Evidence map›Paper›PMID 33117714›Full record

ArticleFrontiers in oncology2020

Management of Diffuse Low-Grade Glioma: The Renaissance of Robust Evidence.

Karanbir Brar, Laureen D Hachem, Jetan H Badhiwala, Christine Mau, Brad E Zacharia, Fabio Ynoe de Moraes, Farhad Pirouzmand, Alireza Mansouri

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.International journal of molecular sciences · 2021
    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

8 authors at 3 institutions in 2 countries.

Karanbir BrarFaculty of Medicine, University of Toronto, Toronto, ON, Canada.
Laureen D HachemDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Jetan H BadhiwalaDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Christine MauDepartment of Neurosurgery, Penn State Health, Hershey, PA, United States.
Brad E ZachariaDepartment of Neurosurgery, Penn State Health, Hershey, PA, United States.
Fabio Ynoe de MoraesDivision of Radiation Oncology, Department of Oncology, Kingston General Hospital, Queen's University, Kingston, ON, Canada.
Farhad PirouzmandDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Alireza MansouriDepartment of Neurosurgery, Penn State Health, Hershey, PA, United States.
University of Toronto · CAPenn State Milton S. Hershey Medical Center · USQueen's University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The surgical management of diffuse low-grade gliomas (DLGGs) has undergone a paradigm shift toward striving for maximal safe resection when feasible. While extensive observational data supports this transition, unbiased evidence in the form of high quality randomized-controlled trials (RCTs) is lacking. Furthermore, despite a high volume of molecular, genetic, and imaging data, the field of neuro-oncology lacks personalized care algorithms for individuals with DLGGs based on a robust foundation of evidence. In this manuscript, we (1) discuss the logistical and philosophical challenges hindering the development of surgical RCTs for DLGGs, (2) highlight the potential impact of well-designed international prospective observational registries, (3) discuss ways in which cutting-edge computational techniques can be harnessed to generate maximal insight from high volumes of multi-faceted data, and (4) outline a comprehensive plan of action that will enable a multi-disciplinary approach to future DLGG management, integrating advances in clinical medicine, basic molecular research and large-scale data mining.

Indexed as

artificial intelligencediffuse low-grade gliomamachine learningneuro-oncologyneurosurgeryrandomized controlled trials

Identifiers

PMID33117714
PMCPMC7560299
OpenAlexW3089860800

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.