Data from Phase II Study of Bevacizumab in Combination with Sorafenib in Recurrent Glioblastoma (N0776): A North Central Cancer Treatment Group Trial
Year: 2023
Type: other
Abstract: Purpose: We hypothesized that vertical blockade of VEGF signaling by combining bevacizumab with sorafenib in patients with recurrent glioblastoma would result in a synergistic therapeutic effect. We also investigated whether VEGF, VEGFR2 and hypoxia-inducible factor-1α single-nucleotide polymorphisms (SNP), circulating biomarkers of angiogenesis, and MRI markers such as apparent diffusion coefficient (ADC) are correlated with treatment efficacy and/or toxicity. Experimental Design: Patients received bevacizumab (5 mg/kg every 2 weeks) with sorafenib (200 mg twice a day, weekly, days 1–5; group A). Due to toxicity, the starting sorafenib dose was subsequently modified to 200 mg every day (group B). Results: Fifty-four patients were enrolled: 19 patients in group A and 35 in group B. Objective response rate was 18.5% with median duration of 6.7 months (range 0.5–24.1 months). Six-month progression-free survival (PFS6) was 20.4% (11/54), and median overall survival (OS) was 5.6 months [95% confidence interval (CI), 4.7–8.2]; outcome was similar between the two dose groups. We identified SNPs in the VEGF and VEGFR2 promoter regions, which were associated with PFS6 (P < 0.022). Among molecular markers of angiogenesis, a higher log2 baseline level of stromal cell–derived factor-1 was associated with PFS6 success (P = 0.04). Circulating endothelial cells decreased during treatment with subsequent increase at disease progression (P = 0.022). Imaging analysis showed a trend associating ADC-L with poor outcome. Conclusions: The bevacizumab/sorafenib combination did not improve outcome of patients with recurrent glioblastoma versus historic bevacizumab-treated controls. Biologic markers of response and resistance to bevacizumab in gliomas were identified which merit prospective validation. Clin Cancer Res; 19(17); 4816–23. ©2013 AACR.
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4361949987