Evidence map›Paper›PMID 28220802›Full record

Trial reportProstate cancer and prostatic diseases2017

The prostate cancer prevention trial risk calculator 2.0 performs equally for standard biopsy and MRI/US fusion-guided biopsy.

M Maruf, M Fascelli, A K George, M M Siddiqui, M Kongnyuy, J M DiBianco, A Muthigi, S Valayil, A Sidana, T P Frye and 5 more

Open access · greenAbstract readClinical Trial, Phase III
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Prostate cancer and prostatic diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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

15 authors at 4 institutions in 1 country.

M MarufCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
M FascelliCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
A K GeorgeCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
M M SiddiquiDivision of Urology, Department of Surgery, University of Maryland School of Medicine, Baltimore, MD, USA.
M KongnyuyCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
J M DiBiancoCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
A MuthigiCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
S ValayilCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
A SidanaCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
T P FryeCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
A KilchevskyCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
P L ChoykeMolecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
B TurkbeyMolecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
B J WoodCenter for Interventional Oncology, National Cancer Institute & NIH Clinical Center, National Institutes of Health, Bethesda, MD, USA.
P A PintoCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA.
National Cancer Institute · USCenter for Cancer Research · USNational Institutes of Health · USUniversity of Maryland, Baltimore · US

Funding

Center for Interventional OncologyZIDBC011242 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WOOD, BRADFORD J · 2009 to 2025
$18.7M
Prostate SectionZIABC011081 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PINTO, PETER · 2009 to 2025
$15.2M
Prostate Cancer ImagingZ01BC010655 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2005 to 2008
$2.1M
Prostate SectionZ01BC011081 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PINTO, PETER · 2008 to 2008
$99k
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Intramural NIH HHS Z01 BC010655Intramural NIH HHS Z01 BC011081Intramural NIH HHS ZID BC011242
6 · The paper itself

Abstract

backgroundThe Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC) is a widely used risk-based calculator used to assess a man's risk of prostate cancer (PCa) before biopsy. This risk calculator was created from data of a patient cohort undergoing a 6-core sextant biopsy, and subsequently validated in men undergoing 12-core systematic biopsy (SBx). The accuracy of the PCPTRC has not been studied in patients undergoing magnetic resonance imaging/ultrasound (MRI/US) fusion-guided biopsy (FBx). We sought to assess the performance of the PCPTRC for straitifying PCa risk in a FBx cohort.

methodsA review of a prospective cohort undergoing MRI and FBx/SBx was conducted. Data from consecutive FBx/SBx were collected between August 2007 and February 2014, and PCPTRC scores using the PCPTRC2.0R-code were calculated. The risk of positive biopsy and high-grade cancer (Gleason ⩾7) on biopsy was calculated and compared with overall and high-grade cancer detection rates (CDRs). Receiver operating characteristic curves were generated and the areas under the curves (AUCs) were compared using DeLong's test.

resultsOf 595 men included in the study, PCa was detected in 39% (232) by SBx compared with 48% (287) on combined FBx/SBx biopsy. The PCPTRC AUCs for the CDR were similar (P=0.70) for SBx (0.69) and combined biopsy (0.70). For high-grade disease, AUCs for SBx (0.71) and combined biopsy (0.70) were slightly higher, but were not statistically different (P=0.55).

conclusionsIn an MRI-screened population of men undergoing FBx, PCPTRC continues to represent a practical method of accurately stratifying PCa risk.

Indexed as

AgedEarly Detection of CancerEndoscopic Ultrasound-Guided Fine Needle AspirationHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleMiddle AgedProstateProstatic NeoplasmsRisk Assessment

Identifiers

PMID28220802
PMCPMC7900903
OpenAlexW2589497564

What OpenQuestion holds

Textmetadata
LicenceTDM
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.