Optimal Therapies for Recurrent Glioblastoma: A Bayesian Network Meta-Analysis

Overview

Journal Front Oncol

Specialty Oncology

Date 2021 Apr 15

PMID 33854975

Citations 24

Authors

Wenlin Chen

Yuekun Wang

Binghao Zhao

Penghao Liu

Lei Liu

Yu Wang

Wenbin Ma

Affiliations

Soon will be listed here.

Abstract

The optimal treatment of recurrent glioblastoma (GBM) remains controversial. Therefore, our study aimed to compare and rank active therapies in recurrent GBM. We performed a systematic review and a Bayesian network meta-analysis. We obtained a treatment hierarchy using the surface under the cumulative ranking curve and mean ranks. A cluster analysis was conducted to aggregate the separated results of three outcomes. The protocol was registered in PROSPERO (CRD42019146794). A total of 1,667 citations were identified, and 15 eligible articles with 17 treatments remained in the final network meta-analysis. Pairwise comparison showed no significant difference on the 6-month progression-free survival (6-m PFS) rate, objective response rate (ORR), and overall survival (OS). Among the reports, cediranib plus lomustine (CCNU) corresponded to the highest rates of grade 3-4 adverse events. Ranking and cluster analysis indicated that bevacizumab (BEV) plus CCNU and regorafenib had a higher efficacy on the ORR, 6-m PFS rate and OS, and that BEV monotherapy or BEV combined with active drug therapies was advantageous for the ORR and 6-m PFS rate. Additionally, tumor treatment fields (TTF) plus BEV showed a relatively higher SUCRA value in OS. According to ranking and cluster analysis, BEV plus CCNU and regorafenib are the primary recommendations for treatment. BEV monotherapy alone or combined with active drug therapies are recommended in patients with severe neurological symptoms. Advanced therapy, such as TTF and immunotherapy, remain to be investigated in future studies.

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