To develop an easy-to-use side-specific tool for the prediction of prostate cancer extracapsular extension (ECE) using clinical, biopsy, and MRI parameters.
Retrospective analysis of patients who underwent radical prostatectomy preceded by staging multiparametric MRI of the prostate was performed. Multivariate logistic regression analysis was used to choose independent predictors of ECE. Continuous variables were transformed to categorical ones by choosing threshold values using spline knots or testing thresholds used in previously described models. Internal validation of the rule was carried out as well as validation of other algorithms on our group was performed.
In the analyzed period of time, 88 out of 164 patients who underwent radical prostatectomy met inclusion criteria. ECE was evidenced at radical prostatectomy in 41 patients (46.6%) and in 53 lobes (30.1%). In the multivariate analysis PSA, total percentage of cancerous tissue in cores (%PCa) and maximum tumour diameter (MTD) of Likert 3-5 lesions on MRI were independent predictors of ECE. The following rule for predicting side-specific ECE was proposed: %PCa ≥ 15% OR MTD ≥ 15 mm OR PSA ≥ 20 ng/mL. Internal validation of the algorithm revealed safe lower confidence limits for sensitivity and NPV, proving that model offers accurate risk grouping that can be safely used in decision-making.
The rule developed in this study makes ECE prediction fast, intuitive, and side-specific. However, until validated externally it should be used with caution.
International urology and nephrology. 2019 Jun 10 [Epub ahead of print]
Piotr Zapała, Bartosz Dybowski, Ewa Bres-Niewada, Tomasz Lorenc, Agnieszka Powała, Zbigniew Lewandowski, Marek Gołębiowski, Piotr Radziszewski
Department of Urology, Medical University of Warsaw, Lindleya 4, 02-005, Warsaw, Poland., Department of Urology, Medical University of Warsaw, Lindleya 4, 02-005, Warsaw, Poland. ., 1st Department of Clinical Radiology, Medical University of Warsaw, Warsaw, Poland., Department of Pathology, Medical University of Warsaw, Warsaw, Poland., Department of Epidemiology and Biostatistics, Medical University of Warsaw, Warsaw, Poland.