Identifying the best treatment choice for relapsing/refractory glioblastoma: a systematic review with multiple Bayesian network meta-analyses.

Abstract

Background: Glioblastoma is a highly aggressive primary central nervous system tumor characterized by poor outcomes. In case of relapse or progression to adjuvant chemotherapy, there is no univocal preferred regimen for relapsing glioblastoma.

Methods: We conducted a systematic review and Bayesian trial-level network meta-analyses (NMA) to identify the regimens associated with the best outcomes. The primary endpoint was overall survival (OS). Secondary endpoints were progression-free survival (PFS) and overall response rates (ORR). We estimated separate treatment rankings based on the surface under the cumulative ranking curve values. Only phase II/III prospective comparative trials were included.

Results: Twenty-four studies (3733 patients and 27 different therapies) were ultimately included. Twenty-three different regimens were compared for OS, 21 for PFS, and 26 for ORR. When taking lomustine as a common comparator, only regorafenib was likely to be significantly superior in terms of OS (hazard ratio: 0.50, 95% credible interval: 0.33-0.75). Regorafenib was significantly superior to other 16 (69.6%) regimens, including NovoTTF-100A, bevacizumab monotherapy, and several bevacizumab-based combinations. Regarding PFS and ORR, no treatment was clearly superior to the others.

Conclusions: This NMA supports regorafenib as one of the best available options for relapsing/refractory glioblastoma. Lomustine, NovoTTF-100A, and bevacizumab emerge as other viable alternative regimens. However, evidence on regorafenib is controversial at best. Moreover, most studies were underpowered, with varying inclusion criteria and primary endpoints, and no longer adapted to the most recent glioblastoma classification. A paradigmatic change in clinical trials' design for relapsing/refractory glioblastoma and more effective treatments are urgently required.