Use of multivariate models to improve prediction of pathologic stage for men with clinically localized prostate cancer

To benefit from definitive local therapy, men with clinically localized pro state cancer should have organ-confined disease. We discuss the use of mult ivariate analysis using serum PSA, biopsy Gleason score and clinical stage to improve the prediction of pathologic stage. Serum PSA, biopsy Gleason scores and clinical stage correlate with patholog ic stage by univariate analysis are used in this study. However, each of th ese variables cannot accurately predict stage for the individual patient Se veral investigators have proposed clinical algorithms based on multivariate analysis to enhance pretreatment staging. For men with clinically localized prostate cancer, multivariate algorithms are useful to determine the probability of a man having organ-confined dise ase, seminal vesicle invasion and lymph node involvement. This information will better enable clinicians and patients to make informed decisions about appropriate treatment options.