Literature DB >> 33129868

Multiparametric Magnetic Resonance Imaging Should Be Preferred Over Digital Rectal Examination for Prostate Cancer Local Staging and Disease Risk Classification.

Timo F W Soeterik1, Harm H E van Melick2, Lea M Dijksman3, Douwe H Biesma3, J Alfred Witjes4, Jean-Paul A van Basten5.   

Abstract

OBJECTIVE: To assess the impact of multiparametric magnetic resonance imaging (mp-MRI) local tumor staging on prostate cancer risk stratification and choice of treatment.
MATERIALS AND METHODS: Prostate cancer patients, newly diagnosed from 2017 to 2018 at 7 Dutch teaching hospitals were included. Risk group classification was done twice, using either digital rectal examination (DRE) or mp-MRI information. Risk group migration and rates of treatment intensification associated with mp-MRI upstaging were established. Diagnostic accuracy measures for the detection of nonorgan-confined disease (stage ≥T3a), for both DRE and mp-MRI, were assessed in patients undergoing robot-assisted radical prostatectomy.
RESULTS: A total of 1683 patients were included. Upstaging due to mp-MRI staging occurred in 493 of 1683 (29%) patients and downstaging in 43 of 1683 (3%) patients. Upstaging was associated with significant higher odds for treatment intensification (odds ratio [OR]: 3.5 95% confidence interval [CI] 1.9-6.5). Stage ≥T3a on mp-MRI was the most common reason for risk group upstaging (77%). Sensitivity for the detection of stage ≥T3a was higher for mp-MRI compared to DRE (51% vs 12%, P <.001), whereas specificity was lower (82% vs 97%, P <.001). Mp-MRI resulted in a significantly higher cumulative rate of true positive and true negative stage ≥T3a predictions compared with DRE (67% vs 58%, P <.001).
CONCLUSION: Use of mp-MRI tumor stage for prostate cancer risk classification leads to upstaging in 1 of 3 patients. Mp-MRI enables superior detection of nonorgan-confined disease compared with DRE, and should be the preferred tool for determining clinical tumor stage.
Copyright © 2020 Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 33129868     DOI: 10.1016/j.urology.2020.08.089

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  3 in total

Review 1.  More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis-A Systematic Review.

Authors:  Teodora Telecan; Iulia Andras; Nicolae Crisan; Lorin Giurgiu; Emanuel Darius Căta; Cosmin Caraiani; Andrei Lebovici; Bianca Boca; Zoltan Balint; Laura Diosan; Monica Lupsor-Platon
Journal:  J Pers Med       Date:  2022-06-16

2.  Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population.

Authors:  Artitaya Lophatananon; Matthew H V Byrne; Tristan Barrett; Anne Warren; Kenneth Muir; Ibifuro Dokubo; Fanos Georgiades; Mostafa Sheba; Lisa Bibby; Vincent J Gnanapragasam
Journal:  BMC Cancer       Date:  2022-08-11       Impact factor: 4.638

3.  Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy.

Authors:  Marina Triquell; Lucas Regis; Mathias Winkler; Nicolás Valdés; Mercè Cuadras; Ana Celma; Jacques Planas; Juan Morote; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-08-17       Impact factor: 6.575

  3 in total

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