EURURO Vol. 72 No. 6

888 1030

Platinum Priority – Prostate Cancer
Editorial by Thomas Hermanns and Ce´dric Poyet on pp. 897–898 of this issue
Combined Clinical Parameters and Multiparametric Magnetic
Resonance Imaging for Advanced Risk Modeling of Prostate
Cancer—Patient-tailored Risk Stratification Can Reduce
Unnecessary Biopsies
Jan Philipp Radtke Manuel Wiesenfarth Claudia Kesch Martin T. Freitag
Celine D. Alt Kamil Celik Florian Distler y, Wilfried Roth , Kathrin Wieczorek
Christian Stock Stefan Duensing Matthias C. Roethke Dogu Teber
Heinz-Peter Schlemmer Markus Hohenfellner David Bonekamp Boris A. Hadaschik
a Department of Urology, University Hospital Heidelberg, Heidelberg, Germany; b Department of Radiology, German Cancer Research Center (DKFZ),
Heidelberg, Germany; cDivision of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany; d Department of Diagnostic and
Interventional Radiology, University[1_TD$DIFF] Du¨sseldorf[6_TD$DIFF], Medical Faculty, Du¨sseldorf, Germany; e Institute of Pathology, University of Heidelberg, Heidelberg,
Germany; f Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Heidelberg, Germany
available at
journal homepage:
Article info
Article history:
Accepted March 27, 2017
Associate Editor:
Matthew Cooperberg
Keywords:
Prostate cancer
Magnetic resonance imaging
European Randomised Study of
Screening for Prostate Cancer
Risk model
Risk stratification
Multiparametric magnetic
resonance imaging
Abstract
Background: Multiparametric magnetic resonance imaging (mpMRI) is gaining wide-
spread acceptance in prostate cancer (PC) diagnosis and improves significant PC (sPC;
Gleason score 3 + 4) detection. Decision making based on European Randomised
Study of Screening for PC (ERSPC) risk-calculator (RC) parameters may overcome
prostate-specific antigen (PSA) limitations.
Objective: We added pre-biopsy mpMRI to ERSPC-RC parameters and developed risk
models (RMs) to predict individual sPC risk for biopsy-naı¨vemen and men after previous
biopsy.
Design, setting, and participants: We retrospectively analyzed clinical parameters of
1159 men who underwent mpMRI prior to MRI/transrectal ultrasound fusion biopsy
between 2012 and 2015.
Outcome measurements and statistical analysis: Multivariate regression analyses were
used to determine significant sPC predictors for RM development. The prediction
performance was compared with ERSPC-RCs, RCs refitted on our cohort, Prostate
Imaging Reporting and Data System (PI-RADS) v1.0, and ERSPC-RC plus PI-RADSv1.0
using receiver-operating characteristics (ROCs). Discrimination and calibration of the
RM, as well as net decision and reduction curve analyses were evaluated based on
resampling methods.
y Present address: Department of Urology, Paracelsus Medical University Nuremberg, Nuremberg,
Germany.
z Present address: Institute of Pathology, University Medicine Mainz, Germany.
§ These authors contributed equally to this work.
k Present address: Department of Urology, University Hospital Essen, Essen, Germany.
* Corresponding author. Department of Urology, University Hospital Heidelberg, Im Neuenheimer
Feld 110, Heidelberg 69120, Germany. Tel. +49 6221 56 36321; Fax: +49 6221 56 5366.
E-mail address: (J.P. Radtke).
0302-2838/# 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.