Evidence map›Paper›PMID 27400645›Full record

ReviewFuture oncology (London, England)2016

Risk stratification of prostate cancer: integrating multiparametric MRI, nomograms and biomarkers.

Matthew J Watson, Arvin K George, Mahir Maruf, Thomas P Frye, Akhil Muthigi, Michael Kongnyuy, Subin G Valayil, Peter A Pinto

Abstract readReview
In one paragraph

Review in Future oncology (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

8 authors.

Matthew J WatsonUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Arvin K GeorgeUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Mahir MarufUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Thomas P FryeUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Akhil MuthigiUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Michael KongnyuyUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Subin G ValayilUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Peter A PintoUrological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.

Funding

Prostate SectionZIABC011081 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PINTO, PETER · 2009 to 2025
$15.2M
6 · The paper itself

Abstract

Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.

Indexed as

NomogramsBiomarkersHumansMagnetic Resonance ImagingMaleMass ScreeningNeoplasm StagingPopulation SurveillancePrognosisProstatic NeoplasmsRiskBiomarkersbiomarkersmultiparametric MRInomogramsprostateprostate cancer

Identifiers

PMID27400645
PMCPMC5066119

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.