TY - JOUR
T1 - An updated model for predicting side-specific extraprostatic extension in the era of MRI-targeted biopsy
AU - Martini, Alberto
AU - Wever, Lieke
AU - Soeterik, Timo F W
AU - Rakauskas, Arnas
AU - Fankhauser, Christian Daniel
AU - Grogg, Josias Bastian
AU - Checcucci, Enrico
AU - Amparore, Daniele
AU - Haiquel, Luciano
AU - Rodriguez-Sanchez, Lara
AU - Ploussard, Guillaume
AU - Qiang, Peng
AU - Affentranger, Andres
AU - Marquis, Alessandro
AU - Marra, Giancarlo
AU - Ettala, Otto
AU - Zattoni, Fabio
AU - Falagario, Ugo Giovanni
AU - De Angelis, Mario
AU - Kesch, Claudia
AU - Apfelbeck, Maria
AU - Al-Hammouri, Tarek
AU - Kretschmer, Alexander
AU - Kasivisvanathan, Veeru
AU - Preisser, Felix
AU - Lefebvre, Emilie
AU - Olivier, Jonathan
AU - Radtke, Jan Philipp
AU - Carrieri, Giuseppe
AU - Moro, Fabrizio Dal
AU - Boström, Peter
AU - Jambor, Ivan
AU - Gontero, Paolo
AU - Chiu, Peter K
AU - John, Hubert
AU - Macek, Petr
AU - Porpiglia, Francesco
AU - Hermanns, Thomas
AU - van den Bergh, Roderick C N
AU - van Basten, Jean-Paul A
AU - Young Academic Urologists working group on Prostate Cancer of the European Association of Urology
AU - Gandaglia, Giorgio
AU - Valerio, Massimo
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature Limited 2024.
PY - 2024/9
Y1 - 2024/9
N2 - PURPOSE: Accurate prediction of extraprostatic extension (EPE) is pivotal for surgical planning. Herein, we aimed to provide an updated model for predicting EPE among patients diagnosed with MRI-targeted biopsy.MATERIALS AND METHODS: We analyzed a multi-institutional dataset of men with clinically localized prostate cancer diagnosed by MRI-targeted biopsy and subsequently underwent prostatectomy. To develop a side-specific predictive model, we considered the prostatic lobes separately. A multivariable logistic regression analysis was fitted to predict side-specific EPE. The decision curve analysis was used to evaluate the net clinical benefit. Finally, a regression tree was employed to identify three risk categories to assist urologists in selecting candidates for nerve-sparing, incremental nerve sparing and non-nerve-sparing surgery.RESULTS: Overall, data from 3169 hemi-prostates were considered, after the exclusion of prostatic lobes with no biopsy-documented tumor. EPE was present on final pathology in 1,094 (34%) cases. Among these, MRI was able to predict EPE correctly in 568 (52%) cases. A model including PSA, maximum diameter of the index lesion, presence of EPE on MRI, highest ISUP grade in the ipsilateral hemi-prostate, and percentage of positive cores in the ipsilateral hemi-prostate achieved an AUC of 81% after internal validation. Overall, 566, 577, and 2,026 observations fell in the low-, intermediate- and high-risk groups for EPE, as identified by the regression tree. The EPE rate across the groups was: 5.1%, 14.9%, and 48% for the low-, intermediate- and high-risk group, respectively.CONCLUSION: In this study we present an update of the first side-specific MRI-based nomogram for the prediction of extraprostatic extension together with updated risk categories to help clinicians in deciding on the best approach to nerve-preservation.
AB - PURPOSE: Accurate prediction of extraprostatic extension (EPE) is pivotal for surgical planning. Herein, we aimed to provide an updated model for predicting EPE among patients diagnosed with MRI-targeted biopsy.MATERIALS AND METHODS: We analyzed a multi-institutional dataset of men with clinically localized prostate cancer diagnosed by MRI-targeted biopsy and subsequently underwent prostatectomy. To develop a side-specific predictive model, we considered the prostatic lobes separately. A multivariable logistic regression analysis was fitted to predict side-specific EPE. The decision curve analysis was used to evaluate the net clinical benefit. Finally, a regression tree was employed to identify three risk categories to assist urologists in selecting candidates for nerve-sparing, incremental nerve sparing and non-nerve-sparing surgery.RESULTS: Overall, data from 3169 hemi-prostates were considered, after the exclusion of prostatic lobes with no biopsy-documented tumor. EPE was present on final pathology in 1,094 (34%) cases. Among these, MRI was able to predict EPE correctly in 568 (52%) cases. A model including PSA, maximum diameter of the index lesion, presence of EPE on MRI, highest ISUP grade in the ipsilateral hemi-prostate, and percentage of positive cores in the ipsilateral hemi-prostate achieved an AUC of 81% after internal validation. Overall, 566, 577, and 2,026 observations fell in the low-, intermediate- and high-risk groups for EPE, as identified by the regression tree. The EPE rate across the groups was: 5.1%, 14.9%, and 48% for the low-, intermediate- and high-risk group, respectively.CONCLUSION: In this study we present an update of the first side-specific MRI-based nomogram for the prediction of extraprostatic extension together with updated risk categories to help clinicians in deciding on the best approach to nerve-preservation.
UR - http://www.scopus.com/inward/record.url?scp=85181446267&partnerID=8YFLogxK
U2 - 10.1038/s41391-023-00776-x
DO - 10.1038/s41391-023-00776-x
M3 - Article
C2 - 38182804
SN - 1365-7852
VL - 27
SP - 520
EP - 524
JO - Prostate Cancer and Prostatic Diseases
JF - Prostate Cancer and Prostatic Diseases
IS - 3
ER -
