Impact of Grade Groups on Prostate Cancer-Specific and Other-Cause Mortality: Competing Risk Analysis from a Large Single Institution Series.

Abstract

Simple SummaryFor prostate cancer patient, information on risk of long-term cancer-specific and other-cause mortality is essential to avoid over- and undertreatment. Patient stratification to low-, intermediate-, and high-risk groups has been used for decades. However, recent evidence has shown that such stratification is not optimal and outcomes differ widely, especially in high-risk prostate cancer patients. Gleason score grading is an important factor for the prediction of cancer-specific survival and has been included in all prostate cancer risk stratification models. Moreover, this parameter could be used as an independent predictor. Recently proposed grade group model demonstrated good predictive probability on short-term outcomes. However, there is a lack of data regarding long-term cancer-specific survival. In the presented study, we analyzed long-term oncological outcomes in different grade groups. Detected ratio between cancer-specific and other-cause mortality could be very informative and helpful in prostate cancer patient risk stratification and more precise clinical decision making.Objective: To assess the risk of cancer-specific mortality (CSM) and other-cause mortality (OCM) using post-operative International Society of Urological Pathology Grade Group (GG) model in patients after radical prostatectomy (RP). Patients and Methods: Overall 1921 consecutive men who underwent RP during 2001 to 2017 in a single tertiary center were included in the study. Multivariate competing risk regression analysis was used to identify significant predictors and quantify cumulative incidence of CSM and OCM. Time-depending area under the curve (AUC) depicted the performance of GG model on prediction of CSM. Results: Over a median follow-up of 7.9-year (IQR 4.4-11.7) after RP, 235 (12.2%) deaths were registered, and 52 (2.7%) of them were related to PCa. GG model showed high and stable performance (time-dependent AUC 0.88) on prediction of CSM. Cumulative 10-year CSM in GGs 1 to 5 was 0.9%, 2.3%, 7.6%, 14.7%, and 48.6%, respectively; 10-year OCM in GGs was 15.5%, 16.1%, 12.6%, 17.7% and 6.5%, respectively. The ratio between 10-year CSM/OCM in GGs 1 to 5 was 1:17, 1:7, 1:2, 1:1, and 7:1, respectively. Conclusions: Cancer-specific and other-cause mortality differed widely between GGs. Presented findings could aid in personalized clinical decision making for active treatment.