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Predicting contralateral extraprostatic extension in unilateral high-risk prostate cancer: a multicentric external
Romain Diamand1, Jean-Baptiste Roche2, Vito Lacetera3
1Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Rue Meylemeersch 90, 1070, Brussels, Belgium. romain.diamand@hubruxelles.be.
World Journal of Urology
|April 22, 2024
Summary
Martini et al.'s algorithm accurately predicts contralateral extraprostatic extension (EPE) in unilateral high-risk prostate cancer (PCa) patients. This validation supports its use in guiding radical prostatectomy decisions.
Area of Science:
- Urology
- Oncology
- Medical Imaging
Background:
- Accurate prediction of extraprostatic extension (EPE) is vital for surgical planning in radical prostatectomy (RP), particularly for nerve-sparing techniques.
- Martini et al. developed a three-tier algorithm to predict contralateral EPE in unilateral high-risk prostate cancer (PCa).
Purpose of the Study:
- To externally validate Martini et al.'s three-tier algorithm for predicting contralateral EPE.
- To assess the algorithm's performance in a multicentric European cohort of patients undergoing RP for unilateral high-risk PCa.
Main Methods:
- Retrospective analysis of 208 unilateral high-risk PCa patients treated with RP between January 2016 and November 2021.
- Model performance evaluated using discrimination (AUC), calibration, and decision-curve analysis (DCA) per TRIPOD guidelines.
- Comparison with two established multivariable logistic regression models for predicting side-specific EPE risk.
Main Results:
- The algorithm stratified patients into low (38%), intermediate (48%), and high-risk (14%) groups.
- Contralateral EPE rates were 6.3%, 12%, and 34% in the respective risk groups.
- The algorithm showed acceptable discrimination (AUC 0.68), comparable to other models, with adequate calibration and superior net benefit on DCA.
Conclusions:
- The validated algorithm demonstrates commendable performance in predicting contralateral EPE.
- Findings support the algorithm's utility in guiding treatment decisions for unilateral high-risk PCa patients undergoing RP.
