Evidence map›Paper›PMID 33387095›Full record

ReviewCurrent oncology reports2021

Radiogenomics in Interventional Oncology.

Amgad M Moussa, Etay Ziv

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current oncology reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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  10. Construction of an enhanced computed tomography radiomics model for non-invasively predicting granzyme A in head and neck squamous cell carcinoma by machine learning.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2023
    Article
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  15. Article
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  18. Brain Tumor Radiogenomic Classification of OCancer control : journal of the Moffitt Cancer Center
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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

2 authors at 1 institution in 1 country.

Amgad M MoussaDepartment of Interventional Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Suite H-112, New York, NY, 10065, USA.
Etay ZivDepartment of Interventional Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Suite H-112, New York, NY, 10065, USA. zive@mskcc.org.ORCID 0000-0002-3188-0085
Memorial Sloan Kettering Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewRadiogenomics is a growing field that has garnered immense interest over the past decade, owing to its numerous applications in the field of oncology and its potential value in improving patient outcomes. Current applications have only begun to delve into the potential of radiogenomics, and particularly in interventional oncology, there is room for development and increased value of these applications. RECENT

findingsThe field of interventional oncology (IO) has seen valuable radiogenomic applications, from prediction of response to locoregional therapies in hepatocellular carcinoma to identification of genetic mutations in non-small cell lung cancer. Future directions that can increase the value of radiogenomics include applications that address tumor heterogeneity, predict immune responsiveness of tumors, and differentiate between oligoprogression and early widespread progression, among others. Radiogenomics, whether in terms of methodologies or applications, is still in the early stages of development and far from maturation. Future applications, particularly in the field of interventional oncology, will allow realization of its full potential.

Indexed as

NeoplasmsRadiation GenomicsRadiation OncologyArtificial IntelligenceHumansArtificial intelligenceHepatocellular carcinomaInterventional oncologyNon-small cell lung cancerRadiogenomicsRadiomics

Identifiers

PMID33387095
OpenAlexW3113981802

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.