Evidence map›Paper›PMID 40927528›Full record

ArticleFrontiers in oncology2025

Predictive role of MGMT and IDH status in the efficacy of bevacizumab for high-grade glioma: a retrospective study.

Bai Xuexue, Yan Chengrui, Wenbin Ma, Feng Ming, Wu Chao

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bai XuexueDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Yan ChengruiDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Wenbin Ma *Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Feng Ming *Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Wu Chao *Department of Neurosurgery, Tengzhou Central People's Hospital, Tengzhou, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The objective of this study is to investigate the predictive role of O6-methylguanine-DNA methyltransferase (MGMT) and isocitrate dehydrogenase (IDH) status on the efficacy of bevacizumab (BEV) in high-grade glioma (HGG), while excluding the interference of chemotherapy agents. Methods: A retrospective, single-center analysis was conducted on 103 patients with HGG who received BEV treatment. The enrolled patients were grouped based on their different biomarker statuses. Depending on whether the numerical variables of the patients satisfied the normal distribution, t-test or rank-sum test was employed. Chi-square test was used for the comparison of categorical variables. Univariate and multivariate Cox regression analyses were performed to identify prognostic factors affecting progression-free survival (PFS) and overall survival (OS). Results: Multivariate COX regression analysis revealed that pathological grade, extent of resection, MGMT status, and IDH status were independent factors influencing PFS and OS in patients with HGG. The PFS, OS, and therapeutic response were superior in the MGMT methylated group compared to the unmethylated group. Similarly, patients with IDH mutations exhibited better PFS, OS, and therapeutic response than those with IDH wild-type. Conclusions: After controlling for potential confounding effects of chemotherapeutic agents, HGG patients with concurrent MGMT methylation and IDH mutations are likely to derive greater benefit from BEV treatment.

Indexed as

bevacizumabhigh-grade gliomaIDHMGMTpredictor

Identifiers

PMID40927528
PMCPMC12414963

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