[New biomarkers and application of multivariate models for detection of prostate cancer]

The 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 the outstanding initial results or show only marginally 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 the potential to preferentially detect aggressive PCa and to decrease the number 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 recently been performed by incorporating these new markers in several studies. There is generally an advantage to include the new markers and clinical data as additional parameters to PSA and %fPSA within ANN and LR models. Results of these studies and also unexpected pitfalls are discussed in this review.