Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

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.

A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry

There is a significant unmet need for clinical reflex tests that increase the specificity of prostate-specific antigen blood testing, the longstanding but imperfect tool for prostate cancer diagnosis. Towards this endpoint, we present the results from a discovery study that identifies new prostate-specific antigen reflex markers in a large-scale patient serum cohort using differentiating technologies for deep proteomic interrogation. We detect known prostate cancer blood markers as well as novel candidates. Through bioinformatic pathway enrichment and network analysis, we reveal associations of differentially abundant proteins with cytoskeletal, metabolic, and ribosomal activities, all of which have been previously associated with prostate cancer progression. Additionally, optimized machine learning classifier analysis reveals proteomic signatures capable of detecting the disease prior to biopsy, performing on par with an accepted clinical risk calculator benchmark.

Risk calculators for the detection of prostate cancer: a systematic review

BACKGROUND

Prostate cancer (PCa) (early) detection poses significant challenges, including unnecessary testing and the risk of potential overdiagnosis. The European Association of Urology therefore suggests an individual risk-adapted approach, incorporating risk calculators (RCs) into the PCa detection pathway. In the context of 'The PRostate Cancer Awareness and Initiative for Screening in the European Union' (PRAISE-U) project ( https://uroweb.org/praise-u ), we aim to provide an overview of the currently available clinical RCs applicable in an early PCa detection algorithm.

METHODS

We performed a systematic review to identify RCs predicting detection of clinically significant PCa at biopsy. A search was performed in the databases Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar for publications between January 2010 and July 2023. We retrieved relevant literature by using the terms "prostate cancer", "screening/diagnosis" and "predictive model". Inclusion criteria included systematic reviews, meta-analyses, and clinical trials. Exclusion criteria applied to studies involving pre-targeted high-risk populations, diagnosed PCa patients, or a sample sizes under 50 men.

RESULTS

We identified 6474 articles, of which 140 were included after screening abstracts and full texts. In total, we identified 96 unique RCs. Among these, 45 underwent external validation, with 28 validated in multiple cohorts. Of the externally validated RCs, 17 are based on clinical factors, 19 incorporate clinical factors along with MRI details, 4 were based on blood biomarkers alone or in combination with clinical factors, and 5 included urinary biomarkers. The median AUC of externally validated RCs ranged from 0.63 to 0.93.

CONCLUSIONS

This systematic review offers an extensive analysis of currently available RCs, their variable utilization, and performance within validation cohorts. RCs have consistently demonstrated their capacity to mitigate the limitations associated with early detection and have been integrated into modern practice and screening trials. Nevertheless, the lack of external validation data raises concerns about numerous RCs, and it is crucial to factor in this omission when evaluating whether a specific RC is applicable to one's target population.

Lectin-nanoparticle concept for free PSA glycovariant providing superior cancer specificity

BACKGROUND

Using lectins to target cancer-associated modifications of PSA glycostructure for identification of clinically significant prostate cancers, e.g., Gleason score (GS) ≥ 7, from benign and indolent cancers (GS 6), is highly promising yet technically challenging. From previous findings to quantify increased PSA fucosylation in urine, we set out to construct a robust, specific test concept suitable for plasma samples.

METHODS

Macrophage galactose-binding lectin (MGL) coupled to 100 nm Eu3 + -nanoparticles was used to probe PSA captured from cancer cell lines, seminal plasma, and plasma samples from 249 patients with a clinical suspicion of prostate cancer onto 3 mm dense spots of free PSA antibody fab fragments. Results were compared to four kallikrein tests: tPSA, fPSA, iPSA and hK2.

RESULTS

The fPSAMGLglycovariant provided superior discrimination of the GS ≥ 7 and benign + GS 6 groups (p 0.0003) compared to fPSA (NS). The corresponding AUC in ROC analysis was 0.70 compared to 0.66 for tPSA. In contrast to all four kallikrein tests, the fPSAMGLGV was independent of prostate gland volume. Using a logistic regression analysis the fPSAMGLGV significantly improved on the four-kallikrein model.

CONCLUSIONS

Due to Eu-nanoparticles and a dense fPSA capture spot, the fPSAMGL glycovariant identifies an fPSA subform with the highest cancer specificity compared to the four conventional kallikreins.

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.

The Capio Prostate Cancer Center Model for Prostate Cancer Diagnostics-Real-world Evidence from 2018 to 2022

Background

The Capio Prostate Cancer Center (Capio PCC) in Stockholm, Sweden, adopts a comprehensive diagnostic approach, utilizing prostate-specific antigen (PSA), Stockholm3, and magnetic resonance imaging (MRI) for prostate cancer risk assessment, followed by targeted and systematic biopsies for high-risk cases.

Objective

This study aims to elucidate the clinical process and real-world outcomes of the Capio PCC model for prostate cancer diagnosis at Capio S:t Göran Hospital.

Design setting and participants

Between 2018 and 2022, a cohort of 12 406 men aged 45-75 yr underwent prostate cancer testing, adhering to Capio PCC's structured diagnostic protocol.

Outcome measurements and statistical analysis

We provide a comprehensive description of the Capio PCC model and present results from its implementation, including assessments of PSA, Stockholm3, MRI scans, and biopsies. A comparative analysis is conducted between the diagnostic outcomes obtained at Capio PCC and those obtained at other regions in Sweden.

Results and limitations

The median participant age was 61 yr (interquartile range [IQR]: 55-67), with PSA levels at 1.6 ng/ml (IQR: 0.8-3.3) and Stockholm3 scores at 4 (IQR: 3-11). Among 1064 men (8.6%) undergoing biopsies, 611 (57% of biopsied) were diagnosed with International Society of Urological Pathology grade ≥ 2 cancer. Notably, employing a Stockholm3 ≥ 15 cutoff for biopsy, in lieu of PSA ≥ 3 ng/ml, reduced biopsy recommendations by 43%. For men with PSA levels between 1.5 and 2.9 ng/ml, 360 (12%) exhibited Stockholm3 scores of ≥ 15, with 72 (56% of biopsied) diagnosed with clinically significant prostate cancer. A comparative analysis with national Swedish prostate cancer detection data indicated that the Capio PCC model (vs Sweden) revealed a distribution of 14% (vs 25%) low-risk, 59% (vs 42%) intermediate-risk, and 26% (vs 30%) high-risk and advanced cancers.

Conclusions

This study underscores the effectiveness of the protocol-driven diagnostic process at Capio PCC, enabling earlier detection of intermediate-risk prostate cancer and reducing the need for MRI assessments compared with standard prostate cancer care in Sweden.

Patient summary

At the Capio Prostate Cancer Center, a novel diagnostic approach incorporating prostate-specific antigen, Stockholm3, magnetic resonance imaging, and targeted biopsies has been implemented to enhance prostate cancer testing and diagnosis in Stockholm, Sweden.

BioPrev-C - development and validation of a contemporary prostate cancer risk calculator

Objectives

To develop a novel biopsy prostate cancer (PCa) prevention calculator (BioPrev-C) using data from a prospective cohort all undergoing mpMRI targeted and transperineal template saturation biopsy.

Materials and methods

Data of all men who underwent prostate biopsy in our academic tertiary care center between 11/2016 and 10/2019 was prospectively collected. We developed a clinical prediction model for the detection of high-grade PCa (Gleason score ≥7) based on a multivariable logistic regression model incorporating age, PSA, prostate volume, digital rectal examination, family history, previous negative biopsy, 5-alpha-reductase inhibitor use and MRI PI-RADS score. BioPrev-C performance was externally validated in another prospective Swiss cohort and compared with two other PCa risk-calculators (SWOP-RC and PBCG-RC).

Results

Of 391 men in the development cohort, 157 (40.2%) were diagnosed with high-grade PCa. Validation of the BioPrev C revealed good discrimination with an area under the curve for high-grade PCa of 0.88 (95% Confidence Interval 0.82-0.93), which was higher compared to the other two risk calculators (0.71 for PBCG and 0.84 for SWOP). The BioPrev-C revealed good calibration in the low-risk range (0 - 0.25) and moderate overestimation in the intermediate risk range (0.25 - 0.75). The PBCG-RC showed good calibration and the SWOP-RC constant underestimation of high-grade PCa over the whole prediction range. Decision curve analyses revealed a clinical net benefit for the BioPrev-C at a clinical meaningful threshold probability range (≥4%), whereas PBCG and SWOP calculators only showed clinical net benefit above a 30% threshold probability.

Conclusion

BiopPrev-C is a novel contemporary risk calculator for the prediction of high-grade PCa. External validation of the BioPrev-C revealed relevant clinical benefit, which was superior compared to other well-known risk calculators. The BioPrev-C has the potential to significantly and safely reduce the number of men who should undergo a prostate biopsy.

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.

Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men

PURPOSE

To develop nomograms that predict the detection of clinically significant prostate cancer (csPCa, defined as ≥GG2 [Grade Group 2]) at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features.

MATERIALS AND METHODS

Nomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with prostate specific antigen (PSA) of 2-20 ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of csPCa and high-grade prostate cancer (defined as ≥GG3 prostate cancer). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with total PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022.

RESULTS

1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥GG2 PCa, and 271 (26.3%) were found to have ≥GG3 PCa. Age, race, highest PIRADS score, prostate health index when available, % free PSA when available, and PSA density were significant predictors of ≥GG2 and ≥GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥0.885 in the training cohort and ≥0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa.

CONCLUSIONS

Here we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2-20 ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.

Let’s Go 3D! New Generation of Models for Evaluating Drug Response and Resistance in Prostate Cancer

Prostate cancer (PC) is the third most frequently diagnosed cancer worldwide and the second most frequent in men. Several risk factors can contribute to the development of PC, and those include age, family history, and specific genetic mutations. So far, drug testing in PC, as well as in cancer research in general, has been performed on 2D cell cultures. This is mainly because of the vast benefits these models provide, including simplicity and cost effectiveness. However, it is now known that these models are exposed to much higher stiffness; lose physiological extracellular matrix on artificial plastic surfaces; and show changes in differentiation, polarization, and cell–cell communication. This leads to the loss of crucial cellular signaling pathways and changes in cell responses to stimuli when compared to in vivo conditions. Here, we emphasize the importance of a diverse collection of 3D PC models and their benefits over 2D models in drug discovery and screening from the studies done so far, outlining their benefits and limitations. We highlight the differences between the diverse types of 3D models, with the focus on tumor–stroma interactions, cell populations, and extracellular matrix composition, and we summarize various standard and novel therapies tested on 3D models of PC for the purpose of raising awareness of the possibilities for a personalized approach in PC therapy.

Do PHI and PHI density improve detection of clinically significant prostate cancer only in the PSA gray zone?

OBJECTIVES

Prostate health index (PHI) is a predictive biomarker of positive prostate biopsy. The majority of evidence refers to its use in the PSA gray zone (4-10 ng/mL) and negative digital rectal exam (DRE). We aim to evaluate and compare the predictive accuracy of PHI and PHI density (PHId) with PSA, percentage of free PSA and PSA density, in a wider range of patients for the detection of clinically significant prostate cancer (csPCa).

METHODS

Multicenter prospective study that included patients suspicious of harboring prostate cancer. Non-probabilistic convenience sampling, where men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate and compare diagnostic accuracy AUC and decision curve analysis (DCA) were calculated. All these procedures were performed for the overall sample and the following subsamples: PSA < 4 ng/ml; PSA 4-10 ng/ml; PSA 4-10 ng/ml plus negative DRE and PSA > 10 ng/ml.

RESULTS

Among the 559 men included, 194 (34.7%) were diagnosed of csPCa. PHI and PHId outperfomed PSA in all subgroups. PHI best diagnostic performance was found in PSA 4-10 ng/ml with negative DRE (sensitivity 93.33, NPV 96.04). Regarding AUC, significant differences were found between PHId and PSA in the subgroup of PSA 4-10 ng/ml, whatever DRE status. In DCA, PHI density shows the highest net benefit.

CONCLUSIONS

PHI and PHId outperfom PSA in csPCa detection, not only in the PSA grey zone with negative DRE, but also in a wider range of PSA values. There is an urgent need of prospective studies to established a validated threshold and its incorporation in risk calculators.

A prostate biopsy risk calculator based on MRI: development and comparison of the Prospective Loyola University multiparametric MRI (PLUM) and Prostate Biopsy Collaborative Group (PBCG) risk calculators

OBJECTIVES

To develop and validate a prostate cancer (PCa) risk calculator (RC) incorporating multiparametric magnetic resonance imaging (mpMRI) and to compare its performance with that of the Prostate Biopsy Collaborative Group (PBCG) RC.

PATIENTS AND METHODS

Men without a PCa diagnosis receiving mpMRI before biopsy in the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (2015-2020) were included. Data from a separate institution were used for external validation. The primary outcome was diagnosis of no cancer, grade group (GG)1 PCa, and clinically significant (cs)PCa (≥GG2). Binary logistic regression was used to explore standard clinical and mpMRI variables (prostate volume, Prostate Imaging-Reporting Data System [PI-RADS] version 2.0 lesions) with the final PLUM RC, based on a multinomial logistic regression model. Receiver-operating characteristic curve, calibration curves, and decision-curve analysis were evaluated in the training and validation cohorts.

RESULTS

A total of 1010 patients were included for development (N = 674 training [47.8% PCa, 30.9% csPCa], N = 336 internal validation) and 371 for external validation. The PLUM RC outperformed the PBCG RC in the training (area under the curve [AUC] 85.9% vs 66.0%; P < 0.001), internal validation (AUC 88.2% vs 67.8%; P < 0.001) and external validation (AUC 83.9% vs 69.4%; P < 0.001) cohorts for csPCa detection. The PBCG RC was prone to overprediction while the PLUM RC was well calibrated. At a threshold probability of 15%, the PLUM RC vs the PBCG RC could avoid 13.8 vs 2.7 biopsies per 100 patients without missing any csPCa. At a cost level of missing 7.5% of csPCa, the PLUM RC could have avoided 41.0% (566/1381) of biopsies compared to 19.1% (264/1381) for the PBCG RC. The PLUM RC compared favourably with the Stanford Prostate Cancer Calculator (SPCC; AUC 84.1% vs 81.1%; P = 0.002) and the MRI-European Randomized Study of Screening for Prostate Cancer (ERSPC) RC (AUC 84.5% vs 82.6%; P = 0.05).

CONCLUSIONS

The mpMRI-based PLUM RC significantly outperformed the PBCG RC and compared favourably with other mpMRI-based RCs. A large proportion of biopsies could be avoided using the PLUM RC in shared decision making while maintaining optimal detection of csPCa.

Molecular Biomarkers for the Detection of Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis

Context

Prostate cancer (PCa) is the second most common type of cancer in men. Individualized risk stratification is crucial to adjust decision-making. A variety of molecular biomarkers have been developed in order to identify patients at risk of clinically significant PCa (csPCa) defined by the most common PCa risk stratification systems.

Objective

The present study aims to examine the effectiveness (diagnostic accuracy) of blood or urine-based PCa biomarkers to identify patients at high risk of csPCa.

Evidence acquisition

A systematic review of the literature was conducted. Medline and EMBASE were searched from inception to March 2021. Randomized or nonrandomized clinical trials, and cohort and case-control studies were eligible for inclusion. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Pooled estimates of sensitivity, specificity, and area under the curve were obtained.

Evidence synthesis

Sixty-five studies (N = 34 287) were included. Not all studies included prostate-specific antigen-selected patients. The pooled data showed that the Prostate Health Index (PHI), with any cutoff point between 15 and 30, had sensitivity of 0.95-1.00 and specificity of 0.14-0.33 for csPCa detection. The pooled estimates for SelectMDx test sensitivity and specificity were 0.84 and 0.49, respectively.

Conclusions

The PHI test has a high diagnostic accuracy rate for csPCa detection, and its incorporation in the diagnostic process could reduce unnecessary biopsies. However, there is a lack of evidence on patient-important outcomes and thus more research is needed.

Patient summary

It has been possible to verify that the application of biomarkers could help detect prostate cancer (PCa) patients with a higher risk of poorer evolution. The Prostate Health Index shows an ability to identify 95-100 for every 100 patients suffering from clinically significant PCa who take the test, preventing unnecessary biopsies in 14-33% of men without PCa or insignificant PCa.

The Prostate Health Index and multi-parametric MRI improve diagnostic accuracy of detecting prostate cancer in Asian populations

PURPOSE

The aim of this study was to evaluate the effectiveness of the Prostate Health Index (PHI) and prostate multi-parametric magnetic resonance imaging (mpMRI) in predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) during initial prostate biopsy.

MATERIALS AND METHODS

In total, 343 patients underwent initial prostate biopsy and were screened by use of PHI and prostate-specific antigen (PSA) levels between April 2019 and July 2021. A subgroup of 232 patients also underwent prostate mpMRI. Logistic regression analysis was performed to evaluate the accuracies of PSA, PHI, and mpMRI as predictors of PCa or csPCa. These predictive accuracies were quantified by using the area under the receiver operating characteristic curve. The different predictive models were compared using the DeLong test.

RESULTS

Logistic regression showed that age, PSA, PHI, and prostate volume were significant predictors of both PCa and csPCa. In the mpMRI subgroup, age, PSA level, PHI, prostate volume, and mpMRI were predictors of both PCa and csPCa. The PHI (area under the curve [AUC]=0.693) was superior to the PSA level (AUC=0.615) as a predictor of PCa (p=0.038). Combining PHI and mpMRI showed the most accurate prediction of both PCa and csPCa (AUC=0.833, 0.881, respectively).

CONCLUSIONS

The most accurate prediction of both PCa and csPCa can be performed by combining PHI and mpMRI. In the absence of mpMRI, PHI is superior to PSA alone as a predictor of PCa, and adding PHI to PSA can increase the detection rate of both PCa and csPCa.

New strategy for the identification of prostate cancer: The combination of Proclarix and the prostate health index

OBJECTIVES

Prostate health index (PHI) and, more recently, Proclarix have been proposed as serum biomarkers for prostate cancer (PCa). In this study, we aimed to evaluate Proclarix and PHI for predicting clinically significant prostate cancer (csPCa).

PATIENTS AND METHODS

Proclarix and PHI were measured using samples of 344 men from two different centers. All patients underwent prostate biopsy, and among those, 188 men with PCa on biopsy had an additional radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/ml. Evaluation of area under the curve (AUC) and performance at predefined cut-offs of Proclarix and PHI risk scores as well as the linear combination thereof was performed to predict csPCa. PSA density was used as an independent comparator.

RESULTS

The cohort median age and PSA were 65 (interquartile range [IQR]: 60-71) and 5.6 (IQR: 4.3-7.2) ng/ml, respectively. CsPCa was diagnosed in 161 (47%) men based on the RP specimen. ROC analysis showed that Proclarix and PHI accurately predicted csPCa with no significant difference (AUC of 0.79 and 0.76, p = 0.378) but significantly better when compared to PSA density (AUC of 0.66, p < 0.001). When using specific cut-offs, Proclarix (cut-off 10) revealed higher specificity and positive predictive value than PHI (cut-off 27) at similar sensitivities. The combination of Proclarix and PHI provided a significant increase in the AUC (p ≤ 0.007) compared to the individual tests alone and the highest clinical benefit was achieved.

CONCLUSION

Results of this study show that both Proclarix and PHI accurately detect the presence of csPCa. The model combining Proclarix and PHI revealed the synergistic effect and improved the diagnostic performance of the individual tests.

Value of PHI and PHID in the detection of intermediate- and high-risk prostate cancer

BACKGROUND AND AIMS

PSA testing practice results in a large number of unnecessary prostate biopsies and the overdiagnosis of clinically insignificant prostate cancer (PCa). The aim of our study was to evaluate the value of PHI and PHID for the detection of PCa.

MATERIALS AND METHODS

We measured tPSA, fPSA and p2PSA in 455 patients scheduled for biopsy, including 243 patients with PCa. D'Amico criteria were used to classify these patients in three groups related to risk of progression. Intermediate- and high-risk PCa were considered as aggressive PCa.

RESULTS

The best area under the curve (AUC) value obtained in the detection of aggressive PCa was achieved for PHI and PHID (0.766 and 0.760, respectively). We found a relationship of the performance of by these tests with the calculated prostate volume or the estimated prostate size by digital rectal exam, obtaining the higher AUC in patients with a small prostate. Thus, the AUC for PHI was 0,843 for patients with small calculated prostate volume and 0,817 for patients with small estimated prostate size.

CONCLUSIONS

Our results underline that PHI and PHID outperforms the efficacy obtained with tPSA and %fPSA. Substantial differences in their value in relation to prostate volume were found.

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.

Blood and urine biomarkers in prostate cancer: Are we ready for reflex testing in men with an elevated prostate-specific antigen?

Objective

There is no consensus on the role of biomarkers in determining the utility of prostate biopsy in men with elevated prostate-specific antigen (PSA). There are numerous biomarkers such as prostate health index, 4Kscore, prostate cancer antigen 3, ExoDX, SelectMDx, and Mi-Prostate Score that may be useful in this decision-making process. However, it is unclear whether any of these tests are accurate and cost-effective enough to warrant being a widespread reflex test following an elevated PSA. Our goal was to report on the clinical utility of these blood and urine biomarkers in prostate cancer screening.

Methods

We performed a systematic review of studies published between January 2000 and October 2020 to report the available parameters and cost-effectiveness of the aforementioned diagnostic tests. We focus on the negative predictive value, the area under the curve, and the decision curve analysis in comparing reflexive tests due to their relevance in evaluating diagnostic screening tests.

Results

Overall, the biomarkers are roughly equivalent in predictive accuracy. Each test has additional clinical utility to the current diagnostic standard of care, but the added benefit is not substantial to justify using the test reflexively after an elevated PSA.

Conclusions

Our findings suggest these biomarkers should not be used in binary fashion and should be understood in the context of pre-existing risk predictors, patient's ethnicity, cost of the test, patient life-expectancy, and patient goals. There are more recent diagnostic tools such as multi-parametric magnetic resonance imaging, polygenic single-nucleotide panels, IsoPSA, and miR Sentinel tests that are promising in the realm of prostate cancer screening and need to be investigated further to be considered a consensus reflexive test in the setting of prostate cancer screening.

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.

Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.

Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892–0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935–0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1–3 cancer subgroups.

Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

Prostate Cancer Risk Calculators for Healthy Populations: Systematic Review

Background

Screening for prostate cancer has long been a debated, complex topic. The use of risk calculators for prostate cancer is recommended for determining patients’ individual risk of cancer and the subsequent need for a prostate biopsy. These tools could lead to better discrimination of patients in need of invasive diagnostic procedures and optimized allocation of health care resources

Objective

The goal of the research was to systematically review available literature on the performance of current prostate cancer risk calculators in healthy populations by comparing the relative impact of individual items on different cohorts and on the models’ overall performance.

Methods

We performed a systematic review of available prostate cancer risk calculators targeted at healthy populations. We included studies published from January 2000 to March 2021 in English, Spanish, French, Portuguese, or German. Two reviewers independently decided for or against inclusion based on abstracts. A third reviewer intervened in case of disagreements. From the selected titles, we extracted information regarding the purpose of the manuscript, analyzed calculators, population for which it was calibrated, included risk factors, and the model’s overall accuracy.

Results

We included a total of 18 calculators from 53 different manuscripts. The most commonly analyzed ones were the Prostate Cancer Prevention Trial (PCPT) and European Randomized Study on Prostate Cancer (ERSPC) risk calculators developed from North American and European cohorts, respectively. Both calculators provided high diagnostic ability of aggressive prostate cancer (AUC as high as 0.798 for PCPT and 0.91 for ERSPC). We found 9 calculators developed from scratch for specific populations that reached a diagnostic ability as high as 0.938. The most commonly included risk factors in the calculators were age, prostate specific antigen levels, and digital rectal examination findings. Additional calculators included race and detailed personal and family history.

Conclusions

Both the PCPR and ERSPC risk calculators have been successfully adapted for cohorts other than the ones they were originally created for with no loss of diagnostic ability. Furthermore, designing calculators from scratch considering each population’s sociocultural differences has resulted in risk tools that can be well adapted to be valid in more patients. The best risk calculator for prostate cancer will be that which has been calibrated for its intended population and can be easily reproduced and implemented.

Trial Registration

PROSPERO CRD42021242110; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=242110

Prostate Cancer in Older Adults: Risk of Clinically Meaningful Disease, the Role of Screening and Special Considerations

PURPOSE OF REVIEW

Prostate cancer is the second most common cancer in men in the USA and several studies suggest more aggressive disease in older patients. However, screening remains controversial, especially in the older patient population.

RECENT FINDINGS

Aggressive prostate cancers are more common in older men. Screening trial results are conflicting but data suggest an improvement in prostate cancer mortality and increased detection of metastatic disease with screening. When PSA is utilized with multiparametric MRI and biomarker assays, patients at significant risk of clinically meaningful prostate cancer can be appropriately selected for biopsy. A thoughtful and individualized approach is central when considering prostate cancer screening in older men. This approach includes life expectancy estimation, use of appropriate geriatric assessment tools, use of multiparametric MRI and biomarkers in addition to PSA, and most importantly shared decision-making with patients.

Prostate cancer screening using a combination of risk-prediction, MRI, and targeted prostate biopsies (STHLM3-MRI): a prospective, population-based, randomised, open-label, non-inferiority trial

BACKGROUND

Screening for prostate cancer using prostate-specific antigen (PSA) reduces prostate cancer mortality but can lead to adverse outcomes. We aimed to compare a traditional screening approach with a diagnostic strategy of blood-based risk prediction combined with MRI-targeted biopsies.

METHODS

We did a prospective, population-based, randomised, open-label, non-inferiority trial (STHLM3-MRI) in Stockholm county, Sweden. Men aged 50-74 years were randomly selected by Statistics Sweden and invited by mail to participate in screening; those with an elevated risk of prostate cancer, defined as either a PSA of 3 ng/mL or higher or a Stockholm3 score of 0·11 or higher were eligible for randomisation. Men with a previous prostate cancer diagnosis, who had undergone a prostate biopsy within 60 days before the invitation to participate, with a contraindication for MRI, or with severe illness were excluded. Eligible participants were randomly assigned (2:3) using computer-generated blocks of five, stratified by clinically significant prostate cancer risk, to receive either systematic prostate biopsies (standard group) or biparametric MRI followed by MRI-targeted and systematic biopsy in MRI-positive participants (experimental group). The primary outcome was the detection of clinically significant prostate cancer at prostate biopsy, defined as a Gleason score of 3 + 4 or higher. We used a margin of 0·78 to assess non-inferiority for the primary outcome. Key secondary outcome measures included the proportion of men with clinically insignificant prostate cancer (defined as a Gleason score of 3 + 3), and the number of any prostate MRI and biopsy procedures done. We did two comparisons: Stockholm3 (using scores of 0·11 and 0·15 as cutoffs) versus PSA in the experimental group (paired analyses) and PSA plus standard biopsy versus Stockholm3 plus MRI-targeted and systematic biopsy (unpaired, randomised analyses). All analyses were intention to treat. This study is registered with ClinicalTrials.gov, NCT03377881.

FINDINGS

Between Feb 5, 2018, and March 4, 2020, 49 118 men were invited to participate, of whom 12 750 were enrolled and provided blood specimens, and 2293 with elevated risk were randomly assigned to the experimental group (n=1372) or the standard group (n=921). The area under the receiver-operating characteristic curve for detection of clinically significant prostate cancer was 0·76 (95% CI 0·72-0·80) for Stockholm3 and 0·60 (0·54-0·65) for PSA. In the experimental group, a Stockholm3 of 0·11 or higher was non-inferior to a PSA of 3 ng/mL or higher for detection of clinically significant prostate cancer (227 vs 192; relative proportion [RP] 1·18 [95% CI 1·09-1·28], p<0·0001 for non-inferiority), and also detected a similar number of low-grade prostate cancers (50 vs 41; 1·22 [0·96-1·55], p=0·053 for superiority) and was associated with more MRIs and biopsies. Compared with PSA of 3 ng/mL or higher, a Stockholm3 of 0·15 or higher provided identical sensitivity to detect clinically significant cancer, and led to fewer MRI procedures (545 vs 846; 0·64 [0·55-0·82]) and fewer biopsy procedures (311 vs 338; 0·92 (0·86-1·03). Compared with screening using PSA and systematic biopsies, a Stockholm3 of 0·11 or higher combined with MRI-targeted and systematic biopsies was associated with higher detection of clinically significant cancers (227 [3·0%] men tested vs 106 [2·1%] men tested; RP 1·44 [95% CI 1·15-1·81]), lower detection of low-grade cancers (50 [0·7%] vs 73 [1·4%]; 0·46 [0·32-0·66]), and led to fewer biopsy procedures. Patients randomly assigned to the experimental group had a lower incidence of prescription of antibiotics for infection (25 [1·8%] of 1372 vs 41 [4·4%] of 921; p=0·0002) and a lower incidence of admission to hospital (16 [1·2%] vs 31 [3·4%]; p=0·0003) than those in the standard group.

INTERPRETATION

The Stockholm3 test can inform risk stratification before MRI and targeted biopsies in prostate cancer screening. Combining the Stockholm3 test with an MRI-targeted biopsy approach for prostate cancer screening decreases overdetection while maintaining the ability to detect clinically significant cancer.

FUNDING

The Swedish Cancer Society, the Swedish Research Council, and Stockholm City Council.

Diagnostic accuracy of [-2]proPSA versus Gleason score and Prostate Health Index versus Gleason score for the determination of aggressive prostate cancer: a systematic review

OBJECTIVE

The objective of this review was to determine the diagnostic accuracy of [-2]proPSA (p2PSA) and the Prostate Health Index compared to the Gleason score in determining the aggressiveness of prostate cancer.

INTRODUCTION

Prostate cancer is the most commonly diagnosed cancer in men. However, the utility of currently available biomarkers for determining the aggressive form of the disease remains unknown. This review sought to determine the diagnostic accuracy of two new biomarkers in determining the aggressive form of prostate cancer.

INCLUSION CRITERIA

Diagnostic accuracy studies that enrolled men of any age and any prostate specific antigen (PSA) level with histologically confirmed prostate cancer in which Prostate Health Index and p2PSA were assessed in comparison to Gleason score for the determination of aggressive prostate cancer were considered for inclusion. There was no time limitation on study inclusion.

METHODS

A three-step search strategy was utilized to identify both published and unpublished studies in the English language in the following sources: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Web of Science, Google Scholar, MedNar, and SIGLE. Databases were searched from inception to January 2019. Study selection, critical appraisal, data extraction, and data synthesis were done according to the approach recommended by JBI.

RESULTS

A total of 12 studies (n = 8462) that recruited men with aggressive prostate cancer were considered in this review. The majority of included subjects had a total PSA level of 2 to 10ng/mL. The sensitivity of the Prostate Health Index ranged from 67% to 97% while specificity ranged from 6% to 64%. At a Prostate Health Index threshold of 25 and below (three studies, n = 3222), pooled sensitivity was 97% (95% confidence interval [CI], 95% to 98%) and specificity was 10% (95% CI, 6% to 16%). At a Prostate Health Index threshold of between 26 and 35 (six studies, n = 6030), pooled sensitivity was 87% (95% CI, 8% to 91%) and specificity was 45% (95% CI, 39% to 50%). At a Prostate Health Index threshold of 36 and above (five studies, n = 1476), pooled sensitivity was 72% (95% CI, 64% to 79%) and specificity was 74% (95% CI, 68% to 80%). Only one study assessed p2PSA. Sensitivity ranged from 80% to 95%, and specificity ranged from 9.9% to 27.9% with increasing threshold values from 7.9 to 10.9ng/mL.

CONCLUSIONS

Overall, both Prostate Health Index and p2PSA have acceptable accuracy for the determination of the likelihood of aggressive prostate cancer. However, the inverse relationship between sensitivity and specificity makes it difficult to determine an optimum cut-off value for positivity. Further research is warranted to determine their utility in the management of prostate cancer.

Use of the prostate health index in the detection of prostate cancer at all PSA levels (use of prostate health index in prostate cancer)

OBJECTIVES

To determine the efficiency of prostate health index (PHI) calculated simultaneously during an ultrasound-guided fine-needle prostate biopsy in prostate cancer diagnosis.

METHODS

The present study included 258 subsequent patients who underwent a TRUS-guided biopsy in our clinic between August 2015 and March 2016 due to elevated blood levels of PSA and suspicion of prostate cancer. The total PSA, free PSA and pro-PSA were analysed in all patients before the procedure.

RESULTS

The average age of 258 patients was 63.5 (36-91) years, and the mean PSA level and mean PHI values were 40.1 (0.12-2170) and 118 (0.41-1308), respectively. According to the PSA data, the patients were divided into two groups: the low PSA (<4 ng/mL) group containing ten patients with adenocancer (31.2%) and 22 patients with BPH (68.8%) and the high PSA (>4 ng/mL) group consisting of 86 patients with adenocancer (42.2%) and 118 (57.8%) with BPH. The sensitivity and specificity of PSA in detecting prostate adenocancer were calculated as 89.6% and 15.7%, respectively. Similarly, when a PHI level below 55 was accepted as low, and a PHI level at or above 55 was accepted as high, PHI's sensitivity and specificity were determined as 71.9% and 67.9%, respectively.

CONCLUSIONS

The overall findings indicate that the specificity of PHI is higher than PSA in terms of prostate cancer detection.

The Value of a New Diagnostic Test for Prostate Cancer: A Cost-Utility Analysis in Early Stage of Development

BACKGROUND

Standard biopsy for prostate cancer diagnosis is an unpleasant and sometimes painful procedure with a detection rate as low as around 50%. Consequently, an accurate blood-based test would be highly desirable to improve the predictive accuracy. However, the clinical value of a new blood test for diagnosing prostate cancer depends on its sensitivity and specificity, in relation to the selected target population.

OBJECTIVE

The aim of this analysis was to investigate the health-economic value of introducing a new and more accurate diagnostic blood-based test to identify men in need of a biopsy to diagnose prostate cancer.

METHOD

We developed a Discrete Event Simulation Model with outputs including number of biopsies, cancer diagnosis, treatments and prostate cancer deaths. The analysis was performed from a health care perspective. It used epidemiologic data, treatment patterns, and health care costs from the Swedish region Skåne (population of 1.3 million). A 90% sensitivity and specificity of the new test was assumed.

RESULTS

Among 31,250 men, age 50-69 years, 16.4% had a PSA between 3.0 and 9.9 µg/L and 28.9% a PSA of 2.0-9.9 µg/L. Testing men with PSA 3.0-9.9 µg/L, as in current clinical practice, decreased the number of biopsies by 3595, detected 61 more cancers, resulting in and two more fatalities and subsequently a loss of 14 QALYs. Cost offsets could justify a test value of SEK 4996. Testing a larger population, PSA 2.0-9.9 µg/L prevented 6 deaths, added 50 QALYs, and could justify a value of the test of SEK 5165, given a value of health of SEK 500,000 per QALY.

CONCLUSION

A new blood-based test for prostate cancer has a significant potential to reduce the number of biopsies needed, resulting in reduced health care costs and improve patient care.

Performance of Prostate Health Index in Biopsy Naïve Black Men

PURPOSE

The Prostate Health Index is validated for prostate cancer detection but has not been well validated for Gleason grade group 2-5 prostate cancer detection in Black men. We hypothesize that the Prostate Health Index has greater accuracy than prostate specific antigen for detection of Gleason grade group 2-5 prostate cancer. We estimated probability of overall and Gleason grade group 2-5 prostate cancer across previously established Prostate Health Index ranges and identified Prostate Health Index cutoffs that maximize specificity for Gleason grade group 2-5 prostate cancer with sensitivity >90%.

MATERIALS AND METHODS

We recruited a "cancer-free" Black control cohort (135 patients) and a cohort of biopsy naïve Black men (158) biopsied for elevated prostate specific antigen. Descriptive statistics compared the prostate cancer cases and controls and the frequency of Gleason grade group 2-5 prostate cancer across Prostate Health Index scores. Receiver operating characteristics compared the discrimination of prostate specific antigen, Prostate Health Index and other prostate specific antigen related biomarkers. Sensitivity and specificity for Gleason grade group 2-5 prostate cancer detection were assessed at prostate specific antigen and Prostate Health Index thresholds alone and in series.

RESULTS

Of biopsied subjects 32.9% had Gleason grade group 2-5 prostate cancer. In Blacks with prostate specific antigen from 4.0-10.0 ng/ml, Prostate Health Index and prostate specific antigen had similar discrimination for Gleason grade group 2-5 prostate cancer (0.63 vs 0.57, p=0.27). In Blacks with prostate specific antigen ≤10.0, a threshold of prostate specific antigen ≥4.0 had 90.4% sensitivity for Gleason grade group 2-5 prostate cancer; a threshold of prostate specific antigen ≥4.0 with Prostate Health Index ≥35.0 in series avoided unnecessary biopsy in 33.0% of men but missed 17.3% of Gleason grade group 2-5 prostate cancer. Prostate specific antigen ≥4.0 with Prostate Health Index ≥28.0 in series spared biopsy in 17.9%, while maintaining 90.4% sensitivity of Gleason grade group 2-5 prostate cancer.

CONCLUSIONS

The Prostate Health Index has moderate accuracy in detecting Gleason grade group 2-5 prostate cancer in Blacks, but Prostate Health Index ≥28.0 can be safely used to avoid some unnecessary biopsies in Blacks.

PHI density prospectively improves prostate cancer detection

Purpose

To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort.

Methods

PHID values were calculated from prostate-specific antigen (PSA), free PSA and [− 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate cancer (PCa) and 505 with no evidence of malignancy (NEM). In detail, 562 patients were biopsied at the Charité Hospital Berlin and 495 patients at the Sana Hospital Offenbach. All patients received systematic or magnetic resonance imaging (MRI)/ultrasound fusion-guided biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing areas under the ROC-curves (AUC). The decision curve analysis (DCA) was performed with the MATLAB Neural Network Toolbox.

Results

PHID provided a significant larger AUC than PHI (0.835 vs. 0.801; p = 0.0013) in our prospective cohort of 1057 men from 2 centers. The DCA had a maximum net benefit of ~ 5% for PHID vs. PHI between 35 and 65% threshold probability. In those 698 men within the WHO-calibrated PSA grey-zone up to 8 ng/ml, PHID was also significantly better than PHI (AUC 0.819 vs. 0.789; p = 0.0219). But PHID was not different from PHI in the detection of significant PCa.

Conclusions

Based on ROC analysis and DCA, PHID had an advantage in comparison with PHI alone to detect any PCa but PHI and PHID performed equal in detecting significant PCa.

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.

A review of current clinical biomarkers for prostate cancer: towards personalised and targeted therapy

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortality in Canadian men. The current ‘gold standard’ for the diagnosis of prostate cancer is a prostate biopsy and the decision on when to biopsy a patient with non-suspicious Digital Rectal Examination (DRE) result and total prostate specific antigen (tPSA) of 4–10 ng/ml can be challenging. In order to shift the treatment paradigm of prostate cancer toward more personalised and targeted therapy, there is the need for a clear system that makes its detection binary so as to decrease the rate of inaccurate detections. Therefore in recent years, there have been several investigations into the development of various biomarkers with high sensitivity and specificity for screening, early detection and personalised patient-specific targeted medicine from diagnosis to treatment of the disease.

Materials and methods:

This paper reports on nine currently available clinical biomarkers used in screening for early detection and diagnosis, to reduce the number of unnecessary biopsies, in risk assessment of aggressive disease and in monitoring treatment response of prostate cancer.

Conclusion:

Current clinical prostate cancer biomarkers have the potential for a personalised risk assessment of aggressive disease and the risk of developing distant metastatic disease and have been proven to be useful tools to guide clinicians in personalised patient-specific targeted treatment and in the shared decision making between patients and their physicians regarding prostate biopsy and treatment. Using biomarkers to select patients with a significant probability of aggressive prostate cancer would potentially avoid premature death from the disease, while at the same time would safely preclude patients who do not require unnecessary invasive intervention.

Biomarkers in the setting of benign prostatic hyperplasia-induced lower urinary tract symptoms: what an interventional radiologist needs to know

With increasing evidence to support prostate artery embolization (PAE) in the treatment of benign prostatic hyperplasia (BPH)-induced lower urinary tract symptoms (LUTS), Interventional Radiologists have begun to play an important role in the management of these patients. One area of knowledge needed when developing a PAE practice is knowledge of prostate-specific antigen (PSA) and other biomarkers utilized to detect prostate cancer in this population and what role they should play in the work up and follow-up of patients presenting with presumed BPH-induced LUTS. Furthermore, understanding how to evaluate presumed BPH-induced LUTS and stratify the risk of prostate cancer is an important skill to develop. The goal of this review is to provide Interventional Radiologists who have begun or aim to begin a PAE practice with the information they need to know regarding PSA levels and prostate cancer risk stratification for this patient population.

The predictive value of the prostate health index vs. multiparametric magnetic resonance imaging for prostate cancer diagnosis in prostate biopsy

PURPOSE

To compare the ability of Prostate Health Index (PHI) to diagnose csPCa, with that of total PSA, PSA density (PSAD) and the multiparametric magnetic resonance (mpMRI) of the prostate.

METHODS

We analysed a group of 395 men planned for a prostate biopsy who underwent a mpMRI of the prostate evaluated using the PIRADS v1 criteria. All patients had their PHI measured before prostate biopsy. In patients with an mpMRI suspicious lesions, an mpMRI/ultrasound software fusion-guided biopsy was performed first, with 12 core systematic biopsy performed in all patients. A ROC analysis was performed for PCa detection for total PSA, PSAD, PIRADS score and PHI; with an AUC curve calculated for all criteria and a combination of PIRADS score and PHI. Subsequent sub-analyses included patients undergoing first and repeat biopsy.

RESULTS

The AUC for predicting the presence of csPCa in all patients was 59.5 for total PSA, 69.7 for PHI, 64.9 for PSAD and 62.5 for PIRADS. In biopsy naive patients it was 61.6 for total PSA, 68.9 for PHI, 64.6 for PSAD and 63.1 for PIRADS. In patients with previous negative biopsy the AUC for total PSA, PHI, PSAD and PIRADS was 55.4, 71.2, 64.4 and 69.3, respectively. Adding of PHI to PIRADS increased significantly (p = 0.007) the accuracy for prediction of csPCa.

CONCLUSION

Prostate Health Index could serve as a tool in predicting csPCa. When compared to the mpMRI, it shows comparable results. The PHI cannot, however, help us guide prostate biopsies in any way, and its main use may, therefore, be in pre-MRI or pre-biopsy triage.

Prostate Health Index and Prostate Health Index Density as Diagnostic Tools for Improved Prostate Cancer Detection

Background

To evaluate the diagnostic potential of [-2] proPSA (p2PSA), %p2PSA, Prostate Health Index (phi), and phi density (PHID) as independent biomarkers and in composition of multivariable models in predicting high-grade prostatic intraepithelial neoplasia (HGPIN) and overall and clinically significant prostate cancer (PCa).

Methods

210 males scheduled for prostate biopsy with total PSA (tPSA) range 2-10 ng/mL and normal digital rectal examination were enrolled in the prospective study. Blood samples to measure tPSA, free PSA (fPSA), and p2PSA were collected immediately before 12-core prostate biopsy. Clinically significant PCa definition was based on Epstein's criteria or ISUP grade ≥ 2 at biopsy.

Results

PCa has been diagnosed in 112 (53.3%) patients. Epstein significant and ISUP grade ≥ 2 PCa have been identified in 81 (72.3%) and 40 (35.7%) patients, respectively. Isolated HGPIN at biopsy have been identified in 24 (11.4%) patients. Higher p2PSA and its derivative mean values were associated with PCa. At 90% sensitivity, PHID with cut-off value of 0.54 have demonstrated the highest sensitivity of 35.7% for overall PCa detection, so PHID and phi with cut-off values of 33.2 and 0.63 have demonstrated the specificity of 34.7% and 34.1% for ISUP grade ≥ 2 PCa detection at biopsy, respectively. In univariate ROC analysis, PHID with AUC of 0.77 and 0.80 was the most accurate predictor of overall and Epstein significant PCa, respectively, so phi with AUC of 0.77 was the most accurate predictor of ISUP grade ≥ 2 PCa at biopsy. In multivariate logistic regression analysis, phi improved diagnostic accuracy of multivariable models by 5% in predicting ISUP grade ≥ 2 PCa.

Conclusions

PHID and phi have shown the greatest specificity at 90% sensitivity in predicting overall and clinically significant PCa and would lead to significantly avoid unnecessary biopsies. PHID is the most accurate predictor of overall and Epstein significant PCa, so phi is the most accurate predictor of ISUP grade ≥ 2 PCa. phi significantly improves the diagnostic accuracy of multivariable models in predicting ISUP grade ≥ 2 PCa.

Temporal trends in the number of men electing for conservative management for low-risk prostate cancer in the United States

BACKGROUND

Concurrent with the decrease in the number of men diagnosed with prostate cancer (PCa), the proportion of men with low-risk PCa managed conservatively (active surveillance or watchful waiting) has increased in the United States. We aimed to determine whether this increase is a result of more men being managed conservatively or rather a higher proportion of the diminishing number of low-risk PCa managed this way.

METHODS

The SEER "Prostate Watchful Waiting Database" identified men managed initially with conservative management between 2010 and 2016. Men > 40 years old who were diagnosed with low-risk (Gleason score 3 + 3, T1-T2a, PSA level < 10 ng/mL) PCa were included. Age-standardized and age-specific PCa incidence and conservative management rates were calculated per 100,000 man-years. The annual percent change in rates for the entire time period was also calculated.

RESULTS

The incidence of low-risk PCa declined by 11.8% per year (95% confidence interval [CI] -15.4% to -8.0%), whereas the number of men assigned to conservative management for low-risk disease did not increase significantly, rising by +3.7% per year (95% CI -0.7% to 8.4%). In age-specific analysis, the number of men < 60 years and those who were 60-69 years managed conservatively increased by +9.6% per year (95% CI 2.7% to 16.9%) and 4.5% per year (95% CI 0.1% to 9.1%), respectively, whereas the number of men ≥ 70 years electing conservative management remained stable at -4% per year (95% CI -11.2% to 3.7%).

CONCLUSIONS

The number of men electing conservative management has remained largely stable between 2010 and 2016, despite an increase in the proportion of low-risk PCa managed in this manner.

Personalized strategies in population screening for prostate cancer

This review discusses evidence for population-based screening with contemporary screening tools. In Europe, prostate-specific antigen (PSA)-based screening led to a relative reduction of prostate cancer (PCa) mortality, but also to a substantial amount of overdiagnosis and unnecessarily biopsies. Risk stratification based on a single variable (a clinical variable or based on the presence of a lesion on prostate imaging) or based on multivariable approaches can aid in reducing unnecessary prostate biopsies and overdiagnosis by selecting men who can benefit from further clinical assessment. Multivariable approaches include clinical variables, and biomarkers, often combined in risk calculators or nomograms. These risk calculators can also incorporate the result of MRI imaging. In general, as compared to a purely PSA based approach, the combination of relevant prebiopsy information results in superior selection of men at higher risk of harboring clinically significant prostate cancer. Currently, it is not possible to draw any conclusions on the superiority of these multivariable risk-based approaches since head-to-head comparisons are virtually lacking. Recently initiated large population-based screening studies in Finland, Germany and Sweden, incorporating various multivariable risk stratification approaches will hopefully give more insight in whether the harm-benefit ratio can be improved, that is, maintain (or improving) the ability to reduce metastatic disease and prostate cancer mortality while reducing harm caused by unnecessary testing and overdiagnosis including related overtreatment.

Adaptation of the prostate biopsy collaborative group risk calculator in patients with PSA less than 10 ng/ml improves its performance

PURPOSES

The prostate biopsy collaborative group risk calculator (PBCGRC) is a newly developed risk estimator for predicting prostate biopsy outcomes. However, its clinical usefulness is still unknown within the so-called gray area of PSA values. This study aimed to determine whether updating the PBCGRC improves its predictive performance for predicting any-grade and high-grade (HG), defined as biopsy Gleason score ≥ 7, prostate cancer (PCa) in patients with prostate-specific antigen (PSA) less than 10 ng/ml.

METHODS

The risk of any-grade and HGPCa was calculated using the PBCG risk calculation formulas updated by recalibration in the large, logistic recalibration and model revision. Predictive performances of the PBCGRC and the updated models were compared using discrimination, calibration, and clinical utility.

RESULTS

Within the study sample of 526 patients, PCa was detected in 193 (36.7%), and 78 (14.8%) of them had HGPCa. According to the calibration curves, the PBCGRC overestimated the risk of PCa. Predictive accuracy of the revised model was higher [the area under the receiver-operating characteristic curve (AUCs), 65.4% and 70.2%] than that of the PBCGRC (AUCs, 60.4% and 64.3%) for any-grade and HGPCa. The net benefit was greater for model revision in comparison with the original model.

CONCLUSION

The performance accuracy of PBCGRC for the prediction of any and HGPC in men undergoing prostate biopsy with PSA levels below 10 ng/ml is suboptimal. The model revision resulted with significant improvement in model performance. However, external validation of the revised model is necessary before its routine use in clinical practice.

Serum and urinary biomarkers for detection and active surveillance of prostate cancer

PURPOSE OF REVIEW

To provide a comprehensive review of the available biomarkers for the detection and active surveillance of prostate cancer and simplify decision-making while choosing between them.

RECENT FINDINGS

The limitations of PSA and mpMRI and the invasive nature of prostate biopsy has led to a constant search for serum and urinary biomarkers for both the detection and monitoring during active surveillance of prostate cancer. 4K, PHI and PCA3 have been validated in prospective clinical trials for initial detection of prostate cancer and recent evidence points to potential differentiation between indolent and aggressive cancer. However, the usage in monitoring tumor dynamics is debatable because of lack of conclusive evidence. The answer to the existing problems lies in high-quality studies to establish definitive evidence and also to help choose between the plethora of biomarkers available today.

SUMMARY

Despite the advancements in innovation and usage of biomarkers in prostate cancer, there exists tremendous potential in improving them to fulfil the unmet need that exists today. Studies to establish conclusive evidence and integration with imaging can tremendously aid diagnosis and monitoring.

Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study

BACKGROUND

The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies.

METHODS

A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed.

RESULTS

A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds.

CONCLUSION

phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.

Serum and urine biomarkers for detecting clinically significant prostate cancer

Since the "prostate-specific antigen (PSA) era," we have seen an increase in unnecessary biopsies, which has ultimately lead to an overtreatment of low-risk cancers. Given the limitations of prostate-specific antigen and the invasive nature of prostate biopsy several serum and urinary biomarkers have been developed. In this paper, we provide a comprehensive review of the available biomarkers for the detection clinically significant prostate cancer namely PHI, 4Kscore, PCA3, MiPS, SelectMDx, ExosomeDX. Current literature suggests that these biomarkers can improve detection of clinically significant prostate cancer reducing overtreatment and making treatment strategies more cost-effective. Nevertheless, large prospective studies with head-to-head-comparisons of the available biomarkers are necessary to fully assess the potential of incorporating biomarkers in routine clinical practice.

Early Diagnosis of Prostate Cancer from the Perspective of Chinese Physicians

Prostate cancer (PCa) is the seventh most diagnosed cancer and the tenth leading cause of cancer mortality in China. Unlike the USA, both incidence and mortality continue to increase. In China, PCa is often diagnosed at a locally advanced or metastatic stage, resulting in a high mortality-to-incidence ratio. Implementing regular screening using a well-validated biomarker may result in the earlier diagnosis of localized disease. Furthermore, it is important to be able to distinguish between low-grade and high-grade disease, to avoid subjecting patients to unnecessary biopsies, undertreatment of significant disease, or overtreatment of indolent disease. While prostate-specific antigen (PSA) is commonly used in PCa screening around the world, its relationship to PCa is still unclear and results vary widely across different studies. New biomarkers, imaging techniques and risk predictive models have been developed in recent years to improve upon the accurate detection of high-grade PCa. Blood- and urine-based biomarkers, such as PSA isoforms, prostate cancer antigen 3, or mRNA transcripts, have been used to improve the detection of high-grade PCa. These markers have also been used to create risk predictive models, which can further improve PCa detection. Furthermore, multiparametric magnetic resonance imaging is becoming increasingly accessible for the detection of PCa. Because of ethnic variations, biomarkers and risk predictive models validated in Western populations cannot be directly applied to Chinese men. Validation of new biomarkers and risk predictive models in the Chinese population may improve PCa screening and reduce mortality of this disease in China.

Beyond PSA: The Role of Prostate Health Index (phi)

Background: Widespread use of prostate specific antigen (PSA) in screening procedures allowed early identification of an increasing number of prostate cancers (PCas), mainly including indolent cancer. Availability of different therapeutic strategies which have a very different impact on the patient’s quality of life suggested a strong need for tools able to identify clinically significant cancer at diagnosis. Multi-parametric magnetic resonance showed very good performance in pre-biopsy diagnosis. However, it is an expensive tool and requires an experienced radiologist. In this context, a simple blood-based test is worth investigating. In this context, researchers focused their attention on the development of a laboratory test able to minimize overdiagnosis without losing the identification of aggressive tumors. Results: Recent literature data on PCa biomarkers revealed a clear tendency towards the use of panels of biomarkers or a combination of biomarkers and clinical variables. Phi, the 4Kscore, and Stockholm3 as circulating biomarkers and the Mi-prostate score, Exo DX Prostate, and Select MD-X as urinary biomarker-based tests have been developed. In this scenario, phi is worthy of attention as a noninvasive test significantly associated with aggressive PCa. Conclusions: Literature data showed that phi had good diagnostic performance to identify clinically significant (cs) PCa, suggesting that it could be a useful tool for personalized treatment decision-making. In this review, phi potentialities, limitations, and comparisons with other blood- and urinary-based tests were explored.

Optimal threshold of the prostate health index in predicting aggressive prostate cancer using predefined cost-benefit ratios and prevalence

PURPOSES

The aim of the study was to determine optimal threshold of the Prostate Health Index (Phi) for predicting aggressive prostate cancer (PCa), taking into account misclassification costs, prevalence, and plausible risk factors.

METHODS

This prospective cohort study analyzed patients undergoing prostate biopsy and Phi testing. The primary endpoint was aggressive PCa, defined as biopsy Gleason score ≥ 7. The data about age, total prostate-specific antigen (PSA), percentage of free PSA (%fPSA), and digital rectal examination (DRE) were extracted from the patient files. We divided the patients to the low- and high-risk group. The clinical usefulness of the Phi was assessed by the decision curve analysis. The predictive performance was assessed using the area under the receiver operating characteristic curve (AUC), per-class metrics, and the potential reduction in unnecessary biopsies. The uncertain interval of Phi values was also determined.

RESULTS

There were 200 men included in the study, 35 (17.5%) of them having aggressive PCa. Important predictors of aggressive PCa were %fPSA, DRE, Phi, and belonging to the high-risk group. With optimal threshold of 30.7, about 32% unnecessary biopsies would be avoided. The optimal threshold of Phi was lower in the high-risk group than in the low-risk group. The AUC for detection of aggressive PCa was 0.791. Per-class metrics showed that the Phi has insufficient diagnostic accuracy. The lower and upper limits of the uncertain interval were 41.8 and 51.4, respectively.

CONCLUSION

Different thresholds of the Phi could be optimal, depending on prevalence, patient characteristics, and misclassification costs. Further studies with a larger patient sample are necessary to confirm our conclusions.

Preanalytical stability of [-2]proPSA in whole blood stored at room temperature before separation of serum and plasma: implications to Phi determination

Background [-2]proPSA seems to outperform free/total prostate-specific antigen (PSA) ratio in prostate cancer diagnosis. However, [-2]proPSA stability remains an underestimated issue. We examined [-2]proPSA stability over time in whole blood before separation of serum and plasma and its implications for prostate health index (Phi) determination. Total PSA (tPSA) and free PSA (fPSA) stabilities were also assessed. Methods Blood was drawn from 26 patients and separated in two tubes for plasma (K2EDTA and K2EDTA plus protease inhibitors - P100) and one for serum (clot activator plus gel separator). Tubes were stored at room temperature before centrifugation 1, 3 and 5 h for serum and EDTA plasma or 1 and 5 h for P100 plasma. To investigate the influence of gel separator on markers' stability, blood was collected from 10 patients in three types of tubes to obtain serum: tubes with clot activator plus gel separator, with silica particles or glass tubes. Biomarkers were assayed with chemiluminescent immunoassays. Results [-2]proPSA and Phi levels significantly and progressively increased over time in serum (+4.81% and +8.2% at 3 h; +12.03% and +14.91% at 5 h, respectively, vs. 1 h; p<0.001). Conversely, [-2]proPSA levels did not change in plasma (EDTA or P100). tPSA levels did not change over time in serum or plasma, whereas fPSA decreased in serum. All markers were higher in plasma than in serum at any time point. This difference did not seem to be attributable to the use of gel for serum preparation. Conclusions EDTA prevented spurious in vitro modifications in PSA-related isoforms, confirming that a stabilized blood sample is a prerequisite for [-2]proPSA measurement and Phi determination.

Observational study comparing the accuracy/variability between the ERSPC and the PCPT risk calculators for the prediction of significant prostate cancer in patients with PSA <10 ng/mL

INTRODUCTION

Risk calculators (RCs) are easy-to-use tools considering available clinical variables that could help to select those patients with risk of prostate cancer (PCa) who should undergo a prostate biopsy.

OBJECTIVE

To perform a comparison for the prediction of significant PCa (SigPCa) between the European Randomised Study of Screening for PCa (ERSPC) and the PCa Prevention Trial (PCPT) RCs in patients with prostate-specific antigen (PSA) between 3 and 10 ng/mL through an evaluation of the accuracy/variability between two consecutive PSA values.

SETTING

An observational study in a major university hospital in the south of Spain.

METHODS AND PARTICIPANTS

An observational study was performed in patients who underwent a prostate biopsy. SigPCa probabilities were calculated with the two PSA measures using ERSPC3/4+digital rectal examination and PCPT v2+free PSA RCs. The prediction of SigPCa was determined by the area under the receiver operating characteristic curve (AUC). Calibration, discrimination and decision curve analysis were studied. The variability between both RCs' agreement was compared using Cohen's kappa coefficient.

RESULTS

510 patients were analysed (87 diagnosed with SigPCa). The median PSA values were 5.3 and 5 ng/mL for PSA1 and PSA2, respectively. Both RCs overestimated the risk in the case of high-risk probabilities. Discriminative ability for SigPCa was similar between models with an AUC=0.73 (0.68-0.79) for ERSPC-RC versus 0.73 (0.67-0.79) for PCPT-RC. ERSPC-RC showed less variability than PCPT-RC, with a constant agreement (k=0.7-0.8) for usual range of clinical decision-making. Remarkably, a higher number of biopsies would be avoided using the ERSPC-RC, but more SigPCa would be missed along all the risk probabilities.

CONCLUSIONS

Both RCs performed similar in the prediction of SigPCa. However, ERSPC-RC seems to be more stable for intraindividual PSA variations.

Combining prostate health index and multiparametric magnetic resonance imaging in the diagnosis of clinically significant prostate cancer in an Asian population

Objective

To evaluate the practicability of combining prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) for the detection of clinically significant prostate cancer (csPC) in an Asian population.

Patients and methods

We prospectively enrolled patients who underwent prostate biopsy due to elevated serum prostate-specific antigen (PSA > 4 ng/mL) and/or abnormal digital rectal examination in a tertiary referral center. Before prostate biopsy, the serum samples were tested for PSA, free PSA, and p2PSA to calculate PHI. Besides, mpMRI was performed using a 3-T scanner and reported in the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2). The diagnostic performance of PHI, mpMRI, and combination of both was assessed.

Result

Among 102 subjects, 39 (38.2%) were diagnosed with PC, including 24 (23.5%) with csPC (Gleason ≥ 7). By the threshold of PI-RADS ≥ 3, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to predict csPC were 100%, 44.9%, 35.8%, and 100%, respectively. By the threshold of PHI ≥ 30, the sensitivity, specificity, PPV, and NPV to predict csPC were 91.7%, 43.6%, 33.3%, and 94.4%, respectively. The area under the receiver operator characteristic curve of combining PHI and mpMRI was greater than that of PHI alone (0.873 vs. 0.735, p = 0.002) and mpMRI alone (0.873 vs. 0.830, p = 0.035). If biopsy was restricted to patients with PI-RADS 5 as well as PI-RADS 3 or 4 and PHI ≥ 30, 50% of biopsy could be avoided with one csPC patient being missed.

Conclusion

The combination of PHI and mpMRI had higher accuracy for detection of csPC compared with PHI or mpMRI alone in an Asian population.

Assessment of men's risk thresholds to proceed with prostate biopsy for the early detection of prostate cancer

PURPOSE

To delineate the range of "risk thresholds" for prostate biopsy to determine how improved prostate cancer (CaP) risk prediction tools may impact shared decision-making (SDM).

METHODS

We conducted a cross-sectional survey study involving men 45-75 years old attending a multispecialty urology clinic. Data included demographics, personal and family prostate cancer history, and prostate biopsy history. Respondents were presented with a summary of the details, risks, and benefits of prostate biopsy, then asked to indicate the specific risk threshold (% chance) of high-grade CaP at which they would proceed with prostate biopsy.

RESULTS

Of a total of 103 respondents, 18 men (17%) had a personal history of CaP, and 31 (30%) had undergone prostate biopsy. The median risk threshold to proceed with prostate biopsy was 25% (interquartile range 10-50%). Risk thresholds did not vary by race, education, or employment. Personal history of CaP or prostate biopsy was significantly associated with lower mean risk thresholds (19% vs. 32% [P = 0.02] and 23% vs. 33% [P = 0.04], respectively). In the lowest versus highest risk threshold quartiles, there were significantly higher rates of CaP (36% vs. 1%, P = 0.01) and prior prostate biopsy (46% vs. 17%, P < 0.01).

CONCLUSIONS

Men have a wide range of risk thresholds for high-grade CaP to proceed with prostate biopsy. Men with a prior history of CaP or biopsy reported lower risk thresholds, which may reflect their greater concern for this disease. The extent to which refined risk prediction tools will improve SDM warrants further study.

Structured Population-based Prostate-specific Antigen Screening for Prostate Cancer: The European Association of Urology Position in 2019

Prostate cancer (PCa) is one of the first three causes of cancer mortality in Europe. Screening in asymptomatic men (aged 55-69yr) using prostate-specific antigen (PSA) is associated with a migration toward lower staged disease and a reduction in cancer-specific mortality. By 20yr after testing, around 100 men need to be screened to prevent one PCa death. While this ratio is smaller than for breast and colon cancer, the long natural history of PCa means many men die from other causes. As such, the nonselective use of PSA testing and radical treatments can lead to overdiagnosis and overtreatment. The European Association of Urology (EAU) supports measures to encourage appropriate PCa detection through PSA testing, while reducing overdiagnosis and overtreatment. These goals may be achieved using personalized risk-stratified approaches. For diagnosis, the greatest benefit from early detection is likely to come in men assessed using baseline PSA levels at the age of 45yr to individualize screening intervals. Multiparametric magnetic resonance imaging as well as risk calculators based on family history, ethnicity, digital rectal examination, and prostate volume should be considered to triage the need for biopsy, thus reducing the risk of overdiagnosis. For treatment, the EAU advocates balancing patient's life expectancy and cancer's mortality risk when deciding an approach. Active surveillance is encouraged in well-informed patients with low-risk and some intermediate-risk cancers, as it decreases the risks of overtreatment without compromising oncological outcomes. Conversely, the EAU advocates radical treatment in suitable men with more aggressive PCa. Multimodal treatment should be considered in locally advanced or high-grade cancers. PATIENT SUMMARY: Implementation of prostate-specific antigen (PSA)-based screening should be considered at a population level. Men at risk of prostate cancer should have a baseline PSA blood test (eg, at 45yr). The level of this test, combined with family history, ethnicity, and other factors, can be used to determine subsequent follow-up. Magnetic resonance imaging scans and novel biomarkers should be used to determine which men need biopsy and how any cancers should be treated.