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SIU-WJU Article of the Month – November 2016
Improving Counselling for Patients Considering Active Surveillance: Can We Determine Who Will Fail?
SIU Academy®. Williams M. 11/01/16; 164418 Topic: Active surveillance
Michael Williams
Michael Williams
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Abstract
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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.


Keywords

Active surveillance, Prostate cancer, Nomogram, Survival

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.


Keywords

Active surveillance, Prostate cancer, Nomogram, Survival

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