Predicting prostate biopsy outcome using a PCA3-based nomogram in a Polish cohort
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Updated: May 14, 2026
Enhancing Prostate Tumor Biobanking Reliability with Improved Sampling Technique and Histological Characterization
Published on: November 17, 2023
Maciej Salagierski1, Peter Mulders, Jack A Schalken
1267 Experimental Urology, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, the Netherlands. J.Schalken@uro.umcn.nl
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.
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