Evidence map›Paper›PMID 33661541›Full record

ArticleCancer reports (Hoboken, N.J.)2021

A 4K score/MRI-based nomogram for predicting prostate cancer, clinically significant prostate cancer, and unfavorable prostate cancer.

Vinayak G Wagaskar, Stanislaw Sobotka, Parita Ratnani, James Young, Anna Lantz, Sneha Parekh, Ugo Giovanni Falagario, Li Li, Sara Lewis, Kenneth Haines and 3 more

Abstract readValidation Study
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  20. Advancements in Biomarkers of Prostate Cancer: A Review.Technology in cancer research & treatment
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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

13 authors.

Vinayak G WagaskarDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.ORCID 0000-0001-8027-6661
Stanislaw SobotkaDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Parita RatnaniDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
James YoungDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Anna LantzDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.ORCID 0000-0002-5335-8028
Sneha ParekhDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Ugo Giovanni FalagarioDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.ORCID 0000-0002-1152-3005
Li LiDepartment of Pathology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Sara LewisDepartment of Radiology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Kenneth HainesDepartment of Pathology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Sanoj PunnenDepartment of Urology, University of Miami, Miller School of Medicine, Miami, Florida, USA.
Peter WiklundDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.
Ash TewariDepartment of Urology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe detection of prostate cancer requires histological confirmation in biopsy core. Currently, number of unnecessary prostate biopsies are being performed in the United States. This is due to the absence of appropriate biopsy decision-making protocol.

aimTo develop and validate a 4K score/multiparametric magnetic resonance imaging (mpMRI)-based nomogram to predict prostate cancer (PCa), clinically significant prostate cancer (csPCa), and unfavorable prostate cancer (uPCa). METHODS AND

resultsRetrospective, single-center study evaluating a cohort of 574 men with 4K score test >7% or suspicious digital rectal examination (DRE) or Prostate Imaging Reporting and Data System (PI-RADS) scores 3, 4, or 5 on mpMRI that underwent systematic and/or mpMRI/ultrasound fusion-targeted prostate biopsy between 2016 and 2020. External cohort included 622 men. csPCa and uPCa were defined as Gleason score ≥3 + 4 and ≥4 + 3 on biopsy, respectively. Multivariable logistic regression analysis was performed to build nomogram for predicting PCa, csPCa, and uPCa. Validation was performed by plotting the area under the curve (AUC) and comparing nomogram-predicted probabilities with actual rates of PCa, csPCa, and uPCa probabilities in the external cohort. 4K score, a PI-RADS ≥4, prostate volume and prior negative biopsy were significant predictors of PCa, csPCa, and uPCa. AUCs were 0.84, 0.88, and 0.86 for the prediction of PCa, csPCa, and uPCa, respectively. The predicted and actual rates of PCa, csPCa, and uPCa showed agreement across all percentage probability ranges in the validation cohort. Using the prediction model at threshold of 30, 30% of overall biopsies, 41% of benign biopsies, and 19% of diagnosed indolent PCa could be avoided, while missing 9% of csPCa.

conclusionThis novel nomogram would reduce unnecessary prostate biopsies and decrease detection of clinically insignificant PCa.

Indexed as

Decision Support TechniquesMultiparametric Magnetic Resonance ImagingNomogramsAgedBiopsy, Large-Core NeedleClinical Decision-MakingDigital Rectal ExaminationHumansMaleMedical OveruseMiddle AgedMultimodal ImagingNeoplasm GradingProstateProstatic NeoplasmsRetrospective Studies4K score testbiopsymultiparametric MRIprostate cancer

Identifiers

PMID33661541
PMCPMC8388161

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.