An Innovative Tool for Predicting the Pathologic Stage of Prostate Cancer

Objective: To develop a practical tool for predicting the pathologic stage in prostate cancer. Materials and Methods: Two hundred fifty patients who had had radical prostatectomy were selected from an Italian longitudinal observational study on prostate cancer. Inclusion criteria for selection were the following: a preoperative prostate specific antigen (PSA) value <50 ng/ml; a clinical stage less than or equal to stage T3c (TNM 1992); the availability of the bioptic Gleason score; and the availability of a pathologic specimen obtained during the radical prostatectomy. Pathologic stages were categorized into five levels according to the increasing severity of the illness. Multivariate logistic regression on polythomous ordinal response was performed to obtain a predictive model of disease progression. A set of parallel scale nomographs then was constructed to transfer the predictive model into a new tool, called the “Uro-gramma,” that is able to simplify the practical use of the traditional nomograms. Results: The Gleason score was the factor that influenced the probability of pathologic stage progression the most; PSA and clinical stage were the second and third most significant factors, respectively. Two-way and three-way interactions were tested and were not found to be significant. The confounding effects of age and neoadjuvant hormonal therapy also were tested, and they had no significant influence on the response variable. A logistic regression algorithm then was used to produce a set of nomographs (the Uro-gramma) for the prediction of different pathologic stages using the Gleason score, PSA level, and clinical stage of disease. Conclusion: The predictive model obtained from this Italian study will help physicians and patients in therapeutic decision making. The Uro-gramma provides a new and easier instrument with respect to previous nomograms and multidimensional tables for pathologic stage prediction.