A Four-kallikrein Panel Predicts High-grade Cancer on Biopsy: Independent Validation in a Community Cohort

Performance of 4Kscore as a Reflex Test to Prostate-specific Antigen in the GÖTEBORG-2 Prostate Cancer Screening Trial

BACKGROUND AND OBJECTIVE

We investigated whether adding 4Kscore as a reflex test to prostate-specific antigen (PSA) could improve the screening algorithm for prostate cancer (PC).

METHODS

In the GÖTEBORG-2 PC screening trial, 38 000men (50-60 yr) were invited to PSA testing and, if elevated, followed by magnetic resonance imaging (MRI). For 571 men with PSA ≥3.0 ng/ml and evaluable outcomes, 4Kscore was calculated. The performance using a prespecified 4Kscore cutoff of 7.5% was evaluated.

KEY FINDINGS AND LIMITATIONS

The area under the curve for 4Kscore to identify intermediate- and high-risk PC was 0.84 (95% confidence interval 0.79-0.89), and the positive predictive value, and negative predictive value were 15% (0.12-0.20) and 99% (97-100%), respectively. Of the 54 men diagnosed with intermediate- or high-grade PC, two had a 4Kscore cutoff below 7.5%, both with organ-confined intermediate-risk PC. Per 1000 men with elevated PSA, adding 4Kscore would have resulted in avoidance of MRI for 408 (41%) men, biopsies for 95 (28% reduction) men, and diagnosis of 23 low-grade cancers (23% reduction) while delaying the diagnosis of four men with intermediate-grade cancers (4%).

CONCLUSIONS AND CLINICAL IMPLICATIONS

Including 4Kscore as a reflex test for men with elevated PSA reduces the need for MRI and biopsy markedly, and results in less overdiagnosis of low-grade PC at the cost of delaying the diagnosis of intermediate-grade PC in a few men. These results add further evidence for including new blood-based biomarkers in addition to PSA to improve the harm and benefit ratio of PC screening and reduce the need for resource-demanding MRI and biopsies.

Diagnostic Accuracy of Liquid Biomarkers for Clinically Significant Prostate Cancer Detection: A Systematic Review and Diagnostic Meta-analysis of Multiple Thresholds

CONTEXT

Many liquid biomarkers have entered clinical practice with the praise to improve the detection of clinically significant prostate cancer (csPCa), helping avoid unnecessary prostate biopsies.

OBJECTIVE

We aimed to assess the diagnostic accuracy of multianalyte biomarkers for csPCa detection using multiple thresholds.

EVIDENCE ACQUISITION

A comprehensive literature search was done through PubMed, Web of Science, and Scopus in March 2023 for prospective and retrospective studies reporting the diagnostic performance of liquid biomarkers for detecting csPCa. The outcomes of interest were the diagnostic performance of liquid biomarkers for csPCa detection and identification of optimal thresholds for each biomarker.

EVIDENCE SYNTHESIS

Overall, 49 studies were eligible for this meta-analysis. Using each representative threshold based on the Youden Index, the pooled sensitivity and specificity for detecting csPCa were 0.85 and 0.37 for prostate cancer gene 3 (PCA3), 0.85 and 0.52 for prostate health index (PHI), 0.87 and 0.58 for four kallikrein (4K), 0.82 and 0.56 for SelectMDx, 0.85 and 0.54 for ExoDx, and 0.82 and 0.59 for mi prostate score (MPS), respectively. The diagnostic odds ratio was highest for 4K (8.84), followed by MPS (7.0) and PHI (6.28). According to the meta-analysis incorporating multiple thresholds, the corresponding sensitivity was 0.77 for 4K, 0.69 for PHI, and 0.63 for PCA3; specificity was 0.72 for PHI, 0.70 for 4K, and 0.69 for PCA3.

CONCLUSIONS

Regarding the detection of csPCa, 4K had the highest diagnostic performance among the commercial liquid biomarkers. Based on the optimal thresholds calculated by the present meta-analysis, 4K had the highest sensitivity and PHI had the highest specificity for detecting csPCa. Nevertheless, clinical decision-making requires combination strategies between liquid and imaging biomarkers.

PATIENT SUMMARY

Novel biomarkers for prostate cancer detection were useful for more accurate diagnosis of clinically significant prostate cancer to avoid unnecessary biopsies.

Evaluation of blood and urine based biomarkers for detection of clinically-significant prostate cancer

BACKGROUND

Recognizing the limitations of prostate-specific antigen (PSA) screening and the morbidity of prostate biopsies, several blood- and urine-based biomarkers have been proposed for pre-biopsy risk stratification. These assays aim to reduce the frequency of unnecessary biopsies (i.e., negative or Grade Group 1 [GG1]) while maintaining highly sensitive detection of clinically significant cancer (GG ≥ 2) prostate cancer.

METHODS

We reviewed the literature describing the use of currently available blood- and urine-based biomarkers for detection of GG ≥ 2 cancer, including the Prostate Health Index (PHI), 4Kscore, MyProstateScore (MPS), SelectMDx, ExoDx Prostate Intelliscore (EPI), and IsoPSA. To facilitate clinical application, we focused on the use of biomarkers as a post-PSA secondary test prior to biopsy, as proposed in clinical guidelines. Our outcomes included test performance measures-sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV)-as well as clinical outcomes resulting from biomarker use (i.e., unnecessary biopsies avoided, GG ≥ 2 cancers missed).

RESULTS

Contemporary validation data (2015-2023) reveal that currently available biomarkers provide ~15-50% specificity at a sensitivity of 90-95% for GG ≥ 2 PCa. Clinically, this indicates that secondary use of biomarker testing in men with elevated PSA could allow for avoidance of up to 15-50% of unnecessary prostate biopsies, while preserving detection of 90-95% of GG ≥ 2 cancers that would be detected under the traditional "biopsy all" approach.

CONCLUSIONS

The contemporary literature further supports the proposed role of post-PSA biomarker testing to reduce the use of invasive biopsy while maintaining highly sensitive detection of GG ≥ 2 cancer. Questions remain regarding the optimal application of biomarkers in combination or in sequence with mpMRI.

Prostate Cancer Screening With PSA, Kallikrein Panel, and MRI: The ProScreen Randomized Trial

Importance

Prostate-specific antigen (PSA) screening has potential to reduce prostate cancer mortality but frequently detects prostate cancer that is not clinically important.

Objective

To describe rates of low-grade (grade group 1) and high-grade (grade groups 2-5) prostate cancer identified among men invited to participate in a prostate cancer screening protocol consisting of a PSA test, a 4-kallikrein panel, and a magnetic resonance imaging (MRI) scan.

Design, Setting, and Participants

The ProScreen trial is a clinical trial conducted in Helsinki and Tampere, Finland, that randomized 61 193 men aged 50 through 63 years who were free of prostate cancer in a 1:3 ratio to either be invited or not be invited to undergo screening for prostate cancer between February 2018 and July 2020.

Interventions

Participating men randomized to the intervention underwent PSA testing. Those with a PSA level of 3.0 ng/mL or higher underwent additional testing for high-grade prostate cancer with a 4-kallikrein panel risk score. Those with a kallikrein panel score of 7.5% or higher underwent an MRI of the prostate gland, followed by targeted biopsies for those with abnormal prostate gland MRI findings. Final data collection occurred through June 31, 2023.

Main Outcomes and Measures

In descriptive exploratory analyses, the cumulative incidence of low-grade and high-grade prostate cancer after the first screening round were compared between the group invited to undergo prostate cancer screening and the control group.

Results

Of 60 745 eligible men (mean [SD] age, 57.2 [4.0] years), 15 201 were randomized to be invited and 45 544 were randomized not to be invited to undergo prostate cancer screening. Of 15 201 eligible males invited to undergo screening, 7744 (51%) participated. Among them, 32 low-grade prostate cancers (cumulative incidence, 0.41%) and 128 high-grade prostate cancers (cumulative incidence, 1.65%) were detected, with 1 cancer grade group result missing. Among the 7457 invited men (49%) who refused participation, 7 low-grade prostate cancers (cumulative incidence, 0.1%) and 44 high-grade prostate cancers (cumulative incidence, 0.6%) were detected, with 7 cancer grade groups missing. For the entire invited screening group, 39 low-grade prostate cancers (cumulative incidence, 0.26%) and 172 high-grade prostate cancers (cumulative incidence, 1.13%) were detected. During a median follow-up of 3.2 years, in the group not invited to undergo screening, 65 low-grade prostate cancers (cumulative incidence, 0.14%) and 282 high-grade prostate cancers (cumulative incidence, 0.62%) were detected. The risk difference for the entire group randomized to the screening invitation vs the control group was 0.11% (95% CI, 0.03%-0.20%) for low-grade and 0.51% (95% CI, 0.33%-0.70%) for high-grade cancer.

Conclusions and Relevance

In this preliminary descriptive report from an ongoing randomized clinical trial, 1 additional high-grade cancer per 196 men and 1 low-grade cancer per 909 men were detected among those randomized to be invited to undergo a single prostate cancer screening intervention compared with those not invited to undergo screening. These preliminary findings from a single round of screening should be interpreted cautiously, pending results of the study's primary mortality outcome.

Trial Registration

ClinicalTrials.gov Identifier: NCT03423303.

Liquid Biomarkers in Prostate Cancer Diagnosis: Current Status and Emerging Prospects

Prostate cancer (PCa) is a major health concern that necessitates appropriate diagnostic approaches for timely intervention. This review critically evaluates the role of liquid biopsy techniques, focusing on blood- and urine-based biomarkers, in overcoming the limitations of conventional diagnostic methods. The 4Kscore test and Prostate Health Index have demonstrated efficacy in distinguishing PCa from benign conditions. Urinary biomarker tests such as PCa antigen 3, MyProstateScore, SelectMDx, and ExoDx Prostate IntelliScore test have revolutionized risk stratification and minimized unnecessary biopsies. Emerging biomarkers, including non-coding RNAs, circulating tumor DNA, and prostate-specific antigen (PSA) glycosylation, offer valuable insights into PCa biology, enabling personalized treatment strategies. Advancements in non-invasive liquid biomarkers for PCa diagnosis may facilitate the stratification of patients and avoid unnecessary biopsies, particularly when PSA is in the gray area of 4 to 10 ng/mL.

Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer

BACKGROUND

There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer.

OBJECTIVES

To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set.

DESIGN, SETTINGS, AND PARTICIPANTS

About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.

METHODS

Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer.

RESULTS

The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10.

CONCLUSIONS

The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis.

Biomarkers for Prostate Cancer: From Diagnosis to Treatment

Prostate cancer (PCa) is a widespread malignancy with global significance, which substantially affects cancer-related mortality. Its spectrum varies widely, from slow-progressing cases to aggressive or even lethal forms. Effective patient stratification into risk groups is crucial to therapeutic decisions and clinical trials. This review examines a wide range of diagnostic and prognostic biomarkers, several of which are integrated into clinical guidelines, such as the PHI, the 4K score, PCA3, Decipher, and Prolaris. It also explores the emergence of novel biomarkers supported by robust preclinical evidence, including urinary miRNAs and isoprostanes. Genetic alterations frequently identified in PCa, including BRCA1/BRCA2, ETS gene fusions, and AR changes, are also discussed, offering insights into risk assessment and precision treatment strategies. By evaluating the latest developments and applications of PCa biomarkers, this review contributes to an enhanced understanding of their role in disease management.

Economic evaluation of prostate cancer risk assessment methods: A cost-effectiveness analysis using population data

BACKGROUND

The current prostate cancer (PCa) screening standard of care (SOC) leads to unnecessary biopsies and overtreatment because decisions are guided by prostate-specific antigen (PSA) levels, which have low specificity in the gray zone (3-10 ng/mL). New risk assessment tools (RATs) aim to improve biopsy decision-making. We constructed a modeling framework to assess new RATs in men with gray zone PSA from the British Columbia healthcare system's perspective.

METHODS

We evaluated the cost-effectiveness of a new RAT used in biopsy-naïve men aged 50+ with a PSA of 3-10 ng/mL using a time-dependent state-transition model. The model was informed by engaging patient partners and using linked administrative health data, supplemented with published literature. The incremental cost-effectiveness ratio and the probability of the RAT being cost-effective were calculated. Probabilistic analysis was used to assess parameter uncertainty.

RESULTS

In the base case, a RAT based on an existing biomarker's characteristics was a dominant strategy associated with a cost savings of $44 and a quality-adjusted life years (QALY) gain of 0.00253 over 18 years of follow-up. At a cost-effectiveness threshold of $50,000/QALY, the probability that using a RAT is cost-effective relative to the SOC was 73%. Outcomes were sensitive to RAT costs and accuracy, especially the detection rate of high-grade PCa. Results were also impacted by PCa prevalence and assumptions about undetected PCa survival.

CONCLUSIONS

Our findings showed that a more accurate RAT to guide biopsy can be cost-effective. Our proposed general model can be used to analyze the cost-effectiveness of any novel RAT.

Clinical analysis of EV-Fingerprint to predict grade group 3 and above prostate cancer and avoid prostate biopsy

BACKGROUND

There is an unmet clinical need for minimally invasive diagnostic tests to improve the detection of grade group (GG) ≥3 prostate cancer relative to prostate antigen-specific risk calculators. We determined the accuracy of the blood-based extracellular vesicle (EV) biomarker assay (EV Fingerprint test) at the point of a prostate biopsy decision to predict GG ≥3 from GG ≤2 and avoid unnecessary biopsies.

METHODS

This study analyzed 415 men referred to urology clinics and scheduled for a prostate biopsy, were recruited to the APCaRI 01 prospective cohort study. The EV machine learning analysis platform was used to generate predictive EV models from microflow data. Logistic regression was then used to analyze the combined EV models and patient clinical data and generate the patients' risk score for GG ≥3 prostate cancer.

RESULTS

The EV-Fingerprint test was evaluated using the area under the curve (AUC) in discrimination of GG ≥3 from GG ≤2 and benign disease on initial biopsy. EV-Fingerprint identified GG ≥3 cancer patients with high accuracy (0.81 AUC) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cutoff, 95% of men with GG ≥3 would have been recommended a biopsy while avoiding 144 unnecessary biopsies (35%) and missing four GG ≥3 cancers (5%). Conversely, a 5% cutoff would have avoided 31 unnecessary biopsies (7%), missing no GG ≥3 cancers (0%).

CONCLUSIONS

EV-Fingerprint accurately predicted GG ≥3 prostate cancer and would have significantly reduced unnecessary prostate biopsies.

Managing the impact of inter-method bias of prostate specific antigen assays on biopsy referral: the key to move towards precision health in prostate cancer management

OBJECTIVES

We assessed the inter-method bias of total (tPSA) and free (fPSA) prostate-specific antigen (PSA) immunoassays to establish if tPSA-based risk thresholds for advanced prostate cancer (PCa), obtained from one method (Roche) can be converted into the corresponding concentrations assayed by other methods. Then we evaluated the impact of the bias of tPSA and fPSA on the estimation of the %f/tPSA ratio and performed a re-calibration of the proposed thresholds for the %f/tPSA ratio according to the assay used.

METHODS

tPSA and fPSA were measured in 135 and 137 serum samples, respectively by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM analytical platforms. Scatterplots, Bland-Altman diagrams, Passing-Bablok (PB) were used to inspect and estimate the systematic and proportional bias between the methods. The linear equations with confidence intervals of the parameter estimates were used to transform the tPSA risk thresholds for advanced PCa into the corresponding concentrations measurable by the other analytical methods. To construct a correction coefficient for converting the %f/tPSA ratio from one method to the other, PB and non-parametric boostrapping were used.

RESULTS

The inter-method bias is not constant but strictly linear allowing the conversion of PSA results obtained from Roche into the other assays, which underestimate tPSA vs. Roche. Siemens and Abbott vs. Roche and Beckman assays, being characterized by a positive and a negative proportional bias for tPSA and fPSA measurements, tend to overestimate the %f/tPSA ratio.

CONCLUSIONS

There is a consistent risk to miss advanced PCa, if appropriate conversion factors are not applied.

External Validation of the Prostate Biopsy Collaborative Group Risk Calculator and the Rotterdam Prostate Cancer Risk Calculator in a Swedish Population-based Screening Cohort

Background

External validation of risk calculators (RCs) is necessary to determine their clinical applicability beyond the setting in which these were developed.

Objective

To assess the performance of the Rotterdam Prostate Cancer RC (RPCRC) and the Prostate Biopsy Collaborative Group RC (PBCG-RC).

Design, setting, and participants

We used data from the prospective, population-based STHLM3 screening study, performed in 2012–2015. Participants with prostate-specific antigen ≥3 ng/ml who underwent systematic prostate biopsies were included.

Outcome measurements and statistical analysis

Probabilities for clinically significant prostate cancer (csPCa), defined as International Society of Urological Pathology grade ≥2, were calculated for each participant. External validity was assessed by calibration, discrimination, and clinical usefulness for both original and recalibrated models.

Results and limitations

Out of 5841 men, 1054 (18%) had csPCa. Distribution of risk predictions differed between RCs; median risks for csPCa using the RPCRC and PBCG-RC were 3.3% (interquartile range [IQR] 2.1–7.1%) and 20% (IQR 15–28%), respectively. The correlation between RC risk estimates on individual level was moderate (Spearman’s r = 0.55). Using the RPCRC’s recommended risk threshold of ≥4% for finding csPCa, 36% of participants would get concordant biopsy recommendations. At 10% risk cut-off, RCs agreed in 23% of cases. Both RCs showed good discrimination, with areas under the curves for the RPCRC of 0.74 (95% confidence interval [CI] 0.72–0.76) and the PBCG-RC of 0.70 (95% CI 0.68–0.72). Calibration was adequate using the PBCG-RC (calibration slope: 1.13 [95% CI 1.03–1.23]), but the RPCRC underestimated the risk of csPCa (calibration slope: 0.73 [0.68–0.79]). The PBCG-RC showed a net benefit in a decision curve analysis, whereas the RPCRC showed no net benefit at clinically relevant risk threshold levels. Recalibration improved clinical benefit, and differences between RCs decreased.

Conclusions

Assessment of calibration is essential to ensure the clinical value of risk prediction tools. The PBCG-RC provided clinical benefit in its current version online. On the contrary, the RPCRC cannot be recommended in this setting.

Patient summary

Predicting the probability of finding prostate cancer on biopsy differed between two assessed risk calculators. After recalibration, the agreement of the models improved, and both were shown to be clinically useful.

Grade Migration of Prostate Cancer in the United States During the Last Decade

BACKGROUND

Prostate cancer (PC) screening guidelines have changed over the last decade to reduce overdiagnosis and overtreatment of low-grade disease. We sought to examine and attempt to explain how changes in screening strategies have impacted temporal trends in Gleason grade group (GG) PC at diagnosis and radical prostatectomy pathology.

METHODS

Using the Surveillance, Epidemiology, and End Results Registry database, we identified 438 432 men with newly diagnosed PC during 2010-2018. Temporal trends in incidence of GG at biopsy, radical prostatectomy pathology, prostate-specific antigen (PSA) level, and metastasis at diagnosis were examined. The National Health Interview Survey database was examined to evaluate trends in PSA-screening rates, and a literature review evaluating magnetic resonance imaging and biomarkers utilization during this period was performed.

RESULTS

Between 2010 and 2018, the incidence of low-grade PC (GG1) decreased from 52 to 26 cases per 100 000 (P < .001). The incidence of GG1 as a proportion of all PC decreased from 47% to 32%, and the proportion of GG1 at radical prostatectomy pathology decreased from 32% to 10% (P < .001). However, metastases at diagnosis increased from 3.0% to 5.2% (P < .001). During 2010-2013, PSA screening rates in men aged 50-74 years declined from 39 to 32 per 100 men and remained stable. Utilization rates of magnetic resonance imaging and biomarkers modestly increased from 7.2% in 2012 to 17% in 2019 and 1.3% in 2012 to 13% in 2019, respectively.

CONCLUSIONS

We found a significant decrease in the diagnosis and treatment of GG1 PC between 2010 and 2018. Changes in PSA screening practices appear as the primary contributor. Public health efforts should be directed toward addressing the increase in the diagnoses of metastatic PC.

Population‐based randomized trial of screening for clinically significant prostate cancer ProScreen: pilot study

Objectives

To evaluate the feasibility of a population‐based screening trial using prostate‐specific antigen (PSA), a kallikrein panel and multiparametric magnetic resonance imaging (MRI) aimed at minimizing overdiagnosis, while retaining mortality benefit.

Patients and Methods

Feasibility of the screening algorithm was evaluated in terms of participation, screening test results and cancer detection. A random sample of 400 men aged 65 years was identified from the population registry and invited for screening with three stepwise tests (PSA, kallikrein panel and MRI). Men with PSA levels ≥3 ng/mL were further tested with the kallikrein panel, and those with positive findings (risk >7.5%) were referred for prostate MRI. Men with positive MRI (Prostate Imaging Reporting and Data System [PI‐RADS] score 3–5) had targeted biopsies only. Men with negative MRI, but PSA density ≥0.15 underwent systematic biopsies.

Results

Of the 399 men invited, 158 (40%) participated and 27 had PSA levels ≥3 ng/mL (7% of the invited and 17% of the participants). Of these, 22 had a positive kallikrein panel (6% of the invited and 81% of the PSA‐positive men). Finally, 10 men (3% of the invited and 45% of 4Kscore [kallikrein panel]‐positive) had a suspicious MRI finding (PI‐RADS score ≥3) and five were diagnosed with a clinically significant prostate cancer (Gleason Grade Group [GG] ≥2) at fusion biopsy (3% of the participants), with two GG 1 cases (1%). Additional testing (kallikrein panel and MRI) after PSA reduced biopsies by 56%.

Conclusion

The findings constitute proof of principle for our screening protocol, as we achieved a substantial detection rate for clinically significant cancer with few clinically insignificant cases. Participation, however, was suboptimal.

The versatile role of the contact system in cardiovascular disease, inflammation, sepsis and cancer

The human contact system consists of plasma proteins, which - after contact to foreign surfaces - are bound to them, thereby activating the zymogens of the system into enzymes. This activation mechanism gave the system its name - contact system. It is considered as a procoagulant and proinflammatory response mechanism, as activation finally leads to the generation of fibrin and bradykinin. To date, no physiological processes have been described that are mediated by contact activation. However, contact system factors play a pathophysiological role in numerous diseases, such as cardiovascular diseases, arthritis, colitis, sepsis, and cancer. Contact system factors are therefore an interesting target for new therapeutic options in different clinical conditions.

Fascin-1 and its role as a serological marker in prostate cancer: a prospective case-control study

Aim:

This study aims to investigate any modification of serological FSCN1 in prostate cancer patients compared with patients without neoplasia.

Material & methods:

Clinical data and blood specimens from patients with and without prostate cancer were obtained. A quantitative sandwich ELISA method was used to determine serological values of FSCN1.

Results:

Although serum values of FSCN1 were dissimilar in the two cohorts of patients (6.90 vs 7.33 ng/ml), the difference was not statistically significant (p = 0.20). Serum values of FSCN1 stratified for Gleason score groups were not significantly distinguishable (p = 0.65). A negative correlation (rho = -0.331; p = 0.009) was reported between FSCN1 and age.

Conclusion:

Further studies are required to evaluate a possible diagnostic role of FSCN1 in prostate cancer.

FSCN1 is a potential novel biomarker that we investigated in patients with prostate cancer and evaluated in serum through a quantitative assay. Although FSCN1 serum values were dissimilar between patients with and without prostate cancer (with lower values in the first group), data are currently inconclusive. A negative correlation between FSCN1 and age was instead reported. Further studies are required to investigate a possible diagnostic role of FSCN1.

Individual Patient Data Meta-analysis of Discrimination of the Four Kallikrein Panel Associated With the Inclusion of Prostate Volume

OBJECTIVE

To assess whether adding prostate volume to the kallikrein panel improves discrimination for ISUP Grade Group 2 or higher (GG2+) disease, as some men may have volume measurements available at the time of blood draw. While prostate volume predicts biopsy outcome, it requires an imaging procedure for measurement. The four kallikrein panel - commercially available as the 4Kscore - predicts risk of GG2+ disease and requires only a blood draw.

MATERIALS AND METHODS

A total of 9131 patients with available prostate volume and total PSA ≤25 ng/ml from 5 historical (sextant biopsy, pre-ISUP 2005 grading) and 4 contemporary cohorts (10+ cores, ISUP 2005 grading). Previously published kallikrein panel models were used to predict risk of GG2+. Volume was added to the model in each cohort and change in discrimination was meta-analyzed.

RESULTS

Increased prostate volume was associated with decreased risk of GG2+ disease after controlling for the kallikrein panel in 7/9 cohorts. However, kallikrein panel discrimination (0.817, 95% CI 0.802, 0.831) was not improved after including volume (AUC difference 0.002, 95% CI -0.003, 0.006). Heterogeneity (P <.0001) was driven by an AUC increase in 1 cohort of academic cancer centers (0.044, 95% CI 0.025, 0.064), with no evidence of heterogeneity after excluding this cohort (P = .15).

CONCLUSION

The kallikrein panel provides a non-invasive approach to assess the risk of high-grade prostate cancer. Our results do not justify the inclusion of prostate volume in the four kallikrein panel. There is some evidence that the predictive value of prostate volume is provider dependent: further research is needed to address this question.

Biomarkers for detection of clinically significant prostate cancer: contemporary clinical data and future directions

Use of serum prostate-specific antigen (PSA) testing for early detection of prostate cancer appears to reduce cancer-specific mortality. Due to the limited specificity of PSA for clinically significant [Grade Group (GG) ≥2] cancer, however, screening carries substantial risks, including frequent unnecessary prostate biopsies and overdetection of non-aggressive cancers. To that end, serum and urine biomarkers with improved specificity for GG ≥2 cancer have been proposed for clinical use following PSA. In the current article, we present clinical validation data for five such biomarkers: PHI, 4Kscore, SelectMDx, ExoDx, and MPS. For all studies, we specify the study population (overall biopsy referral vs. pre-specified PSA ranges), previous biopsy status (biopsy-naïve vs. previous negative biopsy), and the proportion of subjects diagnosed with GG ≥2 cancer. Outcomes include test performance characteristics: sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). Published data were used to compute the number of unnecessary biopsies avoided and number of GG ≥2 cancers missed if the biomarker had been used clinically to select for prostate biopsy. The evidence review is preceded by a primer on these and other clinically-relevant summary statistics.

Prospective validation of microseminoprotein-β added to the 4Kscore in predicting high-grade prostate cancer in an international multicentre cohort

OBJECTIVES

To prospectively evaluate the performance of a pre-specified statistical model based on four kallikrein markers in blood (total prostate-specific antigen [PSA], free PSA, intact PSA, and human kallikrein-related peptidase 2), commercially available as the 4Kscore, in predicting Gleason Grade Group (GG) ≥2 prostate cancer at biopsy in an international multicentre study at three academic medical centres, and whether microseminoprotein-β (MSP) adds predictive value.

PATIENTS AND METHODS

A total of 984 men were prospectively enrolled at three academic centres. The primary outcome was GG ≥2 on prostate biopsy. Three pre-specified statistical models were used: a base model including PSA, age, digital rectal examination and prior negative biopsy; a model that added free PSA to the base model; and the 4Kscore.

RESULTS

A total of 947 men were included in the final analysis and 273 (29%) had GG ≥2 on prostate biopsy. The base model area under the receiver operating characteristic curve of 0.775 increased to 0.802 with the addition of free PSA, and to 0.824 for the 4Kscore. Adding MSP to the 4Kscore model yielded an increase (0.014-0.019) in discrimination. In decision-curve analysis of clinical utility, the 4Kscore showed a benefit starting at a 7.5% threshold.

CONCLUSION

A prospective multicentre evaluation of a pre-specified model based on four kallikrein markers (4Kscore) with the addition of MSP improves the predictive discrimination for GG ≥2 prostate cancer on biopsy and could be used to inform biopsy decision-making.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer

BACKGROUND

Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group ≥ 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI).

PURPOSE

To develop and validate radiomics and kallikrein models for the detection of csPCa.

STUDY TYPE

Retrospective.

POPULATION

A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated.

FIELD STRENGTH/SEQUENCE

A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI.

ASSESSMENT

In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores.

STATISTICAL TESTS

For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant.

RESULTS

The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488).

DATA CONCLUSION

The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

[Diagnostic markers in urology]

Cancer diagnostics can be supplemented by disease-related biomarkers. In the course of modern patient-tailored cancer treatment, the importance of correct risk stratification, prognosis and monitoring has significantly increased. In recent years, a multitude of biomarkers and related test procedures have emerged to fulfil this purpose. The following review article summarizes the most recent developments with respect to the use of biomarkers in the diagnostics of urological cancers.

Can serum endoglin be used to improve the diagnostic performance in prostate cancer?

PURPOSE

New biomarkers may contribute to avoid unnecessary biopsies resulting from the suboptimal performance of prostate-specific antigen (PSA) testing. This study aimed to assess serum endoglin as a prostate cancer (PCa) diagnostic tool among biopsy candidates.

METHODS

A total of 262 consecutive patients referred for prostate biopsy based on abnormal digital rectal examination and/or elevated total PSA (tPSA) who had serum endoglin assessed by solid-phase enzyme-linked immunosorbent assay were selected. Receiver operating characteristic curves were used to compare the predictive accuracy of different combinations of biomarkers to distinguish between PCa and benign prostatic conditions, and to identify cut-offs that maximize the ability of endoglin to rule out patients for biopsy (highest sensitivities).

RESULTS

Serum endoglin levels were higher in patients with PCa (median: 7.86 vs. 5.88 pg/mL, P < 0.001). Among patients with baseline tPSA ≤ 10 ng/mL the area under the curve was 0.69 for endoglin. Approximately one-quarter of the patients had serum endoglin < 4.92 ng/mL (sensitivity: 90.3%; specificity: 32.8%), and the probability of PCa varied from 37.7% before testing to 15.2% among those with low endoglin levels [negative predictive value (NPV) = 84.8%]. When restricting the analyses to patients with free/total PSA ratio > 0.25, the probability of cancer was less than 5% among those with serum endoglin < 6.04 ng/mL (sensitivity: 93.8%; specificity: 56.1%), corresponding to a NPV of 95.8%; this could allow sparing approximately 40% of patients from biopsy.

CONCLUSIONS

Serum endoglin may be useful in clinical practice to distinguish between PCa and non-cancer patients among prostatic biopsy candidates.

Identification of a serum biomarker signature associated with metastatic prostate cancer

PURPOSE

Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease.

EXPERIMENTAL DESIGN

In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray.

RESULTS

A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified.

CONCLUSIONS AND CLINICAL RELEVANCE

The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.

SelectMDx and Multiparametric Magnetic Resonance Imaging of the Prostate for Men Undergoing Primary Prostate Biopsy: A Prospective Assessment in a Multi-Institutional Study

Prostate-specific antigen (PSA) testing as the sole indication for prostate biopsy lacks specificity, resulting in overdiagnosis of indolent prostate cancer (PCa) and missing clinically significant PCa (csPCa). SelectMDx is a biomarker-based risk score to assess urinary HOXC6 and DLX1 mRNA expression combined with traditional clinical risk factors. The aim of this prospective multi-institutional study was to evaluate the diagnostic accuracy of SelectMDx and its association with multiparametric magnetic resonance (mpMRI) when predicting PCa in prostate biopsies. Overall, 310 consecutive subjects were included. All patients underwent mpMRI and SelectMDx prior to prostate biopsy. SelectMDx and mpMRI showed sensitivity and specificity of 86.5% vs. 51.9%, and 73.8% vs. 88.3%, respectively, in predicting PCa at biopsy, and 87.1% vs. 61.3%, and 63.7% vs. 83.9%, respectively, in predicting csPCa at biopsy. SelectMDx was revealed to be a good predictor of PCa, while with regards to csPCa detection, it was demonstrated to be less effective, showing results similar to mpMRI. With analysis of strategies assessed to define the best diagnostic strategy to avoid unnecessary biopsy, SelectMDx appeared to be a reliable pathway after an initial negative mpMRI. Thus, biopsy could be proposed for all cases of mpMRI PI-RADS 4-5 score, and to those with Prostate Imaging-Reporting and Data System (PI-RADS) 1-3 score followed by a positive SelectMDx.

Biomarkers in Prostate Cancer Diagnosis: From Current Knowledge to the Role of Metabolomics and Exosomes

Early detection of prostate cancer (PC) is largely carried out using assessment of prostate-specific antigen (PSA) level; yet it cannot reliably discriminate between benign pathologies and clinically significant forms of PC. To overcome the current limitations of PSA, new urinary and serum biomarkers have been developed in recent years. Although several biomarkers have been explored in various scenarios and patient settings, to date, specific guidelines with a high level of evidence on the use of these markers are lacking. Recent advances in metabolomic, genomics, and proteomics have made new potential biomarkers available. A number of studies focused on the characterization of the specific PC metabolic phenotype using different experimental approaches has been recently reported; yet, to date, research on metabolomic application for PC has focused on a small group of metabolites that have been known to be related to the prostate gland. Exosomes are extracellular vesicles that are secreted from all mammalian cells and virtually detected in all bio-fluids, thus allowing their use as tumor biomarkers. Thanks to a general improvement of the technical equipment to analyze exosomes, we are able to obtain reliable quantitative and qualitative information useful for clinical application. Although some pilot clinical investigations have proposed potential PC biomarkers, data are still preliminary and non-conclusive.

Biomarkers for prostate cancer: prostate-specific antigen and beyond

In recent years, several new biomarkers supplementing the role of prostate-specific antigen (PSA) have become available for men with prostate cancer. Although widely used in an ad hoc manner, the role of PSA in screening asymptomatic men for prostate cancer is controversial. Several expert panels, however, have recently recommended limited PSA screening following informed consent in average-risk men, aged 55-69 years. As a screening test for prostate cancer however, PSA has limited specificity and leads to overdiagnosis which in turn results in overtreatment. To increase specificity and reduce the number of unnecessary biopsies, biomarkers such as percent free PSA, prostate health index (PHI) or the 4K score may be used, while Progensa PCA3 may be measured to reduce the number of repeat biopsies in men with a previously negative biopsy. In addition to its role in screening, PSA is also widely used in the management of patients with diagnosed prostate cancer such as in surveillance following diagnosis, monitoring response to therapy and in combination with both clinical and histological criteria in risk stratification for recurrence. For determining aggressiveness and predicting outcome, especially in low- or intermediate-risk men, tissue-based multigene tests such as Decipher, Oncotype DX (Prostate), Prolaris and ProMark, may be used. Emerging therapy predictive biomarkers include AR-V7 for predicting lack of response to specific anti-androgens (enzalutamide, abiraterone), BRAC1/2 mutations for predicting benefit from PARP inhibitor and PORTOS for predicting benefit from radiotherapy. With the increased availability of multiple biomarkers, personalised treatment for men with prostate cancer is finally on the horizon.

4Kscore diagnostic value in patients with high-grade prostate cancer using cutoff values of 7.5% to 10%: A meta-analysis

BACKGROUND

Reported 4Kscore thresholds used to differentiate between patients with and without high-grade prostate cancer (CaP) were variable. Patients with 4Kscore results <7.5% have been proven to be at low risk of carrying high-grade CaP. This study employed a meta-analysis approach in order to assess the diagnostic accuracy of the 4Kscore as a means of detecting high-grade CaP in prostate biopsy samples using cutoff values of 7.5% to 10%.

METHODS

Relevant studies published as of December 2019 were identified via searching PubMed, Embase, and Cochrane Library. Data pertaining to 4Kscore diagnostic accuracy were then extracted from these studies and utilized for the calculation of pooled sensitivity , specificity , diagnostic odds ratio , and area under the curve values relating to high-grade CaP diagnosis.

RESULTS

In total, 9 studies incorporating 1,689 high-grade CaP patients were included in our meta-analysis. Following the exclusion of 1 outlier study, the pooled sensitivity, specificity , diagnostic odds ratio , and area under the curve values for 4Kscore diagnostic accuracy with corresponding 95% confidence intervals (CIs) were 0.90 (95%CI: 0.86-0.92), 0.44 (95%CI: 0.36-0.52), 7 (95%CI: 5-8), and 0.81 (95%CI: 0.77-0.84), respectively.

CONCLUSION

These findings indicate that 4Kscore can be used as a model for the diagnosis of high-grade CaP. However, we detected significant heterogeneity among studies that was not explained by subgroup or meta-regression analysis, thus lowering our confidence in these results. It is therefore essential that future large, well-designed studies be conducted so as to confirm whether the 4Kscore can be used with cutoff values of 7.5% to 10% to reliably detect high-grade CaP.

A Nomogram Based on a Multiparametric Ultrasound Radiomics Model for Discrimination Between Malignant and Benign Prostate Lesions

Objectives

To evaluate the potential of a clinical-based model, a multiparametric ultrasound-based radiomics model, and a clinical-radiomics combined model for predicting prostate cancer (PCa).

Methods

A total of 112 patients with prostate lesions were included in this retrospective study. Among them, 58 patients had no prostate cancer detected by biopsy and 54 patients had prostate cancer. Clinical risk factors related to PCa (age, prostate volume, serum PSA, etc.) were collected in all patients. Prior to surgery, patients received transrectal ultrasound (TRUS), shear-wave elastography (SWE) and TRUS-guided prostate biopsy. We used the five-fold cross-validation method to verify the results of training and validation sets of different models. The images were manually delineated and registered. All modes of ultrasound radiomics were retrieved. Machine learning used the pathology of “12+X” biopsy as a reference to draw the benign and malignant regions of interest (ROI) through the application of LASSO regression. Three models were developed to predict the PCa: a clinical model, a multiparametric ultrasound-based radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared by receiver operating characteristic curve (ROC) analysis and decision curve.

Results

The multiparametric ultrasound radiomics reached area under the curve (AUC) of 0.85 for predicting PCa, meanwhile, AUC of B-mode radiomics and SWE radiomics were 0.74 and 0.80, respectively. Additionally, the clinical-radiomics combined model (AUC: 0.90) achieved greater predictive efficacy than the radiomics model (AUC: 0.85) and clinical model (AUC: 0.84). The decision curve analysis also showed that the combined model had higher net benefits in a wide range of high risk threshold than either the radiomics model or the clinical model.

Conclusions

Clinical-radiomics combined model can improve the accuracy of PCa predictions both in terms of diagnostic performance and clinical net benefit, compared with evaluating only clinical risk factors or radiomics score associated with PCa.

Verification of Harmonization of Serum Total and Free Prostate-Specific Antigen (PSA) Measurements and Implications for Medical Decisions

BACKGROUND

Previous studies have shown that the harmonization of prostate-specific antigen (PSA) assays remained limited even after the introduction of WHO International Standards. This information needs updating for current measuring systems (MS) and reevaluation according to established analytical performance specifications (APS) and the characteristics of antibodies used.

METHODS

Total (tPSA) and free (fPSA) PSA were measured in 135 and 137 native serum samples, respectively, by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM MSs. Passing-Bablok regression and difference plots were used to compare results from each MS to the all-method median values. Agreement among methods was evaluated against APS for bias derived from biological variation of the 2 measurands.

RESULTS

The median interassay CV for tPSA MSs (11.5%; 25-75th percentiles, 9.2-13.4) fulfilled the minimum APS goal for intermethod bias (15.9%), while the interassay CV for fPSA did not [20.4% (25-75th percentiles, 18.4-22.7) vs goal 17.6%]. Considering the all-method median value of each sample as reference, all tPSA MSs exhibited a mean percentage bias within the minimum goal. On the other hand, Alinity (+21.3%) and Access (-24.2%) were out of the minimum bias goal for fPSA, the disagreement explained only in minimal part by the heterogeneity of employed antibodies.

CONCLUSIONS

The harmonization among tPSA MSs is acceptable only when minimum APS are applied and necessitates further improvement. The marked disagreement among fPSA MSs questions the use of fPSA as a second-level test for biopsy referral.

Urine spermine and multivariable Spermine Risk Score predict high-grade prostate cancer

BACKGROUND

To investigate the role of urine spermine and Spermine Risk Score in prediction of high-grade prostate cancer (HGPCa, ISUP grade group ≥2).

METHODS

Nine hundred and five consecutive men with elevated PSA were prospectively recruited from two hospitals. Core analyses focused on consecutive men with PSA 4-20 ng/mL (n = 600). Pre-biopsy urine without prior prostatic massage was analyzed for spermine level with ultra-high performance liquid chromatography with triple quadrupole mass spectrometer (UPLC-MS/MS). The proportions of PCa and HGPCa were compared across different spermine ranges. Logistic regressions were used to form different models, and their performances were compared using area under curve (AUC) and decision curve analysis (DCA).

RESULTS

PCa and HGPCa were diagnosed in 30.8% (185/600) and 17.2% (103/600) men, respectively, and were significantly associated with lower urine spermine levels. Between the lowest and highest quartiles of spermine results, a threefold increase in PCa risk (49.3% vs. 16.7%) and 3.5-fold increase in ISUP grade group ≥2 PCa risk (31.3% vs. 8.7%) were observed. Multivariate analysis showed PSA, prostate volume (PV), digital rectal examination (DRE), and spermine, which were independent predictors for PCa and HGPCa, and a Spermine Risk Score with these factors achieved the highest AUC of 0.78 for PCa and 0.82 for HGPCa. At 90% sensitivity for HGPCa, 36.7% biopsies and 24.4% ISUP grade group 1 diagnoses could have been avoided, with a negative predictive value of 95.4%. DCA revealed net clinical benefit of the Spermine Risk Score. Internal validation with bootstrapping showed good discrimination and calibration.

CONCLUSION

Urine spermine and Spermine Risk Score identified men at higher risk of HGPCa and reduced unnecessary biopsies.

Clinical utility of current biomarkers for prostate cancer detection

Although prostate-specific antigen (PSA) remains the most used test to detect prostate cancer (PCa), the limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. Over the last three decades, a large body of evidence has indicated that PSA screening methods for PCa are problematic, although PSA screening significantly reduces PCa-specific mortality. A number of novel biomarkers have been introduced to overcome these limitations of PSA in the clinical setting. These biomarkers have demonstrated an increased ability to select patients for biopsy and identify men at risk for clinically significant PCa. Although a number of assays require further validation, initial data are promising. Forthcoming results will ultimately determine the clinical utility and commercial availability of these assays. Extensive efforts have recently been made to identify and commercialize novel PCa biomarkers for more effective detection of PCa, either alone or in combination with currently available clinical tools. This review highlights the role of existing and promising serum and urinary biomarkers for the detection and prognostication of PCa before prostate biopsy.

PSA Based Biomarkers, Imagistic Techniques and Combined Tests for a Better Diagnostic of Localized Prostate Cancer

Prostate cancer represents the most encountered urinary malignancy in males over 50 years old, and the second most diagnosed after lung cancer globally. Digital rectal examination and prostatic specific antigen were the long-time standard tools for diagnosis but with a significant risk of overdiagnosis and overtreatment. Magnetic resonance imaging recently entered the diagnosis process, but to this date, there is no specific biomarker that accurately indicates whether to proceed with the prostate biopsy. Research in this area has gone towards this direction, and recently, serum, urine, imagistic, tissue biomarkers, and Risk Calculators promise to help better diagnose and stratify prostate cancer. In order to eliminate the comorbidities that appear along with the diagnosis and treatment of this disease, there is a constant need to implement new diagnostic strategies. Important uro-oncology associations recommend the use of novel biomarkers in the grey area of prostate cancer, to better distinguish the next step in the diagnostic process. Although it is not that simple, they should be integrated according to the clinical policies, and it should be considered that statistical significance does not always equal clinical significance. In this review, we analyzed the contribution of prostate-specific antigen (PSA)-based biomarkers (PHI, PHID, 4Kscore, STHLM3), imagistic techniques (mp-MRI and mp-US), and combined tests in the early diagnosis process of localized prostate cancer.

Effects of replacing PSA with Stockholm3 for diagnosis of clinically significant prostate cancer in a healthcare system - the Stavanger experience

OBJECTIVE

To describe early experience of replacing PSA with Stockholm3 for detection of prostate cancer in primary care.

DESIGN AND METHODS

Longitudinal observations, comparing outcome measures before and after the implementation of Stockholm3.

SETTING

Stavanger region in Norway with about 370,000 inhabitants, 304 general practitioners (GPs) in 97 primary care clinics, and one hospital.

INTERVENTION

GPs were instructed to use Stockholm3 instead of PSA as standard procedure for diagnosis of prostate cancer.

MAIN OUTCOME MEASURES

Proportion of GP clinics that had ordered a Stockholm3 test. Number of men referred to needle biopsy. Distribution of clinically significant prostate cancer (csPC) (Gleason Score ≥7) and clinically non-significant prostate cancer (cnsPC) (Gleason Score 6), in needle biopsies. Estimation of direct healthcare costs.

RESULTS

Stockholm3 was rapidly implemented as 91% (88/97) of the clinics started to use the test within 14 weeks. After including 4784 tested men, the percentage who would have been referred for prostate needle biopsy was 29.0% (1387/4784) if based on PSA level ≥3ng/ml, and 20.8% (995/4784) if based on Stockholm3 Risk Score (p < 0.000001). The proportion of positive biopsies with csPC increased from 42% (98/233) before to 65% (185/285) after the implementation. Correspondingly, the proportion of cnsPC decreased from 58% (135/233) before to 35% (100/285) after the implementation (p < 0.0017). Direct healthcare costs were estimated to be reduced by 23-28% per tested man.

CONCLUSION

Replacing PSA with Stockholm3 for early detection of prostate cancer in primary care is feasible. Implementation of Stockholm3 resulted in reduced number of referrals for needle-biopsy and a higher proportion of clinically significant prostate cancer findings in performed biopsies. Direct healthcare costs decreased. KEY POINTS A change from PSA to Stockholm3 for the diagnosis of prostate cancer in primary care in the Stavanger region in Norway is described and assessed. •Implementation of a new blood-based test for prostate cancer detection in primary care was feasible. A majority of GP clinics started to use the test within three months. •Implementation of the Stockholm3 test was followed by: -a 28% reduction in number of men referred for urological prostate cancer work-up -an increase in the proportion of clinically significant cancer in performed prostate biopsies from 42 to 65% -an estimated reduction in direct health care costs between 23 and 28%.

Prespecified 4-Kallikrein Marker Model at Age 50 or 60 for Early Detection of Lethal Prostate Cancer in a Large Population Based Cohort of Asymptomatic Men Followed for 20 Years

PURPOSE

A prespecified statistical model based on 4 kallikrein markers in blood, commercially available as the 4Kscore®, has been shown to accurately detect high grade (greater than Grade Group 2) prostate cancer in men with moderately elevated prostate specific antigen. We assessed whether the model predicted prostate cancer metastasis or death in men not subject to prostate specific antigen screening.

MATERIALS AND METHODS

The cohort includes 43,692 unscreened prostate cancer-free men from a Swedish population based cohort with low rates of prostate specific antigen screening (Västerbotten Intervention Project). Using cryopreserved blood collected at ages 50 and 60 years from men in this cohort we analyzed the association between prostate specific antigen and other kallikrein marker levels in blood and risk of prostate cancer metastasis or death.

RESULTS

There were 308 with metastases and 172 prostate cancer deaths. Baseline prostate specific antigen was strongly associated with 20-year risk of prostate cancer death (c-index at age 50, 0.859, 95% CI 0.799-0.916; age 60, 0.840, 95% CI 0.799-0.878). Men 60 years old with prostate specific antigen below median (less than 1.2 ng/ml) had 0.4% risk of prostate cancer death at 20 years. Among men with moderately elevated prostate specific antigen (2.0 ng/ml or greater) the 4Kscore markedly improved discrimination (c-index 0.767 vs 0.828 and 0.774 vs 0.862 in men age 50 and 60, respectively). Long-term risk of prostate cancer death or metastasis in men with low 4Kscores was very low.

CONCLUSIONS

Screening should focus on men in top prostate specific antigen quartile at age 60 years. Men with elevated prostate specific antigen but a low 4Kscore can safely be monitored with repeated blood markers in place of immediate biopsy.

Rethinking prostate cancer screening: could MRI be an alternative screening test?

In the past decade rigorous debate has taken place about population-based screening for prostate cancer. Although screening by serum PSA levels can reduce prostate cancer-specific mortality, it is unclear whether the benefits outweigh the risks of false-positive results and overdiagnosis of insignificant prostate cancer, and it is not recommended for population-based screening. MRI screening for prostate cancer has the potential to be analogous to mammography for breast cancer or low-dose CT for lung cancer. A number of potential barriers and technical challenges need to be overcome in order to implement such a programme. We discuss different approaches to MRI screening that could address these challenges, including abbreviated MRI protocols, targeted MRI screening, longer rescreening intervals and a multi-modal screening pathway. These approaches need further investigation, and we propose a phased stepwise research framework to ensure proper evaluation of the use of a fast MRI examination as a screening test for prostate cancer.

All change in the prostate cancer diagnostic pathway

Following detection of high levels of serum prostate-specific antigen, many men are advised to have transrectal ultrasound-guided biopsy in an attempt to locate a cancer. This nontargeted approach lacks accuracy and carries a small risk of potentially life-threatening sepsis. Worse still, it can detect clinically insignificant cancer cells, which are unlikely to be the origin of advanced-stage disease. The detection of these indolent cancer cells has led to overdiagnosis, one of the major problems of contemporary medicine, whereby many men with clinically insignificant disease are advised to undergo unnecessary radical surgery or radiotherapy. Advances in imaging and biomarker discovery have led to a revolution in prostate cancer diagnosis, and nontargeted prostate biopsies should become obsolete. In this Perspective article, we describe the current diagnostic pathway for prostate cancer, which relies on nontargeted biopsies, and the problems linked to this pathway. We then discuss the utility of prebiopsy multiparametric MRI and novel tumour markers. Finally, we comment on how the incorporation of these advances into a new diagnostic pathway will affect the current risk-stratification system and explore future challenges.

Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI

Background

To evaluate the potential of clinical-based model, a biparametric MRI-based radiomics model and a clinical-radiomics combined model for predicting clinically significant prostate cancer (PCa).

Methods

In total, 381 patients with clinically suspicious PCa were included in this retrospective study; of those, 199 patients did not have PCa upon biopsy, while 182 patients had PCa. All patients underwent 3.0-T MRI examinations with the same acquisition parameters, and clinical risk factors associated with PCa (age, prostate volume, serum PSA, etc.) were collected. We randomly stratified the training and test sets using a 6:4 ratio. The radiomic features included gradient-based histogram features, grey-level co-occurrence matrix (GLCM), run-length matrix (RLM), and grey-level size zone matrix (GLSZM). Three models were developed using multivariate logistic regression analysis to predict clinically significant PCa: a clinical model, a radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared via receiver operating characteristic (ROC) curve analysis and decision curves, respectively.

Results

Both the radiomics model (AUC: 0.98) and the clinical-radiomics combined model (AUC: 0.98) achieved greater predictive efficacy than the clinical model (AUC: 0.79). The decision curve analysis also showed that the radiomics model and combined model had higher net benefits than the clinical model.

Conclusions

Compared with the evaluation of clinical risk factors associated with PCa only, the radiomics-based machine learning model can improve the predictive accuracy for clinically significant PCa, in terms of both diagnostic performance and clinical net benefit.

Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management

The accurate identification and stratified treatment of clinically significant early-stage prostate cancer have been ongoing concerns since the outcomes of large international prostate cancer screening trials were reported. The controversy surrounding clinical and cost benefits of prostate cancer screening has highlighted the lack of strategies for discriminating high-risk disease (that requires early treatment) from low-risk disease (that could be managed using watchful waiting or active surveillance). Advances in molecular subtyping and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostate cancer molecular taxonomy into clinically meaningful and treatable subtypes. Furthermore, the presence of intertumoural and intratumoural heterogeneity in prostate cancer warrants the development of novel nanodiagnostic technologies to identify clinically significant prostate cancer in a rapid, cost-effective and accurate manner. Circulating and urinary next-generation prostate cancer biomarkers for disease molecular subtyping and the newest complementary nanodiagnostic platforms for enhanced biomarker detection are promising tools for precision prostate cancer management. However, challenges in merging both aspects and clinical translation still need to be overcome.

A novel nomogram combined PIRADS v2 and neutrophil-to-lymphocyte ratio to predict the risk of clinically significant prostate cancer in men with PSA < 10 ng/ml at first biopsy

OBJECTIVE

To determine whether Prostate Imaging-Reporting and Data System version 2 (PIRADS v2) and neutrophil-to-lymphocyte ratio(NLR) improve the detection of clinically significant prostate cancer(csCaP) in men with prostate-specific antigen (PSA) <10 ng/ml at first biopsy.

METHODS

Univariable and multivariable binary logistic regression analysis were used to screen for independent risk factors of csCaP. The multivariable model based on the risk factors was to build the nomogram predicting csCaP and assessed by receiver operator characteristic curve analysis, calibration plot, and decision curve analysis.

RESULTS

This retrospective study included 335 men with PSA < 10 ng/ml who underwent initial biopsy. A total of 78 (23.3%) men had csCaP. The nomogram was built based on the multivariable model including age, digital rectal examination, free prostate-specific antigen, PIRADS v2, and NLR. It had high area under the curve of 0.876 and was well calibrated in internal validation. Decision curve analysis also demonstrated that it would improve the prediction of csCaP.

CONCLUSION

PIRADS v2 and NLR improve the detection of csCaP in men with PSA < 10 ng/ml at first biopsy. Due to lack of external validation, relatively small cohort and homogenous population, the study has several limitations. Despite of this, the nomogram based on our study is a promising tool for patients to understand their risk of csCaP and for urologists to make clinical decisions.

Performance of the 4Kscore Test in Plasma and Serum and Stability of the Component Analytes in Clinical Samples

BACKGROUND

The 4Kscore Test determines a personalized risk score for aggressive prostate cancer by combining the blood sample measurements of total prostate-specific antigen (tPSA), free PSA (fPSA), intact PSA (iPSA), and human kallikrein-related peptidase 2 (hK2) with patient clinical information to generate the patient risk's score; thus, accuracy and precision of the 4Kscore depend on the reliability of these measurements. Although tPSA and fPSA are measured on a Food and Drug Administration (FDA)-approved platform, the performance of the iPSA and hK2 assays in the clinical setting has not previously been reported.

METHODS

Analytical performance was determined for the iPSA and hK2 assays in both serum and EDTA plasma, according to Clinical and Laboratory Standards Institute guidelines. Equivalence of the 4Kscore in both sample matrices was demonstrated in a 353-patient clinical cohort, and the stability of endogenous iPSA and hK2 for at least 3 days was demonstrated in a smaller subset.

RESULTS

Intralaboratory and interlaboratory precision of the iPSA and hK2 assays in both matrices was comparable with that of FDA-approved tPSA and fPSA assays (<18% for iPSA; <8% for hK2). The picogram per milliliter sensitivity and wide dynamic range of the iPSA and hK2 assays allowed for accurate measurements in the target population. The 4Kscore generated in either matrix up to 3 days after collection is equivalent to that measured within 24 h of collection (Passing-Bablok slope 95% CI: plasma, 0.999-1.034; serum, 0.997-1.040).

CONCLUSIONS

The robust performance of component assays and reliable stability of the endogenous analytes in clinical samples proven here ensures an accurate 4Kscore Test result.

LacdiNAc-Glycosylated Prostate-specific Antigen Density is a Potential Biomarker of Prostate Cancer

BACKGROUND

Serum LacdiNAc-glycosylated prostate-specific antigen (LDN-PSA) and LDN-PSA density together with PSA and PSA density (PSAD) were measured as a diagnostic tool for prostate cancer (PCa).

PATIENTS AND METHODS

We included 150 patients with PCa without hormonal therapy and 41 patients without PCa obtained from the Kyoto University Hospital between 2012 and 2017. LDN-PSA levels were measured through a WFA-anti-PSA antibody sandwich immunoassay using a highly sensitive surface plasmon field-enhanced fluorescence spectroscopy (SPFS) system. Diagnostic performance of serum LDN-PSA and LDN-PSAD was evaluated by measuring the area under the receiver-operating characteristic curve (AUC).

RESULTS

The AUCs of LDN-PSA, LDN-PSAD, and PSAD levels (0.780, 0.848, and 0.835, respectively) detected in patients with PCa were significantly higher (P = .0001, P < .0001, and P < .0001, respectively) than that of PSA (0.590). Moreover, among 143 patients with PCa who received radical prostatectomy (RP), the AUCs of LDN-PSA, LDN-PSAD, and PSAD levels (0.750, 0.812, and 0.769, respectively) detected in patients with a pathologic Gleason grade group ≥ 2 were significantly higher (P = .0170, P = .0028, and P = .0003, respectively) than that of PSA (0.578). In the group comprising 35 patients who received RP with a Gleason grade group 1-graded biopsy, the LDN-PSA, LDN-PSAD, and PSAD levels were significantly different (P = .0097, P = .0024, and P = .0312, respectively). However, PSA alone could not discriminate cases with adverse features (P = .454).

CONCLUSIONS

LDN-PSAD is a potential marker for detecting PCa and selecting candidates for RP.

Prostate-specific markers to identify rare prostate cancer cells in liquid biopsies

Despite improvements in early detection and advances in treatment, patients with prostate cancer continue to die from their disease. Minimal residual disease after primary definitive treatment can lead to relapse and distant metastases, and increasing evidence suggests that circulating tumour cells (CTCs) and bone marrow-derived disseminated tumour cells (BM-DTCs) can offer clinically relevant biological insights into prostate cancer dissemination and metastasis. Using epithelial markers to accurately detect CTCs and BM-DTCs is associated with difficulties, and prostate-specific markers are needed for the detection of these cells using rare cell assays. Putative prostate-specific markers have been identified, and an optimized strategy for staining rare cancer cells from liquid biopsies using these markers is required. The ideal prostate-specific marker will be expressed on every CTC or BM-DTC throughout disease progression (giving high sensitivity) and will not be expressed on non-prostate-cancer cells in the sample (giving high specificity). Some markers might not be specific enough to the prostate to be used as individual markers of prostate cancer cells, whereas others could be truly prostate-specific and would make ideal markers for use in rare cell assays. The goal of future studies is to use sensitive and specific prostate markers to consistently and reliably identify rare cancer cells.

The Stockholm3 blood-test predicts clinically-significant cancer on biopsy: independent validation in a multi-center community cohort

BACKGROUND

Several blood-based tests have been suggested to improve prostate cancer testing. The Stockholm3 test has been shown to reduce the number of prostate biopsies, to decrease detection of low-grade cancer and to maintain the detection rate of ISUP Gleason Group (GG) ≥ 2 cancer in a screening-by-invitation setting. We aimed to validate the performance of the Stockholm3 test in an independent, clinical practice cohort.

METHODS

The study-population consisted of 533 men in ages 45-75 without previous diagnosis of prostate cancer scheduled for prostate biopsy at any of three centers in Norway and Sweden. Blood samples for Stockholm3 analysis were drawn prior to systematic prostate biopsies. Clinically significant prostate cancer was defined as any finding of ISUP Grade Group (GG) 2 or higher. We calculated area under the curve (AUC) for predicting prostate cancer at biopsy and calculated. Models including PSA and PSA-density (PSA/prostate volume) were compared to a model including also clinical information, protein levels and single nucleotide polymorphisms (SNP).

RESULTS

263 of 533 (49%) participants were diagnosed with prostate cancer. 162 men had prostate cancer with GG ≥ 2. The Stockholm3 test discriminated better for GG ≥ 2 prostate cancer than PSA in combination with PSA-density AUC 8.9 (95% CI 82.7-89.2) and AUC 74.8 (95% CI 70.3-79.3). Using a Stockholm3 cut-off of 10% risk of GG ≥ 2 cancer, 38% of the biopsy procedures were saved, however delaying diagnosis for 6% (n = 10) of men with GG ≥ 2 cancer. Using PSA-density 0.1 as cut-off for biopsy saved 35% of biopsies, delaying diagnosis for 16% (n = 26) of men with GG ≥ 2 cancer.

CONCLUSION

A prediction model including clinical information, protein levels and SNPs was independently validated in a clinical practice cohort and reduces the number of un-necessary biopsies while delaying diagnosis for a limited number of men.

Development and internal validation of PI-RADs v2-based model for clinically significant prostate cancer

BACKGROUND

Our objective is to build a model based on Prostate Imaging Reporting and Data System version 2 (PI-RADs v2) and assess its accuracy by internal validation.

METHODS

Patients who took prostate biopsy from 2014 to 2015 were retrospectively collected to compose training cohort according to the inclusion criteria and patients in 2016 composing validation cohort. Diagnostic performance was evaluated by analyzing the area under the curve (AUC), calibration curves, and decision curves.

RESULTS

Of the 441 patients involved, the clinically significant prostate cancer (csPCa) detection rate were 40.6% (114/281) and 43.8% (70/160) in the training and validation cohort, respectively. Meanwhile, PCa detection rate were 50.2% (141/281) and 53.8% (86/160). Age, prostate-specific antigen density (PSAD)*10 and PI-RADs v2 score composed the model for PCa (model 1) and csPCa (model 2). The area under the curve of models 1 and 2 was 0.870 (95% CI 0.827-0.912) and 0.753 (95% CI 0.717-0.828) in the training cohort, while 0.845 (95% CI 0.786-0.904) and 0.834 (95% CI 0.787-0.882) in the validation cohort. Both models illustrated good calibration, and decision curve analyses showed good performance in predicting PCa or csPCa when the threshold was 0.35 or above.

CONCLUSIONS

The model based on age, PSAD*10 and PI-RADs v2 score showed internally validated high predictive value for both PCa and csPCa. It could be used to improve the diagnostic performance of suspicious PCa.

Emerging biomarkers in the diagnosis of prostate cancer

Prostate cancer (PCa) is the second most common cancer in men worldwide. A large proportion of PCa are latent, never destined to progress or affect the patients’ life. It is of utmost importance to identify which PCa are destined to progress and which would benefit from an early radical treatment. Prostate-specific antigen (PSA) remains the most used test to detect PCa. Its limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. New PCa biomarkers have been proposed to improve the accuracy of PSA in the management of early PCa. Commercially available biomarkers such as PCA3 score, Prostate Health Index (PHI), and the four-kallikrein panel are used with the purpose of reducing the number of unnecessary biopsies and providing information related to the aggressiveness of the tumor. The relationship with PCa aggressiveness seems to be confirmed by PHI and the four-kallikrein panel, but not by the PCA3 score. In this review, we also summarize new promising biomarkers, such as PSA glycoforms, TMPRSS2:ERG fusion gene, microRNAs, circulating tumor cells, androgen receptor variants, and PTEN gene. All these emerging biomarkers could change the management of early PCa, offering more accurate results than PSA. Nonetheless, large prospective studies comparing these new biomarkers among them are required to know their real value in PCa detection and prognosis.