Predicting pathologic outcomes in patients undergoing robot-assisted radical prostatectomy for high risk prostate cancer: A preoperative nomogram - Abstract

OBJECTIVE: To identify which high-risk PCa patients may harbor favorable pathologic outcomes at surgery.

MATERIALS AND METHODS: We evaluated 810 patients with high-risk PCa, defined as having ≥1 of the following: PSA >20 ng/ml, Gleason score ≥8, clinical stage ≥T2c. Patients underwent RARP with pelvic lymph node dissection, between 2003 and 2012, in one center. Only 1.6% (13/810) of patients received any adjuvant treatment. Favorable pathologic outcome was defined as specimen-confined (SC) disease (pT2-T3a, node negative, and negative surgical margins) at RARP-specimen. Logistic regression models were used to test the relationship among all available predicators and harboring SC PCa. A logistic regression coefficient-based nomogram was constructed and internally validated using 200 bootstrap resamples. Kaplan-Meier method estimated biochemical recurrence (BCR) -free and cancer-specific mortality (CSM) free survival rates, after stratification according to pathological disease status.

RESULTS: Overall, 55.2% patients harbored SC disease at RARP. At multivariable analysis, PSA level, clinical stage, primary/secondary Gleason scores, and maximum percent tumor quartiles were all independent predictors of SC PCa (all P< 0.04). A nomogram based on these variables showed 76% discrimination accuracy in predicting SC disease, and very favorable calibration characteristics. Patients with SC disease had significantly higher 8-yr BCR- (72.7% vs 31.7%, P< 0.001) and CSM-free survival rates (100% vs 86.9%, P< 0.001) compared to non-SC disease patients.

CONCLUSIONS: We developed a novel nomogram predicting SC disease at RARP. Patients with SC disease achieved favorable long-term BCR- and CSM-free survival rates following RARP. The nomogram may be used to support clinical decision-making, and aid in selection of high-risk patients most likely to benefit from RARP.

Written by:
Abdollah F, Klett DE, Sood A, Sammon JD, Pucheril D, Dalela D, Diaz M, Peabody JO, Trinh QD, Menon M.   Are you the author?
Vattikuti Urology Institute, Center for Outcomes Research Analytics and Evaluation, Henry Ford Health System, Detroit, MI, USA.

Reference: BJU Int. 2014 Nov 21. Epub ahead of print.
doi: 10.1111/bju.12998


PubMed Abstract
PMID: 25413443

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