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

ML Neal, AD Trister, S Ahn, A Baldock, CA Bridge… - Cancer research, 2013 - AACR
ML Neal, AD Trister, S Ahn, A Baldock, CA Bridge, L Guyman, J Lange, R Sodt, T Cloke…
Cancer research, 2013AACR
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 …
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. ©2013 AACR.
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