Population-level determinants of socio-demographic, tumor, and treatment factors in glioblastoma using seer database (1997-2016)

Abstract BACKGROUND Although socio-demographic and treatment factors have been separately linked to impact on prognosis in several GBM studies, no studies to date have collectively evaluated many potential individual patient and treatment-related factors and their impact on survival in GBM in a comprehensive, multi-institutional, population-based manner. The purpose of this study is to identify sociodemographic, tumor, treatment, and clinical characteristics affecting survival in GBM using a large cancer registry database, the Surveillance Epidemiology End Results (SEER) registry, and identify strategies to reduce risk and disparities for patients with GBM. METHODS Individual-level data were obtained from SEER 18 program (1997-2016) using SEER*Stat software. New variables on urban-rural area and treatment combination among surgery, radiotherapy, and chemotherapy were created to comprehensively identify determinants affecting survival in GBM. Univariate and multivariate survival analyses were performed to estimate median survival time using Kaplan-Meier methods and to evaluate the relative risks of potential determinants using Cox hazard methods. RESULTS (1) The important determinants include age, gender, race, rural-urban area, diagnostic confirmation, tumor size, resection type, metastases, laterality, treatment effects and combined effects. (2) In addition to the standard treatment on GBM, the socio-demographic and clinical factors like rural-urban area (access to hospital), diagnostic conformation, and report type were important to reduce the risk to GBM patients. (3) Coming to modern times, survival time and survival rate have improved, especially in terms of socio-economic factors of people living in metro areas and married people (HR = 0.897 to 0.813 for metro area and HR = 0.999 to 0.918 for married status). CONCLUSIONS Our findings of higher risk determinants in GBM might lead to better prognosis in GBM with socio-demographic and clinical factors affecting the survival in GBM. The future investigation including MGMT promoter methylation might be beneficial with better understanding of determinants affecting risk in GBM.