Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

  • Paula Whitmire
  • , Cassandra R. Rickertsen
  • , Andrea Hawkins-Daarud
  • , Eduardo Carrasco
  • , Julia Lorence
  • , Gustavo De Leon
  • , Lee Curtin
  • , Spencer Bayless
  • , Kamala Clark-Swanson
  • , Noah C. Peeri
  • , Christina Corpuz
  • , Christine Paula Lewis-De Los Angeles
  • , Bernard R. Bendok
  • , Luis Gonzalez-Cuyar
  • , Sujay Vora
  • , Maciej M. Mrugala
  • , Leland S. Hu
  • , Lei Wang
  • , Alyx Porter
  • , Priya Kumthekar
  • Sandra K. Johnston, Kathleen M. Egan, Robert Gatenby, Peter Canoll, Joshua B. Rubin, Kristin R. Swanson

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences. Methods: Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients (299 males and 195 females). Results: Among males, tumor (T1Gd) radius was a predictor of overall survival (HR = 1.027, p = 0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR = 1.011, p < 0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p = 0.010 t-test), but tumor size was not correlated with female overall survival (p = 0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p = 0.004, F p = 0.001, t-test). Conclusion: Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes.

Original languageEnglish
Article number447
JournalBMC Cancer
Volume20
Issue number1
DOIs
StatePublished - May 19 2020

Keywords

  • Biomathematical models
  • Glioblastoma
  • Neuroimaging
  • Sex differences

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