Purpose: Current localized prostate cancer treatment outcome nomograms rely on prostate specific antigen (PSA), tumor stage and grade. We investigated whether the addition of prostate biopsy features may enhance the accuracy of a nomogram predicting recurrence after radical prostatectomy (RP).
Materials and methods: Clinical data from 1,152 patients who underwent RP were used and included PSA, clinical stage, biopsy Gleason grade and systematic biopsy information that quantified the amount of cancer and high grade cancer. Predictive accuracy for freedom from recurrence after RP was assessed with and without tumor quantification in the biopsy by the area under the receiver operating characteristics curve (AUC).
Results: Percentage and number of cores with cancer, and percentage and number of cores with high grade cancer were predictors of outcome when added to models that included PSA, Gleason grade and clinical stage (all p <0.0001). Nomogram accuracy with 3 traditional variables (AUC 0.790) was minimally enhanced with the addition of percentage or number of positive cores (AUC 0.804 and 0.800, respectively), or percentage or number of cores with high grade cancer (AUC 0.802 and 0.800, respectively). Maximum predictive accuracy of 0.811 was achieved after supplementing the traditional 3-variable nomogram with various combinations of additional pathological predictors.
Conclusions: The information provided by systematic biopsies substantially improves the ability to predict outcome following RP. However, some incremental predictive accuracy was achieved by adding systematic biopsy features.