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Lessons learned from contemporary glioblastoma randomized clinical trials through systematic review and network meta-analysis: part 2 newly diagnosed disease.


ABSTRACT:

Background

Glioblastoma (GB) is the most common malignant brain tumor with a dismal prognosis despite standard of care (SOC). Here we used a network meta-analysis on treatments from randomized control trials (RCTs) to assess the effect on overall survival (OS) and progression-free survival (PFS) beyond the SOC.

Methods

We included RCTs that investigated the addition of a new treatment to the SOC in patients with newly diagnosed GB. Our primary outcome was OS, with secondary outcomes including PFS and adverse reactions. Hazard ratio (HR) and its 95% confidence interval (CI) regarding OS and PFS were extracted from each paper. We utilized a frequentist network meta-analysis. We planned a subgroup analysis based on O6-methylguanine-DNA methyl-transferase (MGMT) status. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses.

Results

Twenty-one studies were included representing a total of 7403 patients with GB. There was significant heterogeneity among studies impacting important factors such as timing of randomization and sample size. A confidence analysis on the network meta-analysis results revealed a score of low or very low for all treatment comparisons, across subgroups. Allowing for the heterogeneity within the study population, alkylating nitrosoureas (Lomustine and ACNU) and tumor-treating field improved both OS (HR = 0.53, 95% CI 0.33-0.84 and HR = 0.63 95% CI 0.42-0.94, respectively) and PFS (HR = 0.88, 95% CI 0.77-1.00 and HR = 0.63 95% CI 0.52-0.76, respectively).

Conclusions

Our analysis highlights the numerous studies performed on newly diagnosed GB, with no proven consensus treatment that is superior to the current SOC. Intertrial heterogeneity raises the need for better standardization in neuro-oncology studies.

SUBMITTER: Taslimi S 

PROVIDER: S-EPMC8134529 | biostudies-literature |

REPOSITORIES: biostudies-literature

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