Predicting tumor failure in prostate carcinoma after definitive radiation therapy: Limitations of models based on prostate-specific antigen, clinicalstage, and Gleason score

In this report, we use new patient data to test three popular models develo ped to predict the outcome of definitive radiation therapy, The data come f rom 240 men with localized prostate cancer and who were treated with defini tive radiation therapy at a community hospital. All three models tested wer e based on the three commonly available variables of pretreatment prostate- specific antigen (PSA), Gleason score, and tumor stage, and we used the Cox proportional hazards model and the logistic regression model to relate the se variables to outcome. We discovered that in our data, the optimal way to use pretreatment PSA was as natural log(PSA), the optimal way to use T sta ge was in three categories: T-1 and T-2, T-3, and T-4, and that the optimal use of Gleason score was as <7 versus greater than or equal to 7. Neverthe less, models confined to the optimal use of these three variables leave muc h uncertainty about important outcomes, such as the probability of relapse within 5 years.