Combined Clinical Parameters and Multiparametric Magnetic Resonance Imaging for the Prediction of Extraprostatic Disease-A Risk Model for Patient-tailored Risk Stratification When Planning Radical Prostatectomy.
Extraprostatic extension
Magnetic resonance imaging
Nomogram
Prostate cancer
Radical prostatectomy
Risk model
Journal
European urology focus
ISSN: 2405-4569
Titre abrégé: Eur Urol Focus
Pays: Netherlands
ID NLM: 101665661
Informations de publication
Date de publication:
15 11 2020
15 11 2020
Historique:
received:
15
09
2018
revised:
19
10
2018
accepted:
10
11
2018
pubmed:
28
11
2018
medline:
16
7
2021
entrez:
28
11
2018
Statut:
ppublish
Résumé
Multiparametric magnetic resonance imaging (mpMRI) facilitates the detection of significant prostate cancer. Therefore, addition of mpMRI to clinical parameters might improve the prediction of extraprostatic extension (EPE) in radical prostatectomy (RP) specimens. To investigate the accuracy of a novel risk model (RM) combining clinical and mpMRI parameters to predict EPE in RP specimens. We added prebiopsy mpMRI to clinical parameters and developed an RM to predict individual side-specific EPE (EPE-RM). Clinical parameters of 264 consecutive men with mpMRI prior to MRI/transrectal ultrasound fusion biopsy and subsequent RP between 2012 and 2015 were retrospectively analysed. Multivariate regression analyses were used to determine significant EPE predictors for RM development. The prediction performance of the novel EPE-RM was compared with clinical T stage (cT), MR-European Society of Urogenital Radiology (ESUR) classification for EPE, two established nomograms (by Steuber et al and Ohori et al) and a clinical nomogram based on the coefficients of the established nomograms, and was constructed based on the data of the present cohort, using receiver operating characteristics (ROCs). For comparison, models' likelihood ratio (LR) tests and Vuong tests were used. Discrimination and calibration of the EPE-RM were validated based on resampling methods using bootstrapping. International society of Urogenital Pathology grade on biopsy, ESUR criteria, prostate-specific antigen, cT, prostate volume, and capsule contact length were included in the EPE-RM. Calibration of the EPE-RM was good (error 0.018). The ROC area under the curve for the EPE-RM was larger (0.87) compared with cT (0.66), Memorial Sloan Kettering Cancer Center nomogram (0.73), Steuber nomogram (0.70), novel clinical nomogram (0.79), and ESUR classification (0.81). Based on LR and Vuong tests, the EPE-RM's model fit was significantly better than that of cT, all clinical models, and ESUR classification alone (p<0.001). Limitations include monocentric design and expert reading of MRI. This novel EPE-RM, incorporating clinical and MRI parameters, performed better than contemporary clinical RMs and MRI predictors, therefore providing an accurate patient-tailored preoperative risk stratification of side-specific EPE. Extraprostatic extension of prostate cancer can be predicted accurately using a combination of magnetic resonance imaging and clinical parameters. This novel risk model outperforms magnetic resonance imaging and clinical predictors alone and can be useful when planning nerve-sparing radical prostatectomy.
Sections du résumé
BACKGROUND
Multiparametric magnetic resonance imaging (mpMRI) facilitates the detection of significant prostate cancer. Therefore, addition of mpMRI to clinical parameters might improve the prediction of extraprostatic extension (EPE) in radical prostatectomy (RP) specimens.
OBJECTIVE
To investigate the accuracy of a novel risk model (RM) combining clinical and mpMRI parameters to predict EPE in RP specimens.
DESIGN, SETTING, AND PARTICIPANTS
We added prebiopsy mpMRI to clinical parameters and developed an RM to predict individual side-specific EPE (EPE-RM). Clinical parameters of 264 consecutive men with mpMRI prior to MRI/transrectal ultrasound fusion biopsy and subsequent RP between 2012 and 2015 were retrospectively analysed.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
Multivariate regression analyses were used to determine significant EPE predictors for RM development. The prediction performance of the novel EPE-RM was compared with clinical T stage (cT), MR-European Society of Urogenital Radiology (ESUR) classification for EPE, two established nomograms (by Steuber et al and Ohori et al) and a clinical nomogram based on the coefficients of the established nomograms, and was constructed based on the data of the present cohort, using receiver operating characteristics (ROCs). For comparison, models' likelihood ratio (LR) tests and Vuong tests were used. Discrimination and calibration of the EPE-RM were validated based on resampling methods using bootstrapping.
RESULTS AND LIMITATIONS
International society of Urogenital Pathology grade on biopsy, ESUR criteria, prostate-specific antigen, cT, prostate volume, and capsule contact length were included in the EPE-RM. Calibration of the EPE-RM was good (error 0.018). The ROC area under the curve for the EPE-RM was larger (0.87) compared with cT (0.66), Memorial Sloan Kettering Cancer Center nomogram (0.73), Steuber nomogram (0.70), novel clinical nomogram (0.79), and ESUR classification (0.81). Based on LR and Vuong tests, the EPE-RM's model fit was significantly better than that of cT, all clinical models, and ESUR classification alone (p<0.001). Limitations include monocentric design and expert reading of MRI.
CONCLUSIONS
This novel EPE-RM, incorporating clinical and MRI parameters, performed better than contemporary clinical RMs and MRI predictors, therefore providing an accurate patient-tailored preoperative risk stratification of side-specific EPE.
PATIENT SUMMARY
Extraprostatic extension of prostate cancer can be predicted accurately using a combination of magnetic resonance imaging and clinical parameters. This novel risk model outperforms magnetic resonance imaging and clinical predictors alone and can be useful when planning nerve-sparing radical prostatectomy.
Identifiants
pubmed: 30477971
pii: S2405-4569(18)30336-5
doi: 10.1016/j.euf.2018.11.004
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1205-1212Informations de copyright
Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.