Abdominal myosteatosis measured with computed tomography predicts poor outcomes in patients with glioblastoma.

Background: Alterations in cellular metabolism affect cancer survival and can manifest in metrics of body composition. We investigated the effects of various body composition metrics on survival in patients with glioblastoma (GBM).
Methods: We retrospectively analyzed patients who had an abdominal and pelvic computed tomography (CT) scan performed within 1 month of diagnosis of GBM (178 participants, 102 males, 76 females, median age: 62.1 years). Volumetric body composition metrics were derived using automated CT segmentation of adipose tissue, skeletal muscle, and aortic calcification from L1 to L5. Univariable and multivariable Cox proportional hazards models were performed separately in males and females using known predictors of GBM overall survival (OS) as covariates. A sex-specific composite score of predisposing and protective factors was constructed using the relative importance of each metric in GBM OS.
Results: Higher skeletal muscle volume and lower skeletal muscle fat fraction were associated with better OS in the entire dataset. A robust and independent effect on GBM OS was seen specifically for fraction of inter/intramuscular adipose tissue to total adipose tissue after correction for known survival predictors and comorbidities. Worse OS was observed with increased abdominal aortic calcification volume in both sexes. There was a significant difference in GBM OS among participants stratified into quartiles based on sex-specific composite predisposing and protective scores.
Conclusion: The relationship between body composition and GBM OS provides an actionable advancement toward precision medicine in GBM management, as lifestyle and dietary regimens can alter body composition and metabolism and from there GBM survival.
Competing Interests: V.T.Y.C., D.M., K.P., and M.F.B. developed the software through Voronoi Health Analytics, Inc. that was used for this study. This had no influence on the data analysis, data interpretation, or manuscript preparation and submission at any point.
(© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)