Evidence map›Paper›PMID 40037513›Full record

ReviewNeuro-oncology2025

Molecular-based decision-making in glioblastoma surgery: When to aim for supramaximal resection.

Richard Drexler, Michael Lim, Shawn L Hervey-Jumper

Abstract readReview
In one paragraph

Review in Neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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

3 authors.

Richard DrexlerDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, California, USA.ORCID 0000-0002-4830-3671
Michael LimDepartment of Neurosurgery, Stanford University, Stanford, California, USA.
Shawn L Hervey-JumperDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.

Funding

Cortical information loss in diffuse low-grade glioma infiltrated cortexR01NS137950 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Shawn L. Hervey-Jumper · 2024 to 2026
$1.2M
NINDS NIH HHS R01 NS137950
6 · The paper itself

Abstract

The advent of molecular techniques has enhanced our understanding of the biology of malignancies over the past decade. Multi-omics has facilitated an in-depth characterization of glioblastomas at the cellular level, revealing intricate details about tumor cell states and their compositions. This advancement has substantially enriched our comprehension of tumor cell interactions with the surrounding microenvironment-such as neurons and immune cells-shedding light on patterns of tumor growth, infiltration, and therapeutic resistance. Despite the introduction of immunotherapies and molecularly guided chemotherapeutic treatments, surgical resection remains a cornerstone of the glioblastoma therapeutic regimen. While maximal resection is universally considered to improve patient outcomes, integrating molecular data and insights into tumor cell interactions suggests a role for molecular-based surgical decision-making. Herein, we review how the molecular characterization of glioblastoma subtypes and their interactions can predict the benefits of surgical resection. We discuss how these insights could refine neurosurgical management in the future. Integrating multi-omics-preferably in real-time during surgery-promises to guide patient selection and optimize neurosurgical decision-making. Although these developments are promising for enhancing surgical strategies and improving patient outcomes, further validation in prospective studies involving larger cohorts and the development of workflows for clinical practice is needed.

Indexed as

Biomarkers, TumorBrain NeoplasmsClinical Decision-MakingGlioblastomaNeurosurgical ProceduresDecision MakingHumansBiomarkers, Tumor

Identifiers

PMID40037513
PMCPMC12309719

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.