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18-01-2017 | Glioblastoma multiforme | Article

Early postoperative tumor progression predicts clinical outcome in glioblastoma—implication for clinical trials

Journal:
Journal of Neuro-Oncology

Authors: Andreas Merkel, Dorothea Soeldner, Christina Wendl, Dilek Urkan, Joji B. Kuramatsu, Corinna Seliger, Martin Proescholdt, Ilker Y. Eyupoglu, Peter Hau, Martin Uhl

Publisher: Springer US

Abstract

Molecular markers define the diagnosis of glioblastoma in the new WHO classification of 2016, challenging neuro-oncology centers to provide timely treatment initiation. The aim of this study was to determine whether a time delay to treatment initiation was accompanied by signs of early tumor progression in an MRI before the start of radiotherapy, and, if so, whether this influences the survival of glioblastoma patients. Images from 61 patients with early post-surgery MRI and a second MRI just before the start of radiotherapy were examined retrospectively for signs of early tumor progression. Survival information was analyzed using the Kaplan–Meier method, and a Cox multivariate analysis was performed to identify independent variables for survival prediction. 59 percent of patients showed signs of early tumor progression after a mean time of 24.1 days from the early post-surgery MRI to the start of radiotherapy. Compared to the group without signs of early tumor progression, which had a mean time of 23.3 days (p = 0.685, Student’s t test), progression free survival was reduced from 320 to 185 days (HR 2.3; CI 95% 1.3–4.0; p = 0.0042, log-rank test) and overall survival from 778 to 329 days (HR 2.9; CI 95% 1.6–5.1; p = 0.0005). A multivariate Cox regression analysis revealed that the Karnofsky performance score, O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, and signs of early tumor progression are prognostic markers of overall survival. Early tumor progression at the start of radiotherapy is associated with a worse prognosis for glioblastoma patients. A standardized baseline MRI might allow for better patient stratification.

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