Side-specific, Microultrasound-based Nomogram for the Prediction of Extracapsular Extension in Prostate Cancer

Adriana M Pedraza; Sneha Parekh; Himanshu Joshi; Ralph Grauer; Vinayak Wagaskar; Laura Zuluaga; Raghav Gupta; Flora Barthe; Jordan Nasri; Krunal Pandav; Dhruti Patel; Michael A Gorin; Mani Menon; Ashutosh K Tewari

doi:10.1016/j.euros.2022.12.005

Side-specific, Microultrasound-based Nomogram for the Prediction of Extracapsular Extension in Prostate Cancer

Eur Urol Open Sci. 2022 Dec 28:48:72-81. doi: 10.1016/j.euros.2022.12.005. eCollection 2023 Feb.

Authors

Affiliations

¹ Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
² Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Abstract

Background: Prediction of extracapsular extension (ECE) is essential to achieve a balance between oncologic resection and neural tissue preservation. Microultrasound (MUS) is an attractive alternative to multiparametric magnetic resonance imaging (mpMRI) in the staging scenario.

Objective: To create a side-specific nomogram integrating clinicopathologic parameters and MUS findings to predict ipsilateral ECE and guide nerve sparing.

Design setting and participants: Prospective data were collected from consecutive patients who underwent robotic-assisted radical prostatectomy from June 2021 to May 2022 and had preoperative MUS and mpMRI. A total of 391 patients and 612 lobes were included in the analysis.

Outcome measurements and statistical analysis: ECE on surgical pathology was the primary outcome. Multivariate regression analyses were carried out to identify predictors for ECE. The resultant multivariable model's performance was visualized using the receiver-operating characteristic curve. A nomogram was developed based on the coefficients of the logit function for the MUS-based model. A decision curve analysis (DCA) was performed to assess clinical utility.

Results and limitations: The areas under the receiver-operating characteristic curve (AUCs) of the MUS-based model were 81.4% and 80.9% (95% confidence interval [CI] 75.6, 84.6) after internal validation. The AUC of the mpMRI-model was also 80.9% (95% CI 77.2, 85.7). The DCA demonstrated the net clinical benefit of the MUS-based nomogram and its superiority compared with MUS and MRI alone for detecting ECE. Limitations of our study included its sample size and moderate inter-reader agreement.

Conclusions: We developed a side-specific nomogram to predict ECE based on clinicopathologic variables and MUS findings. Its performance was comparable with that of a mpMRI-based model. External validation and prospective trials are required to corroborate our results.

Patient summary: The integration of clinical parameters and microultrasound can predict extracapsular extension with similar results to models based on magnetic resonance imaging findings. This can be useful for tailoring the preservation of nerves during surgery.

Keywords: Extracapsular extension; Microultrasound; Multiparametric magnetic resonance imaging; Prostate cancer.