Evidence map›Paper›PMID 36160762›Full record

ReviewTherapeutic advances in urology

Radiogenomics influence on the future of prostate cancer risk stratification.

Vinayak Banerjee, Shu Wang, Max Drescher, Ryan Russell, M Minhaj Siddiqui

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Therapeutic advances in urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Vinayak BanerjeeDivision of Urology, Department of Surgery, University of Maryland Medical Center, University of Maryland School of Medicine, Baltimore, MD, USA.
Shu WangDivision of Urology, Department of Surgery, University of Maryland Medical Center, University of Maryland School of Medicine, Baltimore, MD, USA.
Max DrescherDivision of Urology, Department of Surgery, University of Maryland Medical Center, University of Maryland School of Medicine, Baltimore, MD, USA.
Ryan RussellDivision of Urology, Department of Surgery, University of Maryland Medical Center, University of Maryland School of Medicine, Baltimore, MD, USA.
M Minhaj SiddiquiDivision of Urology, Department of Surgery, University of Maryland Medical Center, University of Maryland School of Medicine, 29 S. Greene Street, Suite 500, Baltimore, MD 21201, USA.ORCID https://orcid.org/0000-0002-4484-6820

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In an era of powerful computing tools, radiogenomics provides a personalized, precise approach to the detection and diagnosis in patients with prostate cancer (PCa). Radiomics data are obtained through artificial intelligence (AI) and neural networks that analyze imaging, usually MRI, to assess statistical, geometrical, and textural features of images to provide quantitative data of shape, heterogeneity, and intensity of tumors. Genomics involves assessing the genomic markers that are present from tumor biopsies. In this article, we separately investigate the current landscape of radiomics and genomics within the realm of PCa and discuss the integration and validity of both into radiogenomics using the data from three papers on the topic. We also conducted a clinical trials search using the NIH's database, where we found two relevant actively recruiting studies. Although there is more research needed to be done on radiogenomics to fully adopt it as a viable diagnosis tool, its potential by providing personalized data regarding each tumor cannot be overlooked as it may be the future of PCa risk-stratification techniques.

Indexed as

genomicsprostate cancerradiogenomicsradiomicsrisk stratification

Identifiers

PMID36160762
PMCPMC9490455

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.