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

T. J. Polascik, J. D. Pearson, Alan Wayne Partin

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)301-306
Number of pages6
JournalProstate Cancer and Prostatic Diseases
Volume1
Issue number6
StatePublished - 1998

Fingerprint

Prostatic Neoplasms
Neoplasm Grading
Multivariate Analysis
Biopsy
Seminal Vesicles
Serum
Lymph Nodes
Research Personnel
Therapeutics

Keywords

  • Multivariate analysis
  • Nomogram
  • Prostate cancer
  • PSA
  • Staging

ASJC Scopus subject areas

  • Oncology
  • Urology

Cite this

Use of multivariate models to improve prediction of pathologic stage for men with clinically localized prostate cancer. / Polascik, T. J.; Pearson, J. D.; Partin, Alan Wayne.

In: Prostate Cancer and Prostatic Diseases, Vol. 1, No. 6, 1998, p. 301-306.

Research output: Contribution to journalArticle

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