Xiaoming Rong1,2, Wuyang Yang1, Tomas Garzon-Muvdi1, Justin M Caplan1, Xuan Hui3, Michael Lim1, Judy Huang4. 1. Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland. 2. Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. 4. Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland. jhuang24@jhmi.edu.
Abstract
BACKGROUND: To the authors' knowledge, the impact of insurance status on the survival time of patients with glioblastoma multiforme (GBM) has not been fully understood. The objective of the current study was to clarify the association between insurance status and survival of patients with GBM by analyzing population-based data. METHODS: The authors performed a cohort study using data from the Surveillance, Epidemiology, and End Results program. They included adult patients (aged ≥18 years) with GBM as their primary diagnosis from the years 2007 to 2012. Patients without information regarding insurance status were excluded. A survival analysis between insurance status and GBM-related death was performed using an accelerated failure time model. Demographic and clinical variables were included to adjust for confounding effects. RESULTS: Among the 13,665 adult patients in the study cohort, 558 (4.1%) were uninsured, 1516 (11.1%) had Medicaid coverage, and 11,591 (84.8%) had non-Medicaid insurance. Compared with patients who were uninsured, insured patients were more likely to be older, female, white, married, and with a smaller tumor size at diagnosis. Accelerated failure time analysis demonstrated that older age (hazard ratio [HR], 1.04; P<.001), male sex (HR, 1.08; P<.001), large tumor size at the time of diagnosis (HR, 1.26; P<.001), uninsured status (HR, 1.14; P =.018), and Medicaid insurance (HR, 1.10; P =.006) were independent risk factors for shorter survival among patients with GBM, whereas radiotherapy (HR, 0.40; P<.001) and married status (HR, 0.86; P<.001) indicated a better outcome. The authors discovered an overall yearly progressive improvement in survival in patients with non-Medicaid insurance who were diagnosed from 2007 through 2011 (P =.015), but not in uninsured or Medicaid-insured patients. CONCLUSIONS: Variations existed in insurance status within the GBM population. Uninsured status and Medicaid insurance suggested shorter survival compared with non-Medicaid insurance among a population of patients with GBM. Cancer 2016;122:3157-65.
BACKGROUND: To the authors' knowledge, the impact of insurance status on the survival time of patients with glioblastoma multiforme (GBM) has not been fully understood. The objective of the current study was to clarify the association between insurance status and survival of patients with GBM by analyzing population-based data. METHODS: The authors performed a cohort study using data from the Surveillance, Epidemiology, and End Results program. They included adult patients (aged ≥18 years) with GBM as their primary diagnosis from the years 2007 to 2012. Patients without information regarding insurance status were excluded. A survival analysis between insurance status and GBM-related death was performed using an accelerated failure time model. Demographic and clinical variables were included to adjust for confounding effects. RESULTS: Among the 13,665 adult patients in the study cohort, 558 (4.1%) were uninsured, 1516 (11.1%) had Medicaid coverage, and 11,591 (84.8%) had non-Medicaid insurance. Compared with patients who were uninsured, insured patients were more likely to be older, female, white, married, and with a smaller tumor size at diagnosis. Accelerated failure time analysis demonstrated that older age (hazard ratio [HR], 1.04; P<.001), male sex (HR, 1.08; P<.001), large tumor size at the time of diagnosis (HR, 1.26; P<.001), uninsured status (HR, 1.14; P =.018), and Medicaid insurance (HR, 1.10; P =.006) were independent risk factors for shorter survival among patients with GBM, whereas radiotherapy (HR, 0.40; P<.001) and married status (HR, 0.86; P<.001) indicated a better outcome. The authors discovered an overall yearly progressive improvement in survival in patients with non-Medicaid insurance who were diagnosed from 2007 through 2011 (P =.015), but not in uninsured or Medicaid-insured patients. CONCLUSIONS: Variations existed in insurance status within the GBM population. Uninsured status and Medicaid insurance suggested shorter survival compared with non-Medicaid insurance among a population of patients with GBM. Cancer 2016;122:3157-65.
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