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Background: A recent recalibration of the ONCOTYROL Prostate Cancer Outcome and Policy (PCOP) Model, assuming that latent prostate cancer (PCa) detectable at autopsy might be detectable by screening as well, resulted in considerable worsening of the benefit-harm balance of screening. In this study, we used the recalibrated model to assess the effects of familial risk, quality of life (QoL) preferences, age, and active surveillance.Methods: Men with average and elevated familial PCa risk were simulated in separate models, differing in familial risk parameters. Familial risk was assumed to affect PCa onset and progression simultaneously in the base-case, and separately in scenario analyses. Evaluated screening strategies included one-time screening at different ages, and screening at different intervals and age ranges. Optimal screening strategies were identified depending on age and individual QoL preferences. Strategies were additionally evaluated with active surveillance by biennial re-biopsy delaying treatment of localized cancer until grade progression to Gleason score ≥ 7.Results: Screening men with average PCa risk reduced quality-adjusted life expectancy (QALE) even under favorable assumptions. Men with elevated familial risk, depending on age and disutilities, gained QALE. While for men with familial risk aged 55 and 60 years annual screening to age 69 was the optimal strategy over most disutility ranges, no screening was the preferred option for 65 year-old men with average and above disutilities. Active surveillance greatly reduced overtreatment, but QALE gains by averted adverse events were opposed by losses due to delayed treatment and additional biopsies. The effect of active surveillance on the benefit-harm balance of screening differed between populations, as net losses and gains in QALE predicted for screening without active surveillance in men with average and familial PCa risk, respectively, were both reduced.Conclusions: Assumptions about PCa risk and screen-detectable prevalence significantly affect the benefit-harm balance of screening. Based on the assumptions of our model, PCa screening should focus on candidates with familial predisposition with consideration of individual QoL preferences and age. Active surveillance may require treatment initiation before Gleason score progression to 7. Alternative active surveillance strategies should be evaluated in further modeling studies. [ABSTRACT FROM AUTHOR]

Objective: 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. Patients and Methods: 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. Results: 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). Conclusion: 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. [ABSTRACT FROM AUTHOR]

Background: Active surveillance (AS) is increasingly offered to patients with low risk prostate cancer. The present study was conducted to evaluate the risk of tumor under-grading and -staging for AS eligibility. Moreover, we analyzed possible biomarkers for predicting more unfavorable final tumor histology. Methods: 197 patients who underwent radical prostatectomy (RPE) but would have met the EAU (European Association of Urology) criteria for AS (PSA<10 ng/ml, biopsy GS ≤6, ≤2 cancer-positive biopsy cores with ≤50% of tumor in any core and clinical stage ≤T2a) were included in the study. These AS inclusion parameters were correlated to the final histology of the RPE specimens. The impact of preoperative PSA level (low PSA ≤4 ng/ml vs. intermediate PSA of >4–10 ng/ml), PSA density (<15 vs. ≥ 15 ng/ml) and the number of positive biopsy cores (1 vs. 2 positive cores) on predicting upgrading and final adverse histology of the RPE specimens was analyzed in uni- and multivariate analyses. Moreover, clinical courses of undergraded patients were assessed. Results: In our patient cohort 41.1% were found under-graded in the biopsy (final histology 40.1% GS7, 1% GS8). Preoperative PSA levels, PSA density or the number of positive cores were not predictive for worse final pathological findings including GS >6, extraprostatic extension and positive resection margin (R1) or correlated significantly with up-grading and/or extraprostatic extension in a multivariate model. Only R1 resections were predictable by combining intermediate PSA levels with two positive biopsy cores (p = 0.004). Sub-analyses showed that the number of biopsy cores (10 vs. 15 biopsy cores) had no influence on above mentioned results on predicting biopsy undergrading. Clinical courses of patients showed that 19.9% of patients had a biochemical relapse after RPE, among all of them were undergraded in the initial biopsy. Conclusion: In summary, this study shows that a multitude of patients fulfilling the criteria for AS are under-diagnosed. The use of preoperative PSA levels, PSA density and the number of positive cores were not predictable for undergrading in the present patient collective. [ABSTRACT FROM AUTHOR]

Objectives: To assess the applicability of the Prostate Cancer Prevention Trial High Grade (Gleason grade ≥ 7) Risk Calculator (PCPTHG) in ten international cohorts, representing a range of populations. Methods: A total of 25,512 biopsies from 10 cohorts (6 European, 1 UK and 3 US) were included; 4 implemented 6-core biopsies, and the remaining had 10 or higher schemes; 8 were screening cohorts, and 2 were clinical. PCPTHG risks were calculated using prostate-specific antigen, digital rectal examination, age, African origin and history of prior biopsy and evaluated in terms of calibration plots, areas underneath the receiver operating characteristic curve (AUC) and net benefit curves. Results: The median AUC of the PCPTHG for high-grade disease detection in the 10- and higher-core cohorts was 73.5 % (range, 63.9-76.7 %) compared with a median of 78.1 % (range, 72.0-87.6 %) among the four 6-core cohorts. Only the 10-core Cleveland Clinic cohort showed clear evidence of under-prediction by the PCPTHG, and this was restricted to risk ranges less than 15 %. The PCPTHG demonstrated higher clinical net benefit in higher-core compared with 6-core biopsy cohorts, and among the former, there were no notable differences observed between clinical and screening cohorts, nor between European and US cohorts. Conclusions: The PCPTHG requires minimal patient information and can be applied across a range of populations. PCPTHG risk thresholds ranging from 5 to 20 %, depending on patient risk averseness, are recommended for clinical prostate biopsy decision-making. [ABSTRACT FROM AUTHOR]

Objectives: To compare the predictive performance and potential clinical usefulness of risk calculators of the European Randomized Study of Screening for Prostate Cancer (ERSPC RC) with and without information on prostate volume. Methods: We studied 6 cohorts (5 European and 1 US) with a total of 15,300 men, all biopsied and with pre-biopsy TRUS measurements of prostate volume. Volume was categorized into 3 categories (25, 40, and 60 cc), to reflect use of digital rectal examination (DRE) for volume assessment. Risks of prostate cancer were calculated according to a ERSPC DRE-based RC (including PSA, DRE, prior biopsy, and prostate volume) and a PSA + DRE model (including PSA, DRE, and prior biopsy). Missing data on prostate volume were completed by single imputation. Risk predictions were evaluated with respect to calibration (graphically), discrimination (AUC curve), and clinical usefulness (net benefit, graphically assessed in decision curves). Results: The AUCs of the ERSPC DRE-based RC ranged from 0.61 to 0.77 and were substantially larger than the AUCs of a model based on only PSA + DRE (ranging from 0.56 to 0.72) in each of the 6 cohorts. The ERSPC DRE-based RC provided net benefit over performing a prostate biopsy on the basis of PSA and DRE outcome in five of the six cohorts. Conclusions: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider multiple factors, including an estimate of prostate volume. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the discrimination, calibration, and net benefit performance of the Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) across five European randomized study of screening for prostate cancer (ERSPC), 1 United Kingdom, 1 Austrian, and 3 US biopsy cohorts. Methods: PCPTRC risks were calculated for 25,733 biopsies using prostate-specific antigen (PSA), digital rectal examination, family history, history of prior biopsy, and imputation for missing covariates. Predictions were evaluated using the areas underneath the receiver operating characteristic curves (AUC), discrimination slopes, chi-square tests of goodness of fit, and net benefit decision curves. Results: AUCs of the PCPTRC ranged from a low of 56% in the ERSPC Goeteborg Rounds 2-6 cohort to a high of 72% in the ERSPC Goeteborg Round 1 cohort and were statistically significantly higher than that of PSA in 6 out of the 10 cohorts. The PCPTRC was well calibrated in the SABOR, Tyrol, and Durham cohorts. There was limited to no net benefit to using the PCPTRC for biopsy referral compared to biopsying all or no men in all five ERSPC cohorts and benefit within a limited range of risk thresholds in all other cohorts. Conclusions: External validation of the PCPTRC across ten cohorts revealed varying degree of success highly dependent on the cohort, most likely due to different criteria for and work-up before biopsy. Future validation studies of new calculators for prostate cancer should acknowledge the potential impact of the specific cohort studied when reporting successful versus failed validation. [ABSTRACT FROM AUTHOR]

Purpose: In prostate cancer cases the early diagnosis of tumors carrying a high risk of progression is of the utmost importance. There is an urgent clinical need to avoid unnecessary biopsies and subsequent overtreatment. We validated annexin A3 as a diagnostic marker for prostatic disease in typical clinical populations and relevant segments, such as patients with a negative digital rectal examination and low prostate specific antigen. Materials and Methods: We performed a blinded clinical study (ClinicalTrials.gov Identifier NCT00400894) from September 2005 to January 2007 in 591 patients who were continuously recruited from 4 European urological clinics. Urine was obtained directly after digital rectal examination and the annexin A3 concentration in urine was quantified by Western blot. Statistical analysis included combinations of annexin A3 with total, percent free, complexed and percent complexed prostate specific antigen. Results: Combined readouts of prostate specific antigen and urinary annexin A3 were superior to all others with an area under the ROC curve of 0.82 for a total prostate specific antigen range of 2 to 6 ng/ml, 0.83 for a total prostate specific antigen range of 4 to 10 ng/ml and 0.81 in all patients. The best performing prostate specific antigen derivative was percent free prostate specific antigen with an area under the ROC curve of 0.68 for a total prostate specific antigen range of 2 to 6 ng/ml, 0.72 for a total prostate specific antigen range of 4 to 10 ng/ml and 0.73 in all patients. Annexin A3 has an inverse relationship to cancer and, therefore, its specificity was much better than that of prostate specific antigen. Conclusions: Annexin A3 quantification in urine provides a novel noninvasive biomarker with high specificity. Annexin A3 is complementary to prostate specific antigen or to any other cancer marker. It has a huge potential to avoid unnecessary biopsies with a particular strength in the clinically relevant large group of patients who have a negative digital rectal examination and prostate specific antigen in the lower range of values (2 to 10 ng/ml). [Copyright &y& Elsevier]

Simple Summary: We have proved here that a magnetic bead-based assay using lectins can be effectively applied for glycoprofiling of free prostate specific antigen (fPSA). Such a glycan-based biomarker improves the detection of prostate cancer (PCa) in the PSA grey zone, the discrimination between clinically significant and insignificant cancer, and can significantly reduce the number of unnecessary prostate biopsies and re-biopsies, outperforming current second opinion tests such as percentage of fPSA (fPSA%) and the prostate health index (PHI). Background: To compare the clinical performance of a new PCa serum biomarker based on fPSA glycoprofiling to fPSA% and PHI. Methods: Serum samples from men who underwent prostate biopsy due to increased PSA were used. A comparison between two equal groups (with histologically confirmed PCa or benign, non-cancer condition) was used for the clinical validation of a new glycan-based PCa oncomarker. SPSS and R software packages were used for the multiparametric analyses of the receiver operating curve (ROC) and for genetic algorithm metaheuristics. Results: When comparing the non-cancer and PCa cohorts, the combination of four fPSA glycoforms with two clinical parameters (PGI, prostate glycan index (PGI)) showed an area under receiver operating curve (AUC) value of 0.821 (95% CI 0.754–0.890). AUC values were 0.517 for PSA, 0.683 for fPSA%, and 0.737 for PHI. A glycan analysis was also applied to discriminate low-grade tumors (GS = 6) from significant tumors (GS ≥ 7). Conclusions: Compared to PSA on its own, or fPSA% and the PHI, PGI showed improved discrimination between presence and absence of PCa and in predicting clinically significant PCa. In addition, the use of PGI would help practitioners avoid 63.5% of unnecessary biopsies, while the use of fPSA% and PHI would help avoid 17.5% and 33.3% of biopsies, respectively, while missing four significant tumors (9.5%). [ABSTRACT FROM AUTHOR]

Abstract: Background: Novel markers for prostate cancer (PCa) detection are needed. Total prostate-specific antigen (tPSA) and percent free prostate-specific antigen (%fPSA=tPSA/fPSA) lack diagnostic specificity. Objective: To evaluate the use of prostate-specific antigen (PSA) isoforms p2PSA and benign prostatic hyperplasia–associated PSA (BPHA). Design, setting, and participants: Our study included 405 serum samples from the Rotterdam arm of the European Randomised Study of Screening for Prostate Cancer and 351 samples from the Urology Department of Innsbruck Medical University. Measurements: BPHA, tPSA, fPSA, and p2PSA levels were measured by Beckman-Coulter Access Immunoassay. In addition, the Beckman Coulter Prostate Health Index was calculated: phi=(p2PSA/fPSA)×√(tPSA). Results and limitations: The p2PSA and phi levels differed significantly between men with and without PCa. No difference in BPHA levels was observed. The highest PCa predictive value in both cohorts was achieved by phi with areas under the curve (AUCs) of 0.750 and 0.709, a significant increase compared to tPSA (AUC: 0.585 and 0.534) and %fPSA (AUC: 0.675 and 0.576). Also, %p2PSA (p2PSA/fPSA) showed significantly higher AUCs compared to tPSA and %fPSA (AUC: 0.716 and 0.695, respectively). At 95% and 90% sensitivity, the specificities of phi were 23% and 31% compared to 10% and 8% for tPSA, respectively. In both cohorts, multivariate analysis showed a significant increase in PCa predictive value after addition of p2PSA to a model consisting of tPSA and fPSA (increase in AUC from 0.675 to 0.755 and from 0.581 to 0.697, respectively). Additionally, the specificity at 95% sensitivity increased from 8% to 24% and 7% to 23%, respectively. Furthermore, %p2PSA, phi, and the model consisting of tPSA and fPSA with or without the addition of p2PSA missed the least of the tumours with a biopsy or pathologic Gleason score ≥7 at 95% and 90% sensitivity. Conclusions: This study shows significant increases in PCa predictive value and specificity of phi and %p2PSA compared to tPSA and %fPSA. p2PSA has limited additional value in identifying aggressive PCa (Gleason score ≥7). [Copyright &y& Elsevier]

: ObjectivesTo determine the clinical utility of using proenzyme prostate-specific antigen (pPSA) for early detection of prostate cancer in the 2.5 to 4.0 ng/mL total PSA range. pPSA, the precursor form of PSA that contains a 7 amino acid leader peptide, and truncated forms such as [−2]pPSA and [−4]pPSA can be measured in serum by research immunoassay.: MethodsArchival serum from 119 men (noncancer, 88; cancer, 31), obtained before biopsy and in the total PSA range of 2.5 to 4.0 ng/mL, were assayed for total PSA, free PSA (fPSA), and pPSA. pPSA was defined as the sum of the [−2], [−4], and [−7] forms, and the percent pPSA (%pPSA) was defined as pPSA/fPSA.: ResultspPSA averaged 4.6% ± 0.4% (SEM) of total PSA and 39.3% ± 3.5% of fPSA. PSA and %fPSA values were similar between the noncancer and cancer groups, and %pPSA tended to be higher in the cancer group (50.1% ± 4.4%) compared with the noncancer group (35.5% ± 6.7%; P = 0.07). Using receiver operating characteristic analysis to assess clinical utility, the area under the curve for %pPSA was 0.688 compared with 0.567 for %fPSA. At a fixed sensitivity of 75%, the specificity was significantly greater for %pPSA at 59% compared with %fPSA at 33% (P <0.0001).: ConclusionsIn the 2.5 to 4.0 ng/mL total PSA range, 75% of cancers can potentially be detected with 59% of unnecessary biopsies being spared using %pPSA; use of %fPSA would result in sparing only 33% of unnecessary biopsies. A large prospective clinical trial is needed to confirm these preliminary findings. [Copyright &y& Elsevier]