Evidence map›Paper›PMID 38702557›Full record

ArticleWorld journal of urology2024

Predicting clinically significant prostate cancer following suspicious mpMRI: analyses from a high-volume center.

Matthias Jahnen, Tanja Hausler, Valentin H Meissner, Donna P Ankerst, Michael W Kattan, Andreas Sauter, Juergen E Gschwend, Kathleen Herkommer

Abstract read
In one paragraph

Article in World journal of urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Matthias JahnenDepartment of Urology, School of Medicine and Health, Technical University of Munich (TUM) Rechts der Isar University Hospital, Ismaningerstr. 22, 81675, Munich, Germany. matthias.jahnen@tum.de.ORCID http://orcid.org/0000-0002-5895-2595
Tanja HauslerDepartment of Mathematics, School of Computation, Information, and Technology, Boltzmannstr. 3, 85748, Garching, Germany.
Valentin H MeissnerDepartment of Urology, School of Medicine and Health, Technical University of Munich (TUM) Rechts der Isar University Hospital, Ismaningerstr. 22, 81675, Munich, Germany.
Donna P AnkerstDepartment of Mathematics, School of Computation, Information, and Technology, Boltzmannstr. 3, 85748, Garching, Germany.
Michael W KattanDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, 44195, USA.
Andreas SauterDepartment of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich (TUM) Rechts der Isar University Hospital, Ismaningerstr. 22, 81675, Munich, Germany.
Juergen E GschwendDepartment of Urology, School of Medicine and Health, Technical University of Munich (TUM) Rechts der Isar University Hospital, Ismaningerstr. 22, 81675, Munich, Germany.
Kathleen HerkommerDepartment of Urology, School of Medicine and Health, Technical University of Munich (TUM) Rechts der Isar University Hospital, Ismaningerstr. 22, 81675, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposempMRI is routinely used to stratify the risk of clinically significant prostate cancer (csPCa) in men with elevated PSA values before biopsy. This study aimed to calculate a multivariable risk model incorporating standard risk factors and mpMRI findings for predicting csPCa on subsequent prostate biopsy.

methodsData from 677 patients undergoing mpMRI ultrasound fusion biopsy of the prostate at the TUM University Hospital tertiary urological center between 2019 and 2023 were analyzed. Patient age at biopsy (67 (median); 33-88 (range) (years)), PSA (7.2; 0.3-439 (ng/ml)), prostate volume (45; 10-300 (ml)), PSA density (0.15; 0.01-8.4), PI-RADS (V.2.0 protocol) score of index lesion (92.2% ≥3), prior negative biopsy (12.9%), suspicious digital rectal examination (31.2%), biopsy cores taken (12; 2-22), and pathological biopsy outcome were analyzed with multivariable logistic regression for independent associations with the detection of csPCa defined as ISUP ≥ 3 (n = 212 (35.2%)) and ISUP ≥ 2 (n = 459 (67.8%) performed on 603 patients with complete information.

resultsOlder age (OR: 1.64 for a 10-year increase; p < 0.001), higher PSA density (OR: 1.60 for a doubling; p < 0.001), higher PI-RADS score of the index lesion (OR: 2.35 for an increase of 1; p < 0.001), and a prior negative biopsy (OR: 0.43; p = 0.01) were associated with csPCa.

conclusionmpMRI findings are the dominant predictor for csPCa on follow-up prostate biopsy. However, PSA density, age, and prior negative biopsy history are independent predictors. They must be considered when discussing the individual risk for csPCa following suspicious mpMRI and may help facilitate the further diagnostical approach.

Indexed as

Multiparametric Magnetic Resonance ImagingProstatic NeoplasmsAdultAgedAged, 80 and overHospitals, High-VolumeHumansImage-Guided BiopsyMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentmpMRIProstate biopsyProstate cancerRisk models

Identifiers

PMID38702557
PMCPMC11068682

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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.