New markers and multivariate models for prostate cancer detection

Anticancer Res. 2009 Jul;29(7):2589-600.

Abstract

Specificity of PSA has been enhanced by using molecular forms of PSA and free PSA (fPSA) such as percent free PSA (% fPSA), proPSA, intact PSA or BPHA and/or new serum markers. Most of these promising new serum markers like EPCA2 or ANXA3 still lack confirmation of outstanding initial results or show only marginal enhanced specificity at high sensitivity levels. PCA3, TMPRSS2-ERG, and other analytes in urine collected after digital rectal examination with application of mild digital pressure have potential to preferentially detect aggressive PCa and to decrease the rate of unnecessary repeat biopsies. The combination of these new urinary markers with new and established serum markers seems to be most promising to further increase specificity of tPSA. Multivariate models e.g. artificial neural networks (ANN) or logistic regression (LR)-based nomograms have been recently developed by incorporating these new markers in several studies. There is generally an advantage to including new markers and clinical data as additional parameters to PSA and % fPSA within ANN and LR models. The results and unexpected pitfalls of these studies are shown.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Antigens, Neoplasm / blood
  • Biomarkers, Tumor / blood*
  • Caveolins / blood
  • Growth Differentiation Factor 15 / blood
  • Humans
  • Kallikreins / blood
  • Male
  • Multivariate Analysis
  • Prostate-Specific Antigen / blood
  • Prostatic Neoplasms / blood
  • Prostatic Neoplasms / diagnosis*
  • Somatomedins / metabolism

Substances

  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • Caveolins
  • Growth Differentiation Factor 15
  • Somatomedins
  • early prostate cancer antigen, human
  • Kallikreins
  • Prostate-Specific Antigen