EPID-30. PREDICTORS ASSOCIATED WITH LONG-TERM SURVIVORSHIP FOR PATIENTS WITH GLIOBLASTOMA USING THE NATIONAL CANCER DATABASE (NCDB)

Abstract

Abstract OBJECTIVES To investigate the long-term survival rates and the related predictors in patients with glioblastoma (GBM) using NCDB. METHODS A total of 51570 GBM patients were derived from the NCDB from 2004 to 2011. Three long-term survival measures were defined as patients who lived for at least 3-year, 5-year, or 10-year after diagnosis, respectively. Multivariable binary logistic regressions were performed to identify predictors in relation to 3-year, 5-year, and 10-year survival rates. The relative importance of each survival predictors was calculated, and random forest method was performed to validate the variable importance and decision tree as well. RESULTS A total of 4782 (9.3%), 1481 (3.9%), and 51 (0.9%) GBM patients survived at least 3-year, 5-year, and 10-years, respectively. Significant predictors related to both 3-year and 5-year survival rates from multivariable logistic regression included tumor resection, recent year of diagnosis, age < 65 years, private insurance, adjuvant therapy, non-whites, female, treatment at facility located in South regions or academic facilities, higher income, and non-comorbidity. Moreover, patients who traveled >50 miles for treatment and received care transition were significantly more likely to survival at least 3 years. However, only five predictors were associated with 10-year survivorship: residence-hospital distance >20 miles, non-whites, age < 65 years, resection, and higher income. Based on the calculations of relative importance and random forest method, the most important five factors to predict long-term survival were age, tumor resection, year of diagnosis, comorbidity, and adjuvant therapy (3-year survival); age, tumor resection, comorbidity, gender, and insurance (5-year survival); and age, race, residence-hospital distance, income, and comorbidity (10-year survival), respectively. CONCLUSIONS This study identifies non-molecular factors predicting long-term survivorship among GBM patients using NCDB dataset. Our findings suggested that 3-year and 5-year survivors share similar determinants, while 10-year survivors could be more different in socio-demographics and clinical features.