Title

A Bayesian Adaptive Randomized Phase II Multicenter Trial of Bevacizumab with or without Vorinostat in Adults with Recurrent Glioblastoma

Document Type

Article

Publication Date

3-13-2020

Publication Title

Neuro Oncol

Abstract

BACKGROUND: Bevacizumab has promising activity against recurrent glioblastoma (GBM). However, acquired resistance to this agent results in tumor recurrence. We hypothesized that vorinostat, a histone deacetylase (HDAC) inhibitor with antiangiogenic effects, would prevent acquired resistance to bevacizumab.

METHODS: This multicenter phase II trial used a Bayesian adaptive design to randomize patients with recurrent GBM to bevacizumab alone or bevacizumab plus vorinostat with the primary endpoint of progression-free survival (PFS) and secondary end points of overall survival (OS) and clinical outcomes assessment (MDASI-BT). Eligible patients were adults (≥18 yrs) with histologically confirmed GBM recurrent after prior radiation therapy, with adequate organ function, KPS≥60, and no prior bevacizumab or HDAC inhibitors.

RESULTS: Ninety patients (bevacizumab+vorinostat:49, bevacizumab:41) were enrolled of whom 74 were evaluable for PFS (bevacizumab+vorinostat:44, bevacizumab:30). Median PFS (3.7 vs 3.9 months, p=0.94, HR 0.63 [95% CI 0.38, 1.06, p=0.08]), median OS (7.8 vs 9.3 months, p=0.64, HR 0.93 [95% CI 0.5, 1.6, p=0.79]) and clinical benefit were similar between the two arms. Toxicity (≥grade 3) in 85 evaluable patients included hypertension (n=37), neurological changes (n=2), anorexia (n=2), infections (n=9), wound dehiscence (n=2), DVT/PE (n=2), and colonic perforation (n=1).

CONCLUSIONS: Bevacizumab combined with vorinostat did not yield improvement in PFS, OS or clinical benefit compared with bevacizumab alone nor a clinical benefit in adults with recurrent GBM. This trial is the first to test a Bayesian adaptive design with adaptive randomization and Bayesian continuous monitoring in patients with primary brain tumor and demonstrates the feasibility of using complex Bayesian adaptive design in a multicenter setting.

PubMed ID

32166308

ePublication

ePub ahead of print

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