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A biopsy-integrated algorithm for determining Gleason 6 upgrading risk stratifies risk of active surveillance failure
M L Blute1,2, J M Shiau1, M Truong1,3
1Department of Urology, University of Wisconsin School of Medicine and Public Health, 1685 Highland Ave, Madison, WI, 53705, USA.
Introduction:
A significant proportion of patients that fail active surveillance (AS) for prostate cancer management do so because of cancer upgrading. A previously validated upgrading nomogram generates a score that predicts risk of biopsy Gleason 6 upgrading following radical prostatectomy in lower-risk populations that are candidates for Active Surveillance (Cancer, 2013).
Objectives:
We hypothesize that the upgrading risk (UR) score generated by this nomogram at diagnosis improves the ability to predict patients that will subsequently fail AS.
Methods:
To evaluate the nomogram, retrospective data from several institutional cohorts of patients who met AS criteria, group 1 (n = 75) and group 2 (n = 1230), were independently examined. A UR score was generated using the coefficients from the nomogram consisting of PSA density (PSAD), BMI, maximum % core involvement (MCI), and number of positive cores. AS failure was defined as Gleason score (GS) >6, >50 % maximum core involvement, or >2 positive cores on biopsy. Univariate and multivariate Cox proportional-hazards regression models, upgrading risk score, and other clinicopathologic features were each assessed for their ability to predict AS failure.
Results:
Clinicopathologic parameters were similar in both groups with the exception of mean PSAD (0.13 vs. 0.11, p < 0.01) and follow-up (2.1 vs. 3.2 years, p = 0.2). Most common cause of AS failure was GS > 6 (group 1) compared to >2 positive cores (group 2). On univariate analysis in both populations, features at diagnosis including PSAD and the UR score were significant in predicting AS failure by upgrading (Gleason > 6) and any failure. Multivariate analysis revealed the UR score predicts AS failure by GS upgrading (HR 1.8, 95 % CI 1.12-2.93; p = 0.01) and any failure criteria (HR 1.7, 95 % CI 1.06-2.65); p = 0.02) for group 1. Likewise, the UR score in group 2 predicts AS failure with GS upgrading (HR 1.3, 95 % CI 1.15-1.42; p < 0.0001) and any failure criteria (HR 1.18, 95 % CI 1.18-1.38; p < 0.0001). An ROC generated an AUC of 0.66. Decision curve analysis demonstrated a high net benefit for the UR score across a range of threshold probabilities. Based on these outcomes, at 3 years, patients in the lowest risk quartile have a 15 % risk of AS failure versus a 46 % risk in the highest quartile (p < 0.0001).
Conclusions:
The UR score was predictive of pathologic AS failure on multivariate analysis in several AS cohorts. It outperformed single clinicopathologic criteria and may provide a useful adjunct using clinicopathologic data to stratify patients considering AS.
