Impact of sociodemographic factors and Medicaid expansion on postoperative outcomes for glioblastoma, 2004-2021.

B Bhav Jain (Stanford University School of Medicine, Stanford, CA) P Pragat Patel (University of Pennsylvania, Philadelphia, PA) G Gabriela D. Ruiz Colón (Massachusetts General Hospital, Boston, MA) L Lily H. Kim (Stanford University Medical Center, Stanford, CA) J John Choi E Edward Christopher Dee T Tej D. Azad L Laura M. Prolo G Gordon Li (Stanford University, Stanford, CA) M Michael Lim

Abstract

1614 Background: Glioblastoma (GBM), the most aggressive primary brain tumor in adults, has a median survival of ~15 months despite treatment and exhibits significant disparities in care access. Sociodemographic factors and policy interventions, such as Medicaid expansion under the ACA, show potential to mitigate inequities in other cancers. However, their impact on GBM outcomes remains underexplored. Methods: Using the National Cancer Database, we conducted a retrospective study of 85,631 GBM patients treated with surgery between 2004 and 2021. Multivariate regression models and Kaplan-Meier survival analyses evaluated associations between sociodemographic factors (e.g., race, income, education, rurality, insurance status) and outcomes, including postoperative hospital stay, 30-day readmission, 90-day mortality, and overall survival. All models adjusted for key clinical (e.g., tumor size, comorbidities, receipt of chemotherapy/radiation therapy) and patient (e.g., age, sex) covariates. A difference-in-differences analysis assessed the effects of Medicaid expansion on these outcomes. Results: Regarding postoperative length of hospital stay, disparities were observed by race (Black vs. White β = 1.45 days [1.22–1.68]; Asian American and Pacific Islander [AAPI] vs. White β = 0.86 days [0.50–1.22]), rurality (urban vs. metro β = -0.31 days [-0.47 to -0.15]), insurance status (private vs. uninsured β = -1.10 days [-1.41 to -0.80]), and education (highest vs. lowest quartile β = -0.28 days [-0.48 to -0.09]). Unplanned 30-day hospital readmission rates demonstrated disparities by race (Black vs. White OR = 1.19 [1.04–1.35]), income (highest vs. lowest quartile OR = 0.84 [0.75–0.96]), and education (highest vs. lowest quartile OR = 1.19 [1.05–1.34]). Moreover, 90-day mortality indicated disparities by race (Black vs. White OR = 0.85 [0.77–0.95]; AAPI vs. White OR = 0.64 [0.53–0.77]), income (highest vs. lowest quartile OR = 0.81 [0.74–0.89]), education (highest vs. lowest quartile OR = 1.13 [1.03–1.23]), and insurance status (private vs. uninsured OR = 0.71 [0.62–0.82]). Finally, overall survival demonstrated disparities by race (Black vs. White HR = 0.88 [0.85–0.91]; AAPI vs. White HR = 0.77 [0.73–0.82]), income (highest vs. lowest quartile HR = 0.83 [0.81–0.86]), education (highest vs. lowest quartile HR = 1.12 [1.09–1.15]), rurality (rural vs. metro HR = 1.06 [1.00–1.12]), and insurance status (Medicaid vs. no insurance HR = 1.09 [1.04–1.15]). Medicaid expansion did not significantly impact any outcomes, including overall survival (DID HR = 0.95 [0.84–1.07]). Conclusions: Significant sociodemographic disparities persist in GBM postoperative outcomes, with no improvement from Medicaid expansion. Targeted socioeconomic interventions are needed to address inequities in access to specialized neuro-oncological care and improve outcomes for underserved populations.

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
Pages 1614-1614
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (10)

B

Bhav Jain

Stanford University School of Medicine, Stanford, CA

P

Pragat Patel

University of Pennsylvania, Philadelphia, PA

G

Gabriela D. Ruiz Colón

Massachusetts General Hospital, Boston, MA

L

Lily H. Kim

Stanford University Medical Center, Stanford, CA

J

John Choi

E

Edward Christopher Dee

T

Tej D. Azad

L

Laura M. Prolo

G

Gordon Li

Stanford University, Stanford, CA

M

Michael Lim