Evidence map›Paper›PMID 36960210›Full record

ReviewFrontiers in nutrition2023

Ketogenic therapies for glioblastoma: Understanding the limitations in transitioning from mice to patients.

Angela D Clontz

Open access · goldFull text readReview
In one paragraph

Review in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. 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

1 author at 1 institution in 1 country.

Angela D ClontzDepartment of Nutrition, Meredith College, Raleigh, NC, United States.
Meredith College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma Multiforme is an aggressive brain cancer affecting children and adults frequently resulting in a short life expectancy. Current cancer therapies include surgery and radiation followed by chemotherapy, which due to their ineffectiveness, requires repeated exposure to the same therapies. Since the 1990s, researchers and doctors have explored other therapies, such as diet therapies, to aid in combating gliomas. The ketogenic diet has gained popularity due to Otto Warburg's theory that tumor cells prefer "aerobic glycolysis" and cannot metabolize ketones. The inability of gliomas to use ketones provides an excellent opportunity to weaken the tumor while protecting healthy cells during cancer treatments. This review will examine some of the current research using the ketogenic diet as a form of cancer therapy to determine if this intervention is manageable and effective in patients with glioblastoma. Peer-reviewed articles from 2009 to 2019 were used. The primary objective is to distinguish differences between pre-clinical and clinical research to determine if the ketogenic diet is reproducible from mouse models into humans to determine its effectiveness. The analysis revealed several limitations of the ketogenic diet as an intervention. The effectiveness is more robust in mice than in human studies. Furthermore, tolerability is marginally supported in human studies requiring more reproducible research to validate that the intervention is manageable and effective in patients with glioblastoma.

Indexed as

calorie restrictiondiet interventionglioblastomaketogenic dietlow carbohydrate diet

Identifiers

PMID36960210
PMCPMC10029602
OpenAlexW4323356346

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read159
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.