Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

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

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific "Days Gained" response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.

Original languageEnglish (US)
Article numbere51951
JournalPLoS One
Volume8
Issue number1
DOIs
StatePublished - Jan 29 2013
Externally publishedYes

Fingerprint

Patient Simulation
Glioblastoma
Tumors
Survival
Radiotherapy
Brain
therapeutics
Therapeutics
Radiation
Kinetics
Geometry
Disease-Free Survival
neoplasms
Kaplan-Meier Estimate
radiotherapy
Brain Neoplasms
Neoplasms

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric. / Neal, Maxwell Lewis; Trister, Andrew D.; Cloke, Tyler; Sodt, Rita; Ahn, Sunyoung; Baldock, Anne L.; Bridge, Carly A.; Lai, Albert; Cloughesy, Timothy F.; Mrugala, Maciej; Rockhill, Jason K.; Rockne, Russell C.; Swanson, Kristin.

In: PLoS One, Vol. 8, No. 1, e51951, 29.01.2013.

Research output: Contribution to journalArticle

Neal, ML, Trister, AD, Cloke, T, Sodt, R, Ahn, S, Baldock, AL, Bridge, CA, Lai, A, Cloughesy, TF, Mrugala, M, Rockhill, JK, Rockne, RC & Swanson, K 2013, 'Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric', PLoS One, vol. 8, no. 1, e51951. https://doi.org/10.1371/journal.pone.0051951
Neal, Maxwell Lewis ; Trister, Andrew D. ; Cloke, Tyler ; Sodt, Rita ; Ahn, Sunyoung ; Baldock, Anne L. ; Bridge, Carly A. ; Lai, Albert ; Cloughesy, Timothy F. ; Mrugala, Maciej ; Rockhill, Jason K. ; Rockne, Russell C. ; Swanson, Kristin. / Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric. In: PLoS One. 2013 ; Vol. 8, No. 1.
@article{197d7b66ed234b7bb208e84f80edb220,
title = "Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric",
abstract = "Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific {"}Days Gained{"} response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.",
author = "Neal, {Maxwell Lewis} and Trister, {Andrew D.} and Tyler Cloke and Rita Sodt and Sunyoung Ahn and Baldock, {Anne L.} and Bridge, {Carly A.} and Albert Lai and Cloughesy, {Timothy F.} and Maciej Mrugala and Rockhill, {Jason K.} and Rockne, {Russell C.} and Kristin Swanson",
year = "2013",
month = "1",
day = "29",
doi = "10.1371/journal.pone.0051951",
language = "English (US)",
volume = "8",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "1",

}

TY - JOUR

T1 - Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

AU - Neal, Maxwell Lewis

AU - Trister, Andrew D.

AU - Cloke, Tyler

AU - Sodt, Rita

AU - Ahn, Sunyoung

AU - Baldock, Anne L.

AU - Bridge, Carly A.

AU - Lai, Albert

AU - Cloughesy, Timothy F.

AU - Mrugala, Maciej

AU - Rockhill, Jason K.

AU - Rockne, Russell C.

AU - Swanson, Kristin

PY - 2013/1/29

Y1 - 2013/1/29

N2 - Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific "Days Gained" response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.

AB - Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific "Days Gained" response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.

UR - http://www.scopus.com/inward/record.url?scp=84872770788&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84872770788&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0051951

DO - 10.1371/journal.pone.0051951

M3 - Article

C2 - 23372647

AN - SCOPUS:84872770788

VL - 8

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 1

M1 - e51951

ER -