Evidence map›Paper›PMID 33489907›Full record

ArticleFrontiers in oncology2020

Does Multiparametric Magnetic Resonance of Prostate Outperform Risk Calculators in Predicting Prostate Cancer in Biopsy Naïve Patients?

Ugo Giovanni Falagario, Giovanni Silecchia, Salvatore Mariano Bruno, Michele Di Nauta, Mario Auciello, Francesca Sanguedolce, Paola Milillo, Luca Macarini, Oscar Selvaggio, Giuseppe Carrieri and 1 more

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In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
1.5field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 11 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Ugo Giovanni FalagarioDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Giovanni SilecchiaDepartment of Urology, Bonomo Teaching Hospital, Andria, Italy.
Salvatore Mariano BrunoDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Michele Di NautaDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Mario AucielloDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Francesca SanguedolceDepartment of Pathology, University of Foggia, Foggia, Italy.
Paola MililloDepartment of Radiology, University of Foggia, Foggia, Italy.
Luca MacariniDepartment of Radiology, University of Foggia, Foggia, Italy.
Oscar SelvaggioDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Giuseppe CarrieriDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Luigi CormioDepartment of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
University of Foggia · ITOspedale L. Bonomo · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEuropean Association of Urology (EAU) guidelines recommend using risk-calculators (RCs), imaging or additional biomarkers in asymptomatic men at risk of prostate cancer (PCa).

objectivesTo compare the performance of mpMRI, a RC we recently developed and two commonly used RC not including mpMRI in predicting the risk of PCa, as well as the added value of mpMRI to each RC. DESIGN SETTING AND

participantsSingle-center retrospective study evaluating 221 biopsy-naïve patients who underwent prebiopsy mpMRI. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patients' probabilities of any PCa and clinically significant PCa (csPC, defined as Gleason-Score ≥3 + 4) were computed according to mpMRI, European Randomized Study of Screening for Prostate Cancer RC (ERSPC-RC), the Prostate Biopsy Collaborative Group RC (PBCG-RC) and the Foggia Prostate Cancer RC (FPC-RC). Logistic regression, AUC, and Decision curve analysis (DCA) were used to assess the accuracy of tested models. RESULTS AND LIMITATION: The FPC-RC outperformed mpMRI in diagnosing both any PCa (AUC 0.76

conclusionsmpMRI was outperformed by the novel FPC-RC and showed similar performances compared to the PBCG and ERSPC RCs in predicting csPCa. The addition of mpMRI findings improved the diagnostic accuracy of each of these calculators.

Indexed as

clinically significant prostate cancerdecision curve analysismpMRIprostate cancerrisk calculator

Identifiers

PMID33489907
PMCPMC7821426
OpenAlexW3119405748

What OpenQuestion holds

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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.