The Added Value of Percentage of Free to Total Prostate-specific Antigen, PCA3, and a Kallikrein Panel to the ERSPC Risk Calculator for Prostate Cancer in Prescreened Men

Background: Prostate-specific antigen (PSA) testing has limited accuracy for the early detection of prostate cancer (PCa). Objective: To assess the value added by percentage of free to total PSA (%fPSA), prostate cancer antigen 3 (PCA3), and a kallikrein panel (4k-panel) to the European Randomised Study of Screening for Prostate Cancer (ERSPC) multivariable prediction models: risk calculator (RC) 4, including transrectal ultrasound, and RC 4 plus digital rectal examination (4+DRE) for prescreened men. Design, setting, and participants: Participants were invited for rescreening between October 2007 and February 2009 within the Dutch part of the ERSPC study. Biopsies were taken in men with a PSA level ≥3.0 ng/ml or a PCA3 score ≥10. Additional analyses of the 4k-panel were done on serum samples. Outcome measurements and statistical analysis: Outcome was defined as PCa detectable by sextant biopsy. Receiver operating characteristic curve and decision curve analyses were performed to compare the predictive capabilities of %fPSA, PCA3, 4k-panel, the ERSPC RCs, and their combinations in logistic regression models. Results and limitations: PCa was detected in 119 of 708 men. The %fPSA did not perform better univariately or added to the RCs compared with the RCs alone. In 202 men with an elevated PSA, the 4k-panel discriminated better than PCA3 when modelled univariately (area under the curve [AUC]: 0.78 vs 0.62; p = 0.01). The multivariable models with PCA3 or the 4k-panel were equivalent (AUC: 0.80 for RC 4+DRE). In the total population, PCA3 discriminated better than the 4k-panel (univariate AUC: 0.63 vs 0.56; p = 0.05). There was no statistically significant difference between the multivariable model with PCA3 (AUC: 0.73) versus the model with the 4k-panel (AUC: 0.71; p = 0.18). The multivariable model with PCA3 performed better than the reference model (0.73 vs 0.70; p = 0.02). Decision curves confirmed these patterns, although numbers were small. Conclusions: Both PCA3 and, to a lesser extent, a 4k-panel have added value to the DRE-based ERSPC RC in detecting PCa in prescreened men. Patient summary: We studied the added value of novel biomarkers to previously developed risk prediction models for prostate cancer. We found that inclusion of these biomarkers resulted in an increase in predictive ability.

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