Literature DB >> 27919668

Magnetic Resonance Imaging Provides Added Value to the Prostate Cancer Prevention Trial Risk Calculator for Patients With Estimated Risk of High-grade Prostate Cancer Less Than or Equal to 10.

Eric H Kim1, John K Weaver1, Anup S Shetty2, Joel M Vetter1, Gerald L Andriole1, Seth A Strope3.   

Abstract

OBJECTIVE: To determine the added value of prostate magnetic resonance imaging (MRI) to the Prostate Cancer Prevention Trial risk calculator.
METHODS: Between January 2012 and December 2015, 339 patients underwent prostate MRI prior to biopsy at our institution. MRI was considered positive if there was at least 1 Prostate Imaging Reporting and Data System 4 or 5 MRI suspicious region. Logistic regression was used to develop 2 models: biopsy outcome as a function of the (1) Prostate Cancer Prevention Trial risk calculator alone and (2) combined with MRI findings.
RESULTS: When including all patients, the Prostate Cancer Prevention Trial with and without MRI models performed similarly (area under the curve [AUC] = 0.74 and 0.78, P = .06). When restricting the cohort to patients with estimated risk of high-grade (Gleason ≥7) prostate cancer ≤10%, the model with MRI outperformed the Prostate Cancer Prevention Trial alone model (AUC = 0.69 and 0.60, P = .01). Within this cohort of patients, there was no significant difference in discrimination between models for those with previous negative biopsy (AUC = 0.61 vs 0.63, P = .76), whereas there was a significant improvement in discrimination with the MRI model for biopsy-naïve patients (AUC = 0.72 vs 0.60, P = .01).
CONCLUSION: The use of prostate MRI in addition to the Prostate Cancer Prevention Trial risk calculator provides a significant improvement in clinical risk discrimination for patients with estimated risk of high-grade (Gleason ≥7) prostate cancer ≤10%. Prebiopsy prostate MRI should be strongly considered for these patients.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27919668     DOI: 10.1016/j.urology.2016.08.074

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


  6 in total

1.  Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer.

Authors:  Frank-Jan H Drost; Daniël F Osses; Daan Nieboer; Ewout W Steyerberg; Chris H Bangma; Monique J Roobol; Ivo G Schoots
Journal:  Cochrane Database Syst Rev       Date:  2019-04-25

2.  Nonsuspicious prebiopsy multiparametric MRI: is prostate biopsy still necessary?

Authors:  Vassili Anastay; Bastien Gondran-Tellier; Robin McManus; Raphaelle Delonca; Akram Akiki; Sarah Gaillet; Veronique Delaporte; Marc Andre; Laurent Daniel; Gilles Karsenty; Eric Lechevallier; Romain Boissier; Michael Baboudjian
Journal:  Abdom Radiol (NY)       Date:  2020-09-09

3.  Comparative Analysis of PSA Density and an MRI-Based Predictive Model to Improve the Selection of Candidates for Prostate Biopsy.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Pol Servian; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-05-11       Impact factor: 6.575

4.  Prostate cancer risk prediction models in Eastern Asian populations: current status, racial difference, and future directions.

Authors:  Bi-Ming He; Rui Chen; Tian-Qi Sun; Yue Yang; Chun-Lei Zhang; Shan-Cheng Ren; Xu Gao; Ying-Hao Sun
Journal:  Asian J Androl       Date:  2020 Mar-Apr       Impact factor: 3.285

Review 5.  Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review.

Authors:  Marina Triquell; Miriam Campistol; Ana Celma; Lucas Regis; Mercè Cuadras; Jacques Planas; Enrique Trilla; Juan Morote
Journal:  Cancers (Basel)       Date:  2022-09-29       Impact factor: 6.575

6.  The Barcelona Predictive Model of Clinically Significant Prostate Cancer.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Manel Escobar; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Carles Sola; Pol Servian; Daniel Salvador; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-03-21       Impact factor: 6.639

  6 in total

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