Evidence map›Paper›PMID 28762373›Full record

ArticleProstate cancer and prostatic diseases2017

Changes in prostate cancer detection rate of MRI-TRUS fusion vs systematic biopsy over time: evidence of a learning curve.

B Calio, A Sidana, D Sugano, S Gaur, A Jain, M Maruf, S Xu, P Yan, J Kruecker, M Merino and 4 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article 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 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
7.4field-weighted citation impact, top 2% 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.

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  19. Characterizing the learning curve of MRI-US fusion prostate biopsies.Prostate cancer and prostatic diseases · 2019
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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

14 authors at 2 institutions in 1 country.

B CalioUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
A SidanaUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
D SuganoUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
S GaurMolecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
A JainUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
M MarufUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
S XuCenter for Interventional Oncology, National Cancer Institute and Clinical Center, National Institutes of Health, Bethesda, MD, USA.
P YanCenter for Interventional Oncology, National Cancer Institute and Clinical Center, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-9779-2141
J KrueckerCenter for Interventional Oncology, National Cancer Institute and Clinical Center, National Institutes of Health, Bethesda, MD, USA.
M MerinoCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
P 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 WoodCenter for Interventional Oncology, National Cancer Institute and Clinical Center, National Institutes of Health, Bethesda, MD, USA.
P PintoUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
National Institutes of Health · USNational Cancer Institute · US

Funding

Center for Interventional OncologyZIDBC011242 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WOOD, BRADFORD J · 2009 to 2025
$18.7M
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
Navigation Tools for Image Guided Minimally invasive TherapiesZIACL040011 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
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

backgroundTo determine the effect of urologist and radiologist learning curves and changes in MRI-TRUS fusion platform during 9 years of NCI's experience with multiparametric magnetic resonance imaging (mpMRI)/TRUS fusion biopsy.

methodsA prospectively maintained database of patients undergoing mpMRI followed by fusion biopsy (Fbx) and systematic biopsy (Sbx) from 2007 to 2016 was reviewed. The patients were stratified based on the timing of first biopsy. Cohort 1 (7/2007-12/2010) accounted for learning curve. Cohort 2 (1/2011-5/2013) and cohort 3 (5/2013-4/2016) included patients biopsied prior to and after debut of a new software platform, respectively. Clinically significant (CS) disease was defined as Gleason 7 (3+4) or higher. McNemar's test compared cancer detection rates (CDRs) of Sbx and Fbx between time periods.

results1528 patients were included in the study with 230, 537 and 761 patients included in three respective cohorts. Median age (interquartile range) was 61.0 (±9.0), 62.0 (±7.3), and 64.0 (±11.0) years in three cohorts, respectively (P<0.001). Fbx and Sbx had comparable CS CDR in cohort 1 (24.8 vs 22.2%, P=0.377). Fbx detected significantly more CS disease compared to Sbx in the following two periods (cohort 2: 31.5 vs 25.0%, P=0.001; cohort 3: 36.4 vs 30.3%, P<0.001) and detected significantly less low risk disease in the same period (cohort 2: 14.5 vs 19.6%, P<0.001; cohort 3: 12.6 vs 16.7%, P<0.001). Even after multivariate adjustment with age, PSA, race, clinical stage and MRI suspicion score, Fbx CS cancer detection increased in successive cohorts (cohort 2: OR 2.23, P=0.043; cohort 3: OR 2.92, P=0.007).

conclusionsIn the past 9 years, there has been significant improvement in the accuracy of Fbx. Our results show that after an early learning period, Fbx detected higher rates of CS cancer and lower rates of clinically insignificant cancer than Sbx. Software advances allowed for even greater detection of CS disease.

Indexed as

AgedBiopsyEndoscopic Ultrasound-Guided Fine Needle AspirationHumansImage-Guided BiopsyLearning CurveMagnetic Resonance ImagingMaleMass ScreeningMiddle AgedNeoplasm GradingProstateProstatic Neoplasms

Identifiers

PMID28762373
PMCPMC8170829
OpenAlexW2739848496

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.