Impact of different variables on the outcome of patients with clinically confined prostate carcinoma - Prediction of pathologic stage and biochemicalfailure using an artificial neural network

BACKGROUND. The advent of advanced computing techniques has provided the op portunity to analyze clinical data using artificial intelligence techniques . This study was designed to determine whether a neural network could be de veloped using preoperative prognostic indicators to predict the pathologic stage and time of biochemical failure for patients who undergo radical pros tatectomy. METHODS. The preoperative information included TNM stage, prostate size, pr ostate specific antigen (PSA) level, biopsy results (Gleason score and perc entage of positive biopsy), as well as patient age. All 309 patients underw ent radical prostatectomy at the University of Colorado Health Sciences Cen ter. The data from all patients were used to train a multilayer perceptron artificial neural network. The failure rate was defined as a rise in the PS A level > 0.2 ng/mL. The biochemical failure rate in the data base used was 14.2%. Univariate and multivariate analyses were performed to validate the results. RESULTS. The neural network statistics for the validation set showed a sens itivity and specificity of 79% and 81%, respectively, for the prediction of pathologic stage with an overall accuracy of 80% compared with an overall accuracy of 67% using the multivariate regression analysis. The sensitivity and specificity for the prediction of failure were 67% and 85%, respective ly, demonstrating a high confidence in predicting failure. The overall accu racy rates for the artificial neural network and the multivariate analysis were similar. CONCLUSIONS, Neural networks can offer a convenient vehicle for clinicians to assess the preoperative risk of disease progression for patients whoa re about to undergo radical prostatectomy. Continued investigation of this ap proach with larger data sets seems warranted. Cancer 2001;91:1653-60. (C) 2 001 American Cancer Society.