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

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.