Age-Adjusted PSA Levels in Prostate Cancer Prediction: Updated Results of the Tyrol Prostate Cancer Early Detection Program.

To reduce the number of unnecessary biopsies in patients with benign prostatic disease, however, without missing significant PCa the present study re-evaluates the age-dependent PSA cut-offs in the Tyrol Prostate Cancer (PCa) early detection program.

The study population included 2225 patients who underwent prostate biopsy due to elevated PSA levels at our department. We divided our patient collective into four age groups: ≤49 years (n = 178), 50-59 years (n = 597), 60-69 years (n = 962) and ≥70 years (n = 488). We simulated different scenarios for PSA cut-off values between 1. 25 and 6 ng/mL and fPSA% between 15 and 21% for all four age groups and calculated sensitivity, specificity, confidence intervals and predictive values.

PCa was detected in 1218 men (54. 7%). We found that in combination with free PSA ≤21% the following PSA cut-offs had the best cancer specificity: 1. 75 ng/ml for men ≤49 years and 50-59 years, 2. 25 ng/ml for men aged 60-69 years and 3. 25 ng/ml for men ≥70 years. Using these adjusted PSA cut-off values all significant tumors are recognized in all age groups, yet the number of biopsies is reduced. Overall, one biopsy is avoided in 13 to 14 men (number needed to screen = 13. 3, reduction of biopsies = 7. 5%) when decision regarding biopsy is done according to the "new" cut-off values instead of the "old" ones. For the different age groups the number needed to screen to avoid one biopsy varied between 9. 2 (≤49 years) and 17. 4 (50-59 years).

With "new", fine-tuned PSA cut-offs we detect all relevant PCa with a significant reduction of biopsies compared to the "old" cut-off values. Optimization of age-specific PSA cut-offs is one step towards a smarter strategy in the Tyrol PCa Early Detection Program.

PloS one. 2015 Jul 28*** epublish ***

Isabel Heidegger, Josef Fritz, Helmut Klocker, Renate Pichler, Jasmin Bektic, Wolfgang Horninger

Department of Urology, Medical University Innsbruck, Innsbruck, Austria; Department of Urology, Division of Experimental Urology, Medical University Innsbruck, Innsbruck, Austria. , Department of Medical Statistics, Informatics and Health Economics, Medical University Innsbruck, Innsbruck, Austria. , Department of Urology, Division of Experimental Urology, Medical University Innsbruck, Innsbruck, Austria. , Department of Urology, Medical University Innsbruck, Innsbruck, Austria. , Department of Urology, Medical University Innsbruck, Innsbruck, Austria. , Department of Urology, Medical University Innsbruck, Innsbruck, Austria.

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