Evidence map›Paper›PMID 31992607›Full record

ArticleBMJ open2020

Genetic landscape of prostate cancer conspicuity on multiparametric MRI: a protocol for a systematic review and bioinformatic analysis.

Joseph M Norris, Benjamin S Simpson, Marina A Parry, Clare Allen, Rhys Ball, Alex Freeman, Daniel Kelly, Alex Kirkham, Veeru Kasivisvanathan, Hayley C Whitaker and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Conspicuity of prostate cancer on multiparametric magnetic resonance imaging: A cross-disciplinary translational hypothesis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2020
    Article
  5. Article
  6. 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

11 authors at 4 institutions in 1 country.

Joseph M NorrisUCL Division of Surgery & Interventional Science, University College London, London, UK joseph.norris@ucl.ac.uk.ORCID 0000-0003-2294-0303
Benjamin S SimpsonUCL Division of Surgery & Interventional Science, University College London, London, UK.ORCID 0000-0003-3685-6110
Marina A ParryUCL Cancer Institute, University College London, London, UK.
Clare AllenDepartment of Radiology, University College London Hospitals NHS Foundation Trust, London, UK.
Rhys BallDepartment of Pathology, University College London Hospitals NHS Foundation Trust, London, UK.
Alex FreemanDepartment of Pathology, University College London Hospitals NHS Foundation Trust, London, UK.
Daniel KellySchool of Healthcare Sciences, Cardiff University, Cardiff, South Glamorgan, UK.
Alex KirkhamDepartment of Radiology, University College London Hospitals NHS Foundation Trust, London, UK.
Veeru KasivisvanathanUCL Division of Surgery & Interventional Science, University College London, London, UK.ORCID 0000-0002-0832-382X
Hayley C WhitakerUCL Division of Surgery & Interventional Science, University College London, London, UK.
Mark EmbertonUCL Division of Surgery & Interventional Science, University College London, London, UK.
University College London · GBUniversity College London Hospitals NHS Foundation Trust · GBCardiff University · GBCRUK Lung Cancer Centre of Excellence · GB

Funding

Cancer Research UK 27935Medical Research Council MR/S00680X/1
6 · The paper itself

Abstract

introductionThe introduction of multiparametric MRI (mpMRI) has enabled enhanced risk stratification for men at risk of prostate cancer, through accurate prebiopsy identification of clinically significant disease. However, approximately 10%-20% of significant prostate cancer may be missed on mpMRI. It appears that the genomic basis of lesion visibility or invisibility on mpMRI may have key implications for prognosis and treatment. Here, we describe a protocol for the first systematic review and novel bioinformatic analysis of the genomic basis of prostate cancer conspicuity on mpMRI. METHODS AND ANALYSIS: A systematic search of MEDLINE, PubMed, EMBASE and Cochrane databases will be conducted. Screening, data extraction, statistical analysis and reporting will be performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included papers will be full text articles, written between January 1980 and December 2019, comparing molecular characteristics of mpMRI-visible lesions and mpMRI-invisible lesions at the DNA, DNA-methylation, RNA or protein level. Study bias and quality will be assessed using a modified Newcastle-Ottawa score. Additionally, we will conduct a novel bioinformatic analysis of supplementary material and publicly available data, to combine transcriptomic data and reveal common pathways highlighted across studies. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist. ETHICS AND DISSEMINATION: Ethical approval will not be required, as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals, and presentations at national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42019147423.

Indexed as

Computational BiologyGenomicsHumansImage-Guided BiopsyMaleMultiparametric Magnetic Resonance ImagingNeoplasm GradingProstatic NeoplasmsResearch DesignRisk FactorsSystematic Reviews as TopicTumor Burdencancer geneticsmagnetic resonance imagingprostate diseaseurological tumours

Identifiers

PMID31992607
PMCPMC7045175
OpenAlexW3004366826

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.