You have accessJournal of UrologyProstate Cancer: Epidemiology and Natural History I1 Apr 2012161 PREDICTING ALL-CAUSE AND PROSTATE CANCER SPECIFIC MORTALITY FOLLOWING DEFINITIVE THERAPY FOR LOCALIZED PROSTATE CANCER Brandon Isariyawongse, Andrew Stephenson, Michael Kattan, Tianming Gao, Jennifer Haslag-Minoff, Kenneth Nepple, Jay Piccirillo, Jay Ciezki, Eric Klein, and Adam Kibel Brandon IsariyawongseBrandon Isariyawongse Cleveland, OH More articles by this author , Andrew StephensonAndrew Stephenson Cleveland, OH More articles by this author , Michael KattanMichael Kattan Cleveland, OH More articles by this author , Tianming GaoTianming Gao Cleveland, OH More articles by this author , Jennifer Haslag-MinoffJennifer Haslag-Minoff St. Louis, MO More articles by this author , Kenneth NeppleKenneth Nepple St. Louis, MO More articles by this author , Jay PiccirilloJay Piccirillo St. Louis, MO More articles by this author , Jay CiezkiJay Ciezki Cleveland, OH More articles by this author , Eric KleinEric Klein Cleveland, OH More articles by this author , and Adam KibelAdam Kibel Boston, MA More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.212AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate cancer (CaP) has a protracted natural history relative to other solid malignancies, and the risk of competing causes of mortality is important to weigh at the time of treatment decision-making. We endeavored to develop nomograms predicting all-cause mortality (ACM) and prostate cancer specific mortality (PCSM) following definitive therapy for localized CaP. METHODS A total of 10,429 patients who had undergone radical prostatectomy (RP, n=6,485), external beam radiotherapy (EBRT, n=2,264), or interstitial brachytherapy (PI, n=1,680) for localized CaP at Cleveland Clinic or Barnes-Jewish Hospital between 1995 and 2005 were included in the analysis. Prognostic variables included age, PSA, biopsy Gleason grade (≤6, 7, or ≥8), clinical T stage, treatment modality, and comorbidity status (none, mild, moderate, or severe). ACM was modeled using Cox regression analysis; PCSM was modeled using Fine and Gray competing risk analysis. We performed internal validation using bootstrapping and cross-validation. The calibration was assessed graphically. RESULTS The median follow-up was 5.5 years, and 1,532 (14.7%) of survivors had follow-up greater than 10 years. Overall, 1,256 deaths (12.0%) were observed, 182 (1.7%) of which were attributed to prostate cancer. Age, treatment modality, PSA, biopsy Gleason grade, and comorbidity status were significantly predictive of ACM. In regards to PCSM, age, PSA, biopsy Gleason grade, and clinical T stage were significantly predictive of outcome. Nomograms were constructed for these outcomes with good concordance (c=0.74 and 0.81, respectively). CONCLUSIONS The pre-treatment risk of ACM and PCSM can be predicted with reasonable accuracy. This information is essential when counseling patients - particularly the elderly and those with significant comorbid illnesses - prior to proceeding with definitive therapy for localized CaP. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e67 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Brandon Isariyawongse Cleveland, OH More articles by this author Andrew Stephenson Cleveland, OH More articles by this author Michael Kattan Cleveland, OH More articles by this author Tianming Gao Cleveland, OH More articles by this author Jennifer Haslag-Minoff St. Louis, MO More articles by this author Kenneth Nepple St. Louis, MO More articles by this author Jay Piccirillo St. Louis, MO More articles by this author Jay Ciezki Cleveland, OH More articles by this author Eric Klein Cleveland, OH More articles by this author Adam Kibel Boston, MA More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...