women and that the mean age at diagnosis was 44 years old. The greater number of comorbidities a patient had, the lower the mean survival time was. Majority of patients were treated at an academic/research program. This is one of the largest studies to examine the demographics of patients with oligodendroglioma. Understanding who and how patients are affected can allow us to provide better resources and treatment.
