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Predicting Pathological Features at Radical Prostatectomy in Patients with Prostate Cancer Eligible for Active Surveillance by Multiparametric Magnetic Resonance Imaging.

Authors :
de Cobelli O
Terracciano D
Tagliabue E
Raimondi S
Bottero D
Cioffi A
Jereczek-Fossa B
Petralia G
Cordima G
Almeida GL
Lucarelli G
Buonerba C
Matei DV
Renne G
Di Lorenzo G
Ferro M
Source :
PloS one [PLoS One] 2015 Oct 07; Vol. 10 (10), pp. e0139696. Date of Electronic Publication: 2015 Oct 07 (Print Publication: 2015).
Publication Year :
2015

Abstract

Purpose: The aim of this study was to investigate the prognostic performance of multiparametric magnetic resonance imaging (mpMRI) and Prostate Imaging Reporting and Data System (PIRADS) score in predicting pathologic features in a cohort of patients eligible for active surveillance who underwent radical prostatectomy.<br />Methods: A total of 223 patients who fulfilled the criteria for "Prostate Cancer Research International: Active Surveillance", were included. Mp-1.5 Tesla MRI examination staging with endorectal coil was performed at least 6-8 weeks after TRUS-guided biopsy. In all patients, the likelihood of the presence of cancer was assigned using PIRADS score between 1 and 5. Outcomes of interest were: Gleason score upgrading, extra capsular extension (ECE), unfavorable prognosis (occurrence of both upgrading and ECE), large tumor volume (≥ 0.5 ml), and seminal vesicle invasion (SVI). Receiver Operating Characteristic (ROC) curves and Decision Curve Analyses (DCA) were performed for models with and without inclusion of PIRADS score.<br />Results: Multivariate analysis demonstrated the association of PIRADS score with upgrading (P < 0.0001), ECE (P < 0.0001), unfavorable prognosis (P < 0.0001), and large tumor volume (P = 0.002). ROC curves and DCA showed that models including PIRADS score resulted in greater net benefit for almost all the outcomes of interest, with the only exception of SVI.<br />Conclusions: mpMRI and PIRADS scoring are feasible tools in clinical setting and could be used as decision-support systems for a more accurate selection of patients eligible for AS.

Details

Language :
English
ISSN :
1932-6203
Volume :
10
Issue :
10
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
26444548
Full Text :
https://doi.org/10.1371/journal.pone.0139696