Volumetric study reveals the relationship between outcome and early radiographic response during bevacizumab-containing chemoradiotherapy for unresectable glioblastoma.

Purpose: Although we have shown the clinical benefit of bevacizumab (BEV) in the treatment of unresectable newly diagnosed glioblastomas (nd-GBM), the relationship between early radiographic response and survival outcome remains unclear. We performed a volumetric study of early radiographic responses in nd-GBM treated with BEV.
Methods: Twenty-two patients with unresectable nd-GBM treated with BEV during concurrent temozolomide radiotherapy were analyzed. An experienced neuroradiologist interpreted early responses on fluid-attenuated inversion recovery (FLAIR) and gadolinium-enhanced T1-weighted images (GdT1WI). Volumetric changes were evaluated using diffusion-weighted imaging (DWI) and GdT1WI according to the Response Assessment in Neuro-Oncology (RANO) criteria. The results were categorized into improved (complete response [CR] or partial response [PR]) or non-improved (stable disease [SD] or progressive disease [PD]) groups; outcomes were compared using Kaplan-Meier analysis.
Results: The volumetric GdT1WI improvement was a significant predictive factor for overall survival (OS) prolongation (p = 0.0093, median OS: 24.7 vs. 13.6 months); however, FLAIR and DWI images were not predictive. The threshold for the neuroradiologist's interpretation of improvement in GdT1WI was nearly 20% of volume reduction, which was lesser than 50%, the definition of PR applied in the RANO criteria. However, even less stringent neuroradiologist interpretation could successfully predict OS prolongation (improved vs. non-improved: p = 0.0067, median OS: 17.6 vs. 8.3 months). Significant impact of OS on the early response in volumetric GdT1WI was observed within the cut-off range of 20-50% (20%, p = 0.0315; 30%, p = 0.087; 40%, p = 0.0456).
Conclusions: Early response during BEV-containing chemoradiation can be a predictive indicator of patient outcome in unresectable nd-GBM.
(© 2021. The Author(s).)