Defining the window of opportunity in screening for prostate cancer: Validation of a predictive tumor classification model

BACKGROUND. Subdividing cancers according to the natural course of disease, both at the time of diagnosis and after radical prostatectomy, may influence management decisions of patients with prostate cancer. We investigated whether categorization of prostate cancers into different prognostic subgroups is feasible. METHODS. In 218 screened participants of a randomized study, conventional post-operative tumor features were assessed for their accuracy in predicting PSA relapse after radical prostatectomy using Cox regression analysis. Independent prognostic tumor features were combined to identify subsets of cancers with similar biological potential. A cancer was defined that may be curable after its detection by screening tests, though is destined to progress to clinically manifest disease and cancer-related mortality in the absence of screening. RESULTS. After a median follow-up of 33.0 months, pathological stage (P = 0.03), tumor volume (P = 0.04), and margin status (P = 0.01) each independently predicted PSA relapse after surgery. The proportion of poorly differentiated cancer proved highly superior to the Gleason score and most strongly predicted PSA relapse (P <0.0001). Based on combined independent prognostic tumor features, a tumor classification model powerfully predicted PSA relapse. CONCLUSIONS. Based on tumor characteristics, possibly harmless, and conversely, possibly non-curable disease, may be distinguished from cancers that are likely to show clinical progression in the absence of screening and treatment. Prediction of these subclasses prior to treatment may eventually lead to proper patient management.