Validation of diffusion MRI phenotypes for predicting response to bevacizumab in recurrent glioblastoma

• Verfasst von: Schell, Marianne [VerfasserIn]
• Verfasst von: Pflüger, Irada [VerfasserIn]
• Verfasst von: Brugnara, Gianluca [VerfasserIn]
• Verfasst von: Isensee, Fabian [VerfasserIn]
• Verfasst von: Neuberger, Ulf [VerfasserIn]
• Verfasst von: Foltyn-Dumitru, Martha [VerfasserIn]
• Verfasst von: Keßler, Tobias [VerfasserIn]
• Verfasst von: Sahm, Felix [VerfasserIn]
• Verfasst von: Wick, Antje [VerfasserIn]
• Verfasst von: Nowosielski, Martha [VerfasserIn]
• Verfasst von: Heiland, Sabine [VerfasserIn]
• Verfasst von: Weller, Michael [VerfasserIn]
• Verfasst von: Platten, Michael [VerfasserIn]
• Verfasst von: Maier-Hein, Klaus H. [VerfasserIn]
• Verfasst von: Deimling, Andreas von [VerfasserIn]
• Verfasst von: Van Den Bent, Martin J [VerfasserIn]
• Verfasst von: Gorlia, Thierry [VerfasserIn]
• Verfasst von: Wick, Wolfgang [VerfasserIn]
• Verfasst von: Bendszus, Martin [VerfasserIn]
• Verfasst von: Vollmuth, Philipp [VerfasserIn]
• Titel: Validation of diffusion MRI phenotypes for predicting response to bevacizumab in recurrent glioblastoma
• Titelzusatz: post-hoc analysis of the EORTC-26101 trial
• Verf.angabe: Marianne Schell, Irada Pflüger, Gianluca Brugnara, Fabian Isensee, Ulf Neuberger, Martha Foltyn, Tobias Kessler, Felix Sahm, Antje Wick, Martha Nowosielski, Sabine Heiland, Michael Weller, Michael Platten, Klaus H. Maier-Hein, Andreas Von Deimling, Martin J. Van Den Bent, Thierry Gorlia, Wolfgang Wick, Martin Bendszus, and Philipp Kickingereder
• E-Jahr: 2020
• Jahr: 12 May 2020
• Umfang: 10 S.
• Fussnoten: Gesehen am 16.02.2021
• Titel Quelle: Enthalten in: Neuro-Oncology
• Ort Quelle: Oxford : Oxford Univ. Press, 1999
• Jahr Quelle: 2020
• Band/Heft Quelle: 22(2020), 11, Seite 1667-1676
• ISSN Quelle: 1523-5866
• DOI: doi:10.1093/neuonc/noaa120
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 174837494X

Abstract

This study validated a previously described diffusion MRI phenotype as a potential predictive imaging biomarker in patients with recurrent glioblastoma receiving bevacizumab (BEV).A total of 396/596 patients (66%) from the prospective randomized phase II/III EORTC-26101 trial (with n = 242 in the BEV and n = 154 in the non-BEV arm) met the inclusion criteria with availability of anatomical and diffusion MRI sequences at baseline prior treatment. Apparent diffusion coefficient (ADC) histograms from the contrast-enhancing tumor volume were fitted to a double Gaussian distribution and the mean of the lower curve (ADClow) was used for further analysis. The predictive ability of ADClow was assessed with biomarker threshold models and multivariable Cox regression for overall survival (OS) and progression-free survival (PFS).ADClow was associated with PFS (hazard ratio [HR] = 0.625, P = 0.007) and OS (HR = 0.656, P = 0.031). However, no (predictive) interaction between ADClow and the treatment arm was present (P = 0.865 for PFS, P = 0.722 for OS). Independent (prognostic) significance of ADClow was retained after adjusting for epidemiological, clinical, and molecular characteristics (P ≤ 0.02 for OS, P ≤ 0.01 PFS). The biomarker threshold model revealed an optimal ADClow cutoff of 1241*10-6 mm2/s for OS. Thereby, median OS for BEV-patients with ADClow ≥ 1241 was 10.39 months versus 8.09 months for those with ADClow < 1241 (P = 0.004). Similarly, median OS for non-BEV patients with ADClow ≥ 1241 was 9.80 months versus 7.79 months for those with ADClow < 1241 (P = 0.054).ADClow is an independent prognostic parameter for stratifying OS and PFS in patients with recurrent glioblastoma. Consequently, the previously suggested role of ADClow as predictive imaging biomarker could not be confirmed within this phase II/III trial.