PREDICT: model for prediction of survival in localized prostate cancer

Abstract

Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I-125 brachytherapy (n = 1694), external beam radiotherapy (≥74 Gy, n = 336) or radical prostatectomy (n = 1353). Pre-treatment parameters (clinical T-stage, biopsy grade, PSA and age) were related to the hazard of mortality by multivariate Cox proportional hazard analysis. The PRetreatment Estimation of the risk of Death In Cancer of the prosTate (PREDICT) model was developed. The predictive accuracy of the model was assessed by calibration and discrimination and compared to the Ash risk classification system. Results: Of the 3383 patients analyzed, 2755 patients (81 %) were alive at the end of follow-up, 149 patients (4 %) died of prostate cancer and 365 patients (11 %) died of other causes, and for 114 patients (3 %) cause of death was unknown. Median follow-up time was 7.6 years. After correction for overoptimism, the c-statistic of the prediction model for prostate cancer-specific mortality was 0.78 (95 % CI 0.74–0.82), compared to 0.78 (95 % CI 0.75–0.81) for the risk classification system by Ash et al. The PREDICT model showed better calibration than the Ash risk classification system. Conclusions: The PREDICT model showed a good predictive accuracy and reliability. The PREDICT model might be a promising tool for physicians to predict disease-specific survival prior to any generally accepted intervention in patients with localized prostate cancer.