Evidence map›Paper›PMID 39302458›Full record

ArticleWorld journal of urology2024

Bicenter validation of a risk model for the preoperative prediction of extraprostatic extension of localized prostate cancer combining clinical and multiparametric MRI parameters.

Nicola Edith von Ostau, Analena Elisa Handke, Manuel Wiesenfarth, Peter Albers, Gerald Antoch, Joachim Noldus, Henning Reis, Cristina Cotarelo, Julia Preetz, Lale Umutlu and 5 more

Abstract readValidation StudyMulticenter Study
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  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.

Nicola Edith von Ostau *Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany. nicola.vonostau@uk-essen.de.
Analena Elisa Handke *Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.ORCID http://orcid.org/0009-0000-9472-8956
Manuel WiesenfarthDivision of Biostatistics, German Cancer Research Center, Heidelberg, Germany.
Peter AlbersDepartment of Urology, University Hospital Düsseldorf, Düsseldorf, Germany.
Gerald AntochMedical Faculty, Department of Diagnostic and Interventional Radiology, University Düsseldorf, D-40225, Dusseldorf, Germany.
Joachim NoldusDepartment of Urology, Ruhr-University Bochum, Marien Hospital, Herne, Germany.
Henning ReisDivision of Pathology, University Hospital Frankfurt, Frankfurt, Germany.
Cristina CotareloDepartment of Pathology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Julia PreetzDepartment of Pathology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Lale UmutluDivision of Radiology, University Hospital Essen, Essen, Germany.
Marc IngenwerthDepartment of Pathology, University Hospital Essen, Essen, Germany.
Jan Philipp RadtkeDepartment of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.
Boris HadaschikDepartment of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.
Lars Schimmöller *Medical Faculty, Department of Diagnostic and Interventional Radiology, University Düsseldorf, D-40225, Dusseldorf, Germany.
Claudia Kesch *Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to validate a previously published risk model (RM) which combines clinical and multiparametric MRI (mpMRI) parameters to predict extraprostatic extension (EPE) of prostate cancer (PC) prior to radical prostatectomy (RP). MATERIALS AND

methodsA previously published RM combining clinical with mpMRI parameters including European Society of Urogenital Radiology (ESUR) classification for EPE was retrospectively evaluated in a cohort of two urological university hospitals in Germany. Consecutive patients (n = 205, January 2015 -June 2021) with available preoperative MRI images, clinical information including PSA, prostate volume, ESUR classification for EPE, histopathological results of MRI-fusion biopsy and RP specimen were included. Validation was performed by receiver operating characteristic analysis and calibration plots. The RM's performance was compared to ESUR criteria.

resultsHistopathological T3 stage was detected in 43% of the patients (n = 89); 45% at Essen and 42% at Düsseldorf. Discrimination performance between pT2 and pT3 of the RM in the entire cohort was AUC = 0.86 (AUC = 0.88 at site 1 and AUC = 0.85 at site 2). Calibration was good over the entire probability range. The discrimination performance of ESUR classification alone was comparable (AUC = 0.87).

conclusionsThe RM showed good discriminative performance to predict EPE for decision-making for RP as a patient-tailored risk stratification. However, when experienced MRI reading is available, standardized MRI reading with ESUR scoring is comparable regarding information outcome. A main limitation is the potentially limited transferability to other populations because of the high prevalence of EPE in our subgroups.

Indexed as

Multiparametric Magnetic Resonance ImagingNeoplasm InvasivenessProstatectomyProstatic NeoplasmsAgedHumansMaleMiddle AgedPredictive Value of TestsPreoperative CareRetrospective StudiesRisk AssessmentExtraprostatic extensionMultiparametric MRIPositive surgical marginsProstate cancer

Identifiers

PMID39302458
PMCPMC11415414

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.