Predicting prostate biopsy outcome using a PCA3-based nomogram in a Polish cohort

Anticancer Res. 2013 Feb;33(2):553-7.


Background: Prostate Cancer Gene-3 (PCA3) is highly prostate cancer (PCa)-specific and its application holds promise in identifying men with PCa.

Aim: To determine whether the PCA3 score can be used relative to PCa clinical variables to predict biopsy outcome.

Patients and methods: PCA3 scores were assessed in a group of 80 patients using the Progensa assay (Gen-Probe, San Diego, CA, USA). The logistic regression algorithm was used to combine PCA3 results with the established biopsy risk factors including: age, prostate-specific antigen (PSA), digital rectal examination (DRE) and prostate volume (Pvol).

Results: In univariate analyses, the Progensa PCA3 score outperformed all biopsy risk predictors. A logistic regression algorithm using: age, PCA3, PSA, DRE and Pvol increased the area under the Receiver Operating Characteristic (ROC) curve from 0.72 for PCA3-alone to 0.85.

Conclusion: Combining PCA3 results with PCa risk factors provides significant improvements over the use of PCA3- or PSA-alone in predicting the probability of a positive prostate biopsy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Algorithms
  • Antigens, Neoplasm / urine*
  • Area Under Curve
  • Biomarkers, Tumor / analysis*
  • Biopsy
  • Cohort Studies
  • Humans
  • Male
  • Middle Aged
  • Nomograms*
  • Poland
  • Prostate-Specific Antigen / urine
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / urine
  • ROC Curve
  • Sensitivity and Specificity


  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • prostate cancer antigen 3, human
  • Prostate-Specific Antigen