993 PROSTATE TUMOR VOLUME IS INDEPENDENTLY ASSOCIATED WITH CANCER-SPECIFIC MORTALITY FOLLOWING RADICAL PROSTATECTOMY AND ENHANCES PATIENT RISK STRATIFICATION

Abstract

You have accessJournal of UrologyProstate Cancer: Localized (IV)1 Apr 2013993 PROSTATE TUMOR VOLUME IS INDEPENDENTLY ASSOCIATED WITH CANCER-SPECIFIC MORTALITY FOLLOWING RADICAL PROSTATECTOMY AND ENHANCES PATIENT RISK STRATIFICATION John Knoedler, Robert Karnes, Laureano Rangel, Eric Bergstralh, and Stephen Boorjian John KnoedlerJohn Knoedler Rochester, MN More articles by this author , Robert KarnesRobert Karnes Rochester, MN More articles by this author , Laureano RangelLaureano Rangel Rochester, MN More articles by this author , Eric BergstralhEric Bergstralh Rochester, MN More articles by this author , and Stephen BoorjianStephen Boorjian Rochester, MN More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.577AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Data regarding the independent prognostic significance of tumor volume (TV) are conflicting, and have focused on the outcome measure of biochemical recurrence. Moreover, whether TV improves estimation of prognosis beyond established predictive variables has not been established. Herein, we evaluated the association of TV with prostate cancer mortality following radical prostatectomy (RP), and assessed the additive prognostic value of TV to an established predictive model. METHODS We identified 13,687 patients who underwent RP without preoperative therapy at Mayo Clinic between 1987-2009. TV was estimated using the prolate ellipsoid formula. Cancer-specific survival (CSS) was estimated using the Kaplan Meier method and compared with the log-rank test. Cox proportional hazard regression models were used to evaluate the association of TV with mortality. The ability of TV to enhance the performance of the GPSM prognostic model [Blute et al, J Urol 2001] was assessed using the c-index. RESULTS Median TV was 1.57 cc (interquartile range (IQR) 0.48, 4.19). Increasing TV was associated with older patient age at surgery (p<0.0001), higher preoperative PSA (p<0.0001), smaller prostate volume (p=0.03), as well as higher pathologic Gleason score (p<0.0001), advanced pathologic tumor stage (p<0.0001), and an increased rate of positive surgical margins (p<0.0001). Median postoperative follow-up was 9.4 years (IQR 5.0, 14.5), during which time 3818 patients experienced BCR and 3138 died, including 430 who died of prostate cancer. Patient grouping into quartiles according to TV resulted in significant stratification of outcome, with a 15-year CSS by TV quartile of 99%, 98%, 95%, and 88%, respectively (p<0.001). On multivariate analysis (Table), TV remained associated with a significantly increased risk of death from prostate cancer (HR 1.29; p<0.0001). Addition of TV to the GPSM score increased the model's performance for prediction of prostate cancer mortality from 0.802 to 0.822. CONCLUSIONS TV is independently associated with survival following RP, and increases the performance of an established prediction model. As such, TV should be routinely included in RP pathology reports, and warrants testing in risk stratification tools. Multivariate analysis of factors associated with death from prostate cancer following radical prostatectomy. Variable HR 95% CI p Value Year of surgery 0.95 0.93-0.98 < 0.0001 Age at surgery 1.01 0.99-1.02 0.40 Preoperative PSA 0.95 0.87-1.04 0.26 Pathologic Gleason score 2.69 2.32-3.12 < 0.0001 Pathologic tumor stage 1.51 1.34-1.71 < 0.0001 pN+ 1.74 1.24-2.46 0.002 Positive surgical margin 1.26 1.02-1.58 0.04 Tumor volume 1.29 1.20-1.39 < 0.0001 Receipt of adjuvant RT 0.50 0.33-0.74 0.0006 Receipt of adjuvant ADT 0.61 0.44-0.84 0.002 © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e407 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information John Knoedler Rochester, MN More articles by this author Robert Karnes Rochester, MN More articles by this author Laureano Rangel Rochester, MN More articles by this author Eric Bergstralh Rochester, MN More articles by this author Stephen Boorjian Rochester, MN More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...