Identifying the best candidate for radical prostatectomy among patients with high-risk prostate cancer.

The current role of radical prostatectomy (RP) in patients with high-risk disease remains controversial. OBJECTIVE: To identify which high-risk prostate cancer (PCa) patients might have favorable pathologic outcomes when surgically treated. DESIGN, SETTING, AND PARTICIPANTS: We 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. INTERVENTION: All patients underwent radical retropubic prostatectomy and PLND. MEASUREMENTS: Univariable 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 LIMITATIONS: Overall, 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. CONCLUSIONS: Roughly 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.