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An updated model for predicting side-specific extraprostatic extension in the era of MRI-targeted biopsy

Abstract

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.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Urological Clinic
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Oncology
Health Sciences > Urology
Life Sciences > Cancer Research
Language:English
Date:1 September 2024
Deposited On:21 Feb 2024 07:40
Last Modified:31 Oct 2024 02:36
Publisher:Nature Publishing Group
ISSN:1365-7852
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/s41391-023-00776-x
PubMed ID:38182804

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