Response classification based on a minimal model of glioblastoma growth is prognostic for clinical outcomes and distinguishes progression from pseudoprogression

Maxwell Lewis Neal, Andrew D. Trister, Sunyoung Ahn, Anne Baldock, Carly A. Bridge, Laura Guyman, Jordan Lange, Rita Sodt, Tyler Cloke, Albert Lai, Timothy F. Cloughesy, Maciej M. Mrugala, Jason K. Rockhill, Russell C. Rockne, Kristin R. Swanson

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Glioblastoma multiforme is the most aggressive type of primary brain tumor. Glioblastoma growth dynamics vary widely across patients, making it difficult to accurately gauge their response to treatment. We developed a model-based metric of therapy response called Days Gained that accounts for this heterogeneity. Here, we show in 63 newly diagnosed patients with glioblastoma that Days Gained scores from a simple glioblastoma growth model computed at the time of the first postradiotherapy MRI scan are prognostic for time to tumor recurrence and overall patient survival. After radiation treatment, Days Gained also distinguished patients with pseudoprogression from those with true progression. Because Days Gained scores can be easily computed with routinely available clinical imaging devices, this model offers immediate potential to be used in ongoing prospective studies. Cancer Res; 73(10); 2976-86.

Original languageEnglish (US)
Pages (from-to)2976-2986
Number of pages11
JournalCancer research
Volume73
Issue number10
DOIs
StatePublished - May 15 2013

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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