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

T J Polascik; J D Pearson; A W Partin; Dr TJ Polascik

doi:10.1038/sj.pcan.4500258

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

Prostate Cancer Prostatic Dis. 1998 Dec;1(6):301-306. doi: 10.1038/sj.pcan.4500258.

Authors

T J Polascik¹, J D Pearson, A W Partin, Dr TJ Polascik

Affiliation

¹ James Buchanan Brady Urological Institute, The Johns Hopkins Medical Institutions, 600 North Wolfe Street, Baltimore, MD 21287.

PMID: 12496871
DOI: 10.1038/sj.pcan.4500258

Abstract

To benefit from definitive local therapy, men with clinically localized prostate cancer should have organ-confined disease. We discuss the use of multivariate 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 pathologic stage by univariate analysis are used in this study. However, each of these variables cannot accurately predict stage for the individual patient. Several 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 disease, seminal vesicle invasion and lymph node involvement. This information will better enable clinicians and patients to make informed decisions about appropriate treatment options.