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| Home > Publications database > Framework for Statistical Parametric Mapping of the Interactions between Glioblastoma Location, Treatment, Prognostic Variables, and Survival Using a Phase III Trial. |
| Home > Publications database > Framework for Statistical Parametric Mapping of the Interactions between Glioblastoma Location, Treatment, Prognostic Variables, and Survival Using a Phase III Trial. |
| Journal Article | DKFZ-2026-01322 |
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2026
AACR
Philadelphia, Pa. [u.a.]
Abstract: Brain tumor location is known to affect survival, but there is a lack of methodologic tools for systematically studying the complex interplay between brain tumor location, prognostic variables, treatment schemes, and survival.A total of 592 prospectively enrolled patients with newly diagnosed glioblastoma from the phase III AVAglio trial, randomized to postsurgical chemoradiation with or without bevacizumab, were retrospectively analyzed. Statistical parametric mapping was conducted with multivariate Cox proportional hazards models at the voxel-wise level, incorporating dedicated interaction variables to evaluate the impact of baseline tumor volume and treatment arm on survival for different tumor locations from magnetic resonance imaging (MRI) scans, with subsequent cluster-based correction for multiple testing and mathematical estimation of regional survival curves.Tumor location in the right prefrontal cortex was an independent favorable prognostic factor [median hazard ratio (HR) = 0.57] for survival, whereas tumor involvement in left hemisphere eloquent areas with language and visual functions was unfavorable (median HR = 1.69). Larger presurgical tumor volumes were associated with shorter survival independent of tumor location (HR = 1.005), but the effect was larger for tumor locations including eloquent structures (HR ranging 1.008-1.015), whereas nonsignificant for anterior frontal locations. Bevacizumab seemed to grant a survival benefit when specific brain regions were involved or spared by the tumor, but this result was not confirmed after correction for multiple testing.This workflow allows to map the survival effects of variables onto specific brain tumor locations, revealing location dependency of prognostic variables such as tumor volume, and potentially of treatment schemes, with relevant implications in risk stratification and clinical management.
Keyword(s): Humans (MeSH) ; Glioblastoma: therapy (MeSH) ; Glioblastoma: mortality (MeSH) ; Glioblastoma: pathology (MeSH) ; Glioblastoma: diagnosis (MeSH) ; Prognosis (MeSH) ; Female (MeSH) ; Brain Neoplasms: mortality (MeSH) ; Brain Neoplasms: therapy (MeSH) ; Brain Neoplasms: pathology (MeSH) ; Magnetic Resonance Imaging (MeSH) ; Bevacizumab: administration & dosage (MeSH) ; Middle Aged (MeSH) ; Male (MeSH) ; Aged (MeSH) ; Chemoradiotherapy (MeSH) ; Adult (MeSH) ; Treatment Outcome (MeSH) ; Proportional Hazards Models (MeSH) ; Bevacizumab
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