Identifying the Best Candidate for Radical Prostatectomy Among Patients with High-Risk Prostate Cancer

Abstract

BackgroundThe current role of radical prostatectomy (RP) in patients with high-risk disease remains controversial. ObjectiveTo identify which high-risk prostate cancer (PCa) patients might have favorable pathologic outcomes when surgically treated. Design, setting, and participantsWe evaluated 1366 patients with high-risk PCa (ie, at least one of the following risk factors: prostate-specific antigen [PSA] >20 ng/ml, cT3, biopsy Gleason 8–10) treated with RP and pelvic lymph node dissection (PLND) at eight European centers between 1987 and 2009. A favorable pathologic outcome was defined as specimen-confined (SC) disease—namely, pT2–pT3a, node negative PCa with negative surgical margins. InterventionAll patients underwent radical retropubic prostatectomy and PLND. MeasurementsUnivariable and multivariable logistic regression models tested the association between predictors and SC disease. A logistic regression coefficient-based nomogram was developed and internally validated using 200 bootstrap resamples. The Kaplan-Meier method was used to depict biochemical recurrence (BCR) and cancer-specific survival (CSS) rates. Results and limitationsOverall, 505 of 1366 patients (37%) had SC disease at RP. All preoperative variables (ie, age and PSA at surgery, clinical stage, and biopsy Gleason sum) were independent predictors of SC PCa at RP (all p ≤ 0.04). Patients with SC disease had significantly higher 10-yr BCR-free survival and CSS rates than patients without SC disease at RP (66% vs 47% and 98 vs 88%, respectively; all p<0.001). A nomogram including PSA, age, clinical stage, and biopsy Gleason sum demonstrated 72% accuracy in predicting SC PCa. This study is limited by its retrospective design and by the lack of an external validation of the nomogram. ConclusionsRoughly 40% of patients with high-risk PCa have SC disease at final pathology. These patients showed excellent long-term outcomes when surgically treated, thus representing the ideal candidates for RP as the primary treatment for PCa. Prediction of such patients is possible using a nomogram based on routinely available clinical parameters.