The percentage of prostate-specific antigen (PSA) isoform [-2]proPSA and the Prostate Health Index improve the diagnostic accuracy for clinically relevant prostate cancer at initial and repeat biopsy compared with total PSA and percentage free PSA in men aged ≤65 years

Dual-Enhanced SERS Satellite Immuno-Nanocomplex for Multiple PSA-Mediated PHI Assay Toward Clinical Prostate Cancer Screening

Prostate specific antigen (PSA) is widely used in liquid biopsy of prostate cancer (PCa) but still faces challenges due to the poor specificity. Herein, this study reports a double-SERS satellite immunoassay, made of an Au-Ag dealloyed intra-nanogap nanoflower (Au-Ag DINF) with strong SERS signals and Au magnetic nanoparticles (AuMNPs) with magnetic capture and SERS amplification, for sensing multiple PSA (free PSA (fPSA), complexed PSA (cPSA) and [-2]proPSA (p2PSA)) toward potential PCa screening. Unlike the previous studies focus on the tPSA and fPSA/tPSA ratio (f/t PSA%), this work introduces a multiple PSA-mediated Prostate Health Index (PHI) assay with significantly increased the predictive accuracy and specificity of PCa, especially the patients with a tPSA level in the "diagnostic gray zone". Practical analysis of clinical samples demonstrated the SERS immunoassay is capable of identifying the PCa subjects from healthy candidates (N = 13), and monitoring PCa patients before and after surgery (N = 5), as well as screening suspicious ones who are in the "gray zone" (N = 10). Overall, benefiting from the PSA-responsive satellite immuno-nanoassemble strategy, dual-SERS magnification effect, and multiple PSA-based PHI assessment, this proposes bioassay held enormous potential for the early diagnosis, screening, monitoring, and prognosis of PCa.

Prostate cancer theragnostics biomarkers: An update

Biomarkers are molecules such as proteins, genes, or other substances that may be tested to determine the stage of the tumor in a patient. The role of prostate cancer biomarkers is pivotal and the combination of prostate cancer immunotherapy with efficient biomarkers has emerged as a beneficial treatment strategy and its use has increased rapidly. The two primary objectives of this current prostate cancer early detection programs were recognizing non-symptomatic individuals with prostate cancer requiring prostatic core biopsy and identifying men with prostate cancer who might benefit from definitive medical treatment. The progress that has been made so far in the identification of the biomarkers that can be used for the classification, prediction and prognostication of prostate cancer, and as major targets for its clinical intervention has been well summarized in this review.

G-Protein-Coupled Receptor-Associated Sorting Protein 1 Overexpression Is Involved in the Progression of Benign Prostatic Hyperplasia, Early-Stage Prostatic Malignant Diseases, and Prostate Cancer

Background/Objectives: Prostate cancer (PCa) is a prevalent malignancy, necessitating accurate diagnostic methods to distinguish it from benign conditions such as benign prostatic hyperplasia (BPH). Current diagnostic tools, relying primarily on serum prostate-specific antigen (PSA) levels, lack specificity, leading to an over-diagnosis and unnecessary treatment of patients with benign conditions. This study explores G-protein-coupled receptor-associated sorting protein 1 (GASP-1) as a more sensitive biomarker for PCa detection. Methods: Prostate tissue microarrays of healthy, BPH, and prostate cancer patients with different Gleason scores were studied. Polyclonal antibodies targeted against GASP-1 were used for routine immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) analyses. Results: The results indicated a 5-fold difference in serum GASP-1 levels between BPH and PCa, which was validated through GASP-1 IHC. Furthermore, a novel scoring system, the H-score, assesses GASP-1 granules' intensity and size, revealing a clear distinction between BPH and PCa. An additional analysis of GASP-1 expression between PCa cases with different Gleason scores reveals that GASP-1 overexpression correlates with PCa severity, providing insights into disease progression. Conclusions: The study supports GASP-1's role as a promising diagnostic marker, supplementing PSA testing, and offering improved risk stratification for PCa. Additionally, an open-source software system is introduced for an efficient GASP-1 granule color analysis, enhancing diagnostic accuracy.

Prostate cancer risk prediction based on clinical factors and prostate-specific antigen

INTRODUCTION

The incidence rate of prostate cancer (PCa) has continued to rise in Korea. This study aimed to construct and evaluate a 5-year PCa risk prediction model using a cohort with PSA < 10 ng/mL by incorporating PSA levels and individual factors.

METHODS

The PCa risk prediction model including PSA levels and individual risk factors was constructed using a cohort of 69,319 participants from the Kangbuk Samsung Health Study. 201 registered PCa incidences were observed. A Cox proportional hazards regression model was used to generate the 5-year risk of PCa. The performance of the model was assessed using standards of discrimination and calibration.

RESULTS

The risk prediction model included age, smoking status, alcohol consumption, family history of PCa, past medical history of dyslipidemia, cholesterol levels, and PSA level. Especially, an elevated PSA level was a significant risk factor of PCa (hazard ratio [HR]: 1.77, 95% confidence interval [CI]: [1.67-1.88]). This model performed well with sufficient discrimination ability and satisfactory calibration (C-statistic: 0.911, 0.874; Nam-D'Agostino test statistic:19.76, 4.21 in the development and validation cohort, respectively).

CONCLUSIONS

Our risk prediction model was effective in predicting PCa in a population according to PSA levels. When PSA levels are inconclusive, an assessment of both PSA and specific individual risk factors (e.g., age, total cholesterol, and family history of PCa) could provide further information in predicting PCa.

A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer

BACKGROUND

The Prostate Health Index (PHI) and Proclarix (PCLX) have been proposed as blood-based tests for prostate cancer (PCa). In this study, we evaluated the feasibility of an artificial neural network (ANN)-based approach to develop a combinatorial model including PHI and PCLX biomarkers to recognize clinically significant PCa (csPCa) at initial diagnosis.

METHODS

To this aim, we prospectively enrolled 344 men from two different centres. All patients underwent radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/mL. We used an artificial neural network to develop models that can identify csPCa efficiently. As inputs, the model uses [-2]proPSA, freePSA, total PSA, cathepsin D, thrombospondin, and age.

RESULTS

The output of the model is an estimate of the presence of a low or high Gleason score PCa defined at RP. After training on a dataset of up to 220 samples and optimization of the variables, the model achieved values as high as 78% for sensitivity and 62% for specificity for all-cancer detection compared with those of PHI and PCLX alone. For csPCa detection, the model showed 66% (95% CI 66-68%) for sensitivity and 68% (95% CI 66-68%) for specificity. These values were significantly different compared with those of PHI (p < 0.0001 and 0.0001, respectively) and PCLX (p = 0.0003 and 0.0006, respectively) alone.

CONCLUSIONS

Our preliminary study suggests that combining PHI and PCLX biomarkers may help to estimate, with higher accuracy, the presence of csPCa at initial diagnosis, allowing a personalized treatment approach. Further studies training the model on larger datasets are strongly encouraged to support the efficiency of this approach.

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.

Diagnostic and prognostic factors in patients with prostate cancer: a systematic review

OBJECTIVES

As part of the PIONEER Consortium objectives, we have explored which diagnostic and prognostic factors (DPFs) are available in relation to our previously defined clinician and patient-reported outcomes for prostate cancer (PCa).

DESIGN

We performed a systematic review to identify validated and non-validated studies.

DATA SOURCES

MEDLINE, Embase and the Cochrane Library were searched on 21 January 2020.

ELIGIBILITY CRITERIA

Only quantitative studies were included. Single studies with fewer than 50 participants, published before 2014 and looking at outcomes which are not prioritised in the PIONEER core outcome set were excluded.

DATA EXTRACTION AND SYNTHESIS

After initial screening, we extracted data following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of prognostic factor studies (CHARMS-PF) criteria and discussed the identified factors with a multidisciplinary expert group. The quality of the included papers was scored for applicability and risk of bias using validated tools such as PROBAST, Quality in Prognostic Studies and Quality Assessment of Diagnostic Accuracy Studies 2.

RESULTS

The search identified 6604 studies, from which 489 DPFs were included. Sixty-four of those were internally or externally validated. However, only three studies on diagnostic and seven studies on prognostic factors had a low risk of bias and a low risk concerning applicability.

CONCLUSION

Most of the DPFs identified require additional evaluation and validation in properly designed studies before they can be recommended for use in clinical practice. The PIONEER online search tool for DPFs for PCa will enable researchers to understand the quality of the current research and help them design future studies.

ETHICS AND DISSEMINATION

There are no ethical implications.

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.

Early prediction of prostate cancer biochemical recurrence and identification of disease persistence using PSA isoforms and human kallikrein-2

BACKGROUND

The role of isoforms of prostate specific antigen (PSA) and other kallikrein-related markers in early detection of biochemical recurrence (BCR) after radical prostatectomy (RP) is not well known and serum PSA is currently used in preoperative risk nomograms.

OBJECTIVE

The aim of this research was to study pre- and early postoperative levels of important PSA isoforms and human kallikrein-2 to determine their ability to predict BCR and identify disease persistence (DP).

METHODS

This study included 128 consecutive patients who underwent RP for clinically localized prostate cancer. PSA, fPSA, %fPSA, [-2]proPSA, PHI and hK2 were measured preoperatively, at 1 and 3 months after RP. We determined the ability of these markers to predict BCR and identify DP.

RESULTS

The DP and BCR rate were 11.7%and 20.3%respectively and the median follow up was 64 months (range 3-76 months). Preoperatively, the independent predictors of BCR were PSA (p-value 0.029), [-2]proPSA (p-value 0.002) and PHI (p-value 0.0003). Post-RP, PSA was the single marker correlating with BCR, both at one (p-value 0.0047) and 3 months (p-value 0.0004). PSA, fPSA, [-2]proPSA and PHI significantly correlated to DP at 1 and 3 months post-RP (p-value <  0.05), although PSA had the most significant existing correlation (p-value <  0.0001).

CONCLUSIONS

[-2]proPSA and PHI are preoperative predictors of BCR and DP that outperform the currently used serum PSA. At the early postoperative period there is no additional benefit of the other markers tested.

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.

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.

Prostate Cancer Liquid Biopsy Biomarkers' Clinical Utility in Diagnosis and Prognosis

Prostate cancer (PCa) is the most common cancer in men worldwide. The current gold standard for diagnosing PCa relies on a transrectal ultrasound-guided systematic core needle biopsy indicated after detection changes in a digital rectal examination (DRE) and elevated prostate-specific antigen (PSA) level in the blood serum. PSA is a marker produced by prostate cells, not just cancer cells. Therefore, an elevated PSA level may be associated with other symptoms such as benign prostatic hyperplasia or inflammation of the prostate gland. Due to this marker's low specificity, a common problem is overdiagnosis, which leads to unnecessary biopsies and overtreatment. This is associated with various treatment complications (such as bleeding or infection) and generates unnecessary costs. Therefore, there is no doubt that the improvement of the current procedure by applying effective, sensitive and specific markers is an urgent need. Several non-invasive, cost-effective, high-accuracy liquid biopsy diagnostic biomarkers such as Progensa PCA3, MyProstateScore ExoDx, SelectMDx, PHI, 4K, Stockholm3 and ConfirmMDx have been developed in recent years. This article compares current knowledge about them and their potential application in clinical practice.

Correlation between Gleason score distribution and Prostate Health Index in patients with prostate-specific antigen values of 2.5-10 ng/mL

Purpose

To determine the clinical significance and correlation between the Prostate Health Index (PHI) and Gleason score in patients with a prostate-specific antigen (PSA) value of 2.5–10 ng/mL.

Materials and Methods

This retrospective analysis included 114 patients who underwent biopsy after completion of the PHI from November 2018 to July 2019. Various parameters such as PSA, PHI, PSA density, free PSA, p2PSA, and %free PSA were collected, and correlations with biopsy Gleason score and cancer detection rates were investigated.

Results

Baseline characteristics were comparable between PHI groups (0–26.9 [n=11], 27.0–35.9 [n=17], 36.0–54.9 [n=50], and ≥55.0 [n=36]). A total of 37 patients (32.5%) were diagnosed with prostate cancer, and 28 (24.6%) were diagnosed with clinically significant prostate cancer (CSPC, Gleason score ≥7) after prostate biopsy. The cancer detection rate gradually increased with a corresponding increase in the PHI (18%, 24%, 30%, and 44%, respectively). The same pattern was observed with detecting CSPC (0%, 18%, 26%, and 33%, respectively). There was no CSPC in the groups with PHI <27.0, and Gleason score 7 began to appear in groups with PHI ≥27.0. In particular, patients with Gleason score 8 and 9 were distributed only in the groups with PHI ≥36.0.

Conclusions

The diagnostic accuracy of detection of CSPC could be increased when prostate biopsy is performed in patients with a PHI ≥36.0. In this study, there was a clear Gleason score difference when the PHI cutoff value was set to 27.0 or 36.0.

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.

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.

The emerging landscape of tumor marker panels for the identification of aggressive prostate cancer: the perspective through bibliometric analysis of an Italian translational working group in uro-oncology

Molecular heterogeneity and availability of different therapeutic strategies are relevant clinical features of prostate cancer. On this basis, there is an urgent need to identify prognostic and predictive biomarkers for an individualized therapeutic approach. In this context, researchers focused their attention on biomarkers able to discriminate potential life-threatening from organ-confined disease. Such biomarker could provide aid in clinical decision making, helping to choose the treatment which ensures the best results in terms of patient survival and quality of life. To address this need, many new laboratory tests have been proposed, with a clear tendency to use panels of combined biomarkers. In this review we evaluate current data on the application in clinical practice of the most promising laboratory tests: Phi, 4K score and Stockholm 3 as circulating biomarkers, Mi-prostate score, Exo DX Prostate and Select MD-X as urinary biomarkers, Confirm MDx, Oncotype Dx, Prolaris and Decipher as tissue biomarkers. In particular, the ability of these tests in the identification of clinically significant PCa and their potential use for precision medicine have been explored in this review.

Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model

After skin cancer, prostate cancer (PC) is the most common cancer among men. The gold standard for PC diagnosis is based on the PSA (prostate-specific antigen) test. Based on this preliminary screening, the physician decides whether to proceed with further tests, typically prostate biopsy, to confirm cancer and evaluate its aggressiveness. Nevertheless, the specificity of the PSA test is suboptimal and, as a result, about 75% of men who undergo a prostate biopsy do not have cancer even if they have elevated PSA levels. Overdiagnosis leads to unnecessary overtreatment of prostate cancer with undesirable side effects, such as incontinence, erectile dysfunction, infections, and pain. Here, we used artificial neuronal networks to develop models that can diagnose PC efficiently. The model receives as an input a panel of 4 clinical variables (total PSA, free PSA, p2PSA, and PSA density) plus age. The output of the model is an estimate of the Gleason score of the patient. After training on a dataset of 190 samples and optimization of the variables, the model achieved values of sensitivity as high as 86% and 89% specificity. The efficiency of the method can be improved even further by training the model on larger datasets.

Diagnostic and prognostic factors in patients with prostate cancer: a systematic review protocol

INTRODUCTION

As part of the PIONEER (Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe) Consortium, we will explore which diagnostic and prognostic factors (DPFs) are currently being researched to previously defined clinical and patient-reported outcomes for prostate cancer (PCa).

METHODS AND ANALYSIS

This research project will follow the following four steps: (1) a broad systematic literature review of DPFs for all stages of PCa, covering evidence from 2014 onwards; (2) discussion of systematic review findings by a multidisciplinary expert panel; (3) risk of bias assessment and applicability with Prediction model Risk Of Bias Assessment Tool criteria, Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Quality In Prognosis Studies tool (QUIPS) and (4) additional quantitative assessments if required.

ETHICS AND DISSEMINATION

We aim to develop an online tool to present the DPFs identified in this research and make them available across all stakeholders. There are no ethical implications.

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.

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%.

Modern biomarkers in prostate cancer diagnosis

INTRODUCTION

The most common malignant neoplasm of the urinary tract is prostate cancer (PCa), which is a heterogeneous disease, ranging from very slowly developing and slightly benign to progressing, aggressive, metastatic and fatal, even when properly treated. Existing, imperfect diagnostic methods often lead to over-diagnosis and over-treatment of PCa. That is why new, better PCa biomarkers are being developed.

MATERIAL AND METHODS

This review summarizes the current results of the most promising and clinically used PCa biomarkers, as well as having the potential to create new diagnostic and prognostic tools, based on the Web of Science (www.apps.webofknowledge.com) and Scopus (www.scopus) databases. com).

RESULTS

Limited specificity of the prostate-specific antigen (PSA) test brings a need to develop new and better diagnostic tools. In the last few years, new approaches for providing significantly better biomarkers, an alternative to PSA, have been introduced. Modern biomarkers show improvement in being used as not only a diagnostic procedure, but also for staging, evaluating aggressiveness and managing the therapeutic process. We describe the methods recommended in the diagnosis of PCa and new PCa molecular diagnostics technologies. Individual biomarkers are used in various stages of the PCa diagnostic process, which was presented on the developed diagnostic flowchart describing the role of biomarkers in prostate cancer management.

CONCLUSIONS

Given the diverse nature of PCa, one diagnostic test will not answer all questions, so the use of several diagnostic methods will allow physicians to provide patients with better, personalized clinical advice.

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.

Clinical Applications of Molecular Biomarkers in Prostate Cancer

There is clinically relevant molecular heterogeneity in prostate cancer (PCa), but this biological diversity has had only a minimal impact on clinical practice. Treatment outcomes in patients with localised PCa are often highly variable, even among patients stratified to the same risk group or disease state based on standard clinical and pathological parameters. In recent years, the development of gene panels has provided valuable data on the differential expression of genes in patients with PCa. Nevertheless, there is an urgent need to identify and validate prognostic and predictive biomarkers that can be applied across clinical scenarios, ranging from localised disease to metastatic castration-resistant PCa. The availability of such tools would allow for precision medicine to finally reach PCa patients. In this review, we evaluate current data on molecular biomarkers for PCa, with an emphasis on the biomarkers and gene panels with the most robust evidence to support their application in routine clinical practice.

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.

Use of the Prostate Health Index and Density in 3 Outpatient Centers to Avoid Unnecessary Prostate Biopsies

OBJECTIVES

We investigated the diagnostic efficacy of the prostate health index (PHI) and PHI density (PHID) to avoid unnecessary prostate biopsies in 3 urological practices.

METHODS

In 122 patients, total prostate-specific antigen (PSA), free PSA (f-PSA), the quotient from total PSA and f-PSA (f-PSA%), and [-2]pro-PSA were measured in the serum; PHI, PHID, and PSA density (PSAD) were calculated prior to prostate biopsy. Tissue sampling via transrectal biopsy was indicated in case of suspicious PSA (progression and/or elevation of PSA) and/or suspicious digital rectal examination. PSAD, PHI, and PHID were not used for biopsy indication. The diagnostic efficacy was determined with receiver-operating characteristic (ROC)and decision curve analyses.

RESULTS

Based on prostate biopsies, 38% (n = 46) of the cases had no prostate carcinoma (PCa), 21% (n = 26) no clinically significant (insignificant) PCa, and 41% (n = 50) had clinically significant PCa. ROC analyses of the PSA parameters showed higher diagnostic efficacy for PHI and PHID (AUC 0.722 and 0.739) than for f-PSA%, PSA, and PSAD (AUC 0.612, 0.595, and 0.698, respectively) regarding carcinoma diagnosis. With a combined use of PHI and PHID (cutoff >40 and >0.9, respectively), only 1 clinically significant PCa would have been missed (sensitivity 98%); in 24 (20%) patients, biopsy could have been avoided.

CONCLUSION

The integration of PHI and PHID could improve the diagnostic efficacy of risk calculators to avoid unnecessary prostate biopsies. However, as a prerequisite, validation of cutoff values in prospective studies is urgently required.

A predictive model for prostate cancer incorporating PSA molecular forms and age

The diagnostic specificity of prostate specific antigen (PSA) is limited. We aimed to characterize eight anti-PSA monoclonal antibodies (mAbs) to assess the prostate cancer (PCa) diagnostic utility of different PSA molecular forms, total (t) and free (f) PSA and PSA complexed to α₁-antichymotrypsin (complexed PSA). MAbs were obtained by immunization with PSA and characterized by competition studies, ELISAs and immunoblotting. With them, we developed sensitive and specific ELISAs for these PSA molecular forms and measured them in 301 PCa patients and 764 patients with benign prostate hyperplasia, and analyzed their effectiveness to discriminate both groups using ROC curves. The free-to-total (FPR) and the complexed-to-total PSA (CPR) ratios significantly increased the diagnostic yield of tPSA. Moreover, based on model selection, we constructed a multivariable logistic regression model to predictive PCa that includes tPSA, fPSA, and age as predictors, which reached an optimism-corrected area under the ROC curve (AUC) of 0.86. Our model outperforms the predictive ability of tPSA (AUC 0.71), used in clinical practice. In conclusion, The FPR and CPR showed better diagnostic yield than tPSA. In addition, the PCa predictive model including age, fPSA and complexed PSA, outperformed tPSA detection efficacy. Our model may avoid unnecessary biopsies, preventing harmful side effects and reducing health expenses.

External validation of Cormio nomogram for predicting all prostate cancers and clinically significant prostate cancers

PURPOSE

Recently, the Cormio et al. nomogram has been developed to predict prostate cancer (PCa) and clinically significant PCa using benign prostatic obstruction parameters. The aim of the present study was to externally validate the nomogram in a multicentric cohort.

METHODS

Between 2013 and 2019, patients scheduled for ultrasound-guided prostate biopsy were prospectively enrolled at 11 Italian institutions. Demographic, clinical and histological data were collected and analysed. Discrimination and calibration of Cormio nomogram were assessed with the receiver operator characteristics (ROC) curve and calibration plots. The clinical net benefit of the nomogram was assessed with decision curve analysis. Clinically significant PCa was defined as ISUP grade group > 1.

RESULTS

After accounting for inclusion criteria, 1377 patients were analysed. 816/1377 (59%) had cancer at final pathology (574/816, 70%, clinically significant PCa). Multivariable analysis showed age, prostate volume, DRE and post-voided residual volume as independent predictors of any PCa. Discrimination of the nomogram for cancer was 0.70 on ROC analysis. Calibration of the nomogram was excellent (p = 0.94) and the nomogram presented a net benefit in the 40-80% range of probabilities. Multivariable analysis for predictors of clinically significant PCa found age, PSA, prostate volume and DRE as independent variables. Discrimination of the nomogram was 0.73. Calibration was poor (p = 0.001) and the nomogram presented a net benefit in the 25-75% range of probabilities.

CONCLUSION

We confirmed that the Cormio nomogram can be used to predict the risk of PCa in patients at increased risk. Implementation of the nomogram in clinical practice will better define its role in the patient's counselling before prostate biopsy.

What chance do we have to decrease prostate cancer overdiagnosis and overtreatment? A narrative review

In the era of biochemical tests and algorithms, the management of prostate cancer from prevention to treatment is still controversial. The debate is focused on clinically-significant and clinically-insignificant prostate cancer. As it is well known, the diagnostic tools available are not able to distinguish between the two, thus leading to men treated for prostate cancer even if not strictly necessary. Unfortunately, as of today, there is no test available able to predict the clinical aggressiveness of prostate cancer at the time of the diagnosis. However, some indexes, PSA derivatives, immunocomplexes, and diagnostic methods have been proposed. If properly used in the daily clinical practice, these tools may be of support in the decision making process, in the effort to reduce the overdiagnosis and the overtreatment of prostate cancer.For this reason, we believe that a clear knowledge of this tools, indexes and diagnostic methods is of the utmost importance in preventing the morbidities related to unnecessary treatment as weel as preventing the detrimental effect of missing the diagnosis of a clinically significant prostate cancer.This reviews encompasses the most studied tests and diagnostic methods to predict the aggressiveness of prostate cancer, to avoid to miss a diagnosis of clinically significant cancers and to optimize the overall pre-treatment work-up. (www.actabiomedica.it).

Prediction Medicine: Biomarkers, Risk Calculators and Magnetic Resonance Imaging as Risk Stratification Tools in Prostate Cancer Diagnosis

This review discusses the most recent evidence for currently available risk stratification tools in the detection of clinically significant prostate cancer (csPCa), and evaluates diagnostic strategies that combine these tools. Novel blood biomarkers, such as the Prostate Health Index (PHI) and 4Kscore, show similar ability to predict csPCa. Prostate cancer antigen 3 (PCA3) is a urinary biomarker that has inferior prediction of csPCa compared to PHI, but may be combined with other markers like TMPRSS2-ERG to improve its performance. Original risk calculators (RCs) have the advantage of incorporating easy to retrieve clinical variables and being freely accessible as a web tool/mobile application. RCs perform similarly well as most novel biomarkers. New promising risk models including novel (genetic) markers are the SelectMDx and Stockholm-3 model (S3M). Prostate magnetic resonance imaging (MRI) has evolved as an appealing tool in the diagnostic arsenal with even stratifying abilities, including in the initial biopsy setting. Merging biomarkers, RCs and MRI results in higher performances than their use as standalone tests. In the current era of prostate MRI, the way forward seems to be multivariable risk assessment based on blood and clinical parameters, potentially extended with information from urine samples, as a triaging test for the selection of candidates for MRI and biopsy.

Diagnostic accuracy of the [-2]Pro-PSA and Prostate Health Index versus the Gleason score for determining the aggressiveness of prostate cancer: a systematic review protocol

REVIEW QUESTIONS.

Carbon Footprint in Flexible Ureteroscopy: A Comparative Study on the Environmental Impact of Reusable and Single-Use Ureteroscopes

PURPOSE

There are no comparative assessments on the environmental impact of endourologic instruments. We evaluated and compared the environmental impact of single-use flexible ureteroscopes with reusable flexible ureteroscopes.

PATIENTS AND METHODS

An analysis of the typical life cycle of the LithoVue™ (Boston Scientific) single-use digital flexible ureteroscope and Olympus Flexible Video Ureteroscope (URV-F) was performed. To measure the carbon footprint, data were obtained on manufacturing of single-use and reusable flexible ureteroscopes and from typical uses obtained with a reusable scope, including repairs, replacement instruments, and ultimate disposal of both ureteroscopes. The solid waste generated (kg) and energy consumed (kWh) during each case were quantified and converted into their equivalent mass of carbon dioxide (kg of CO₂) released.

RESULTS

Flexible ureteroscopic raw materials composed of plastic (90%), steel (4%), electronics (4%), and rubber (2%). The manufacturing cost of a flexible ureteroscope was 11.49 kg of CO₂ per 1 kg of ureteroscope. The weight of the single-use LithoVue and URV-F flexible ureteroscope was 0.3 and 1 kg, respectively. The total carbon footprint of the lifecycle assessment of the LithoVue was 4.43 kg of CO₂ per endourologic case. The total carbon footprint of the lifecycle of the reusable ureteroscope was 4.47 kg of CO₂ per case.

CONCLUSION

The environmental impacts of the reusable flexible ureteroscope and the single-use flexible ureteroscope are comparable. Urologists should be aware that the typical life cycle of urologic instruments is a concerning source of environmental emissions.

New biomarkers for diagnosis and prognosis of localized prostate cancer

The diagnostics and management of localized prostate cancer is complicated because of cancer heterogeneity and differentiated progression in various subgroups of patients. As a prostate cancer biomarker, FDA-approved detection assay for serum prostate specific antigen (PSA) and its derivatives are not potent enough to diagnose prostate cancer, especially high-grade disease (Gleason ≥7). To date, a collection of new biomarkers was developed. Some of these markers are superior for primary screening while others are particularly helpful for cancer risk stratification, detection of high-grade cancer, and prediction of adverse events. Two of those markers such as proPSA (a part of the Prostate Health Index (PHI)) and prostate specific antigen 3 (PCA3) (a part of the PCA3 Progensa test) were recently approved by FDA for clinical use. Other markers are not PDA-approved yet but are available from Clinical Laboratory Improvement Amendment (CLIA)-certified clinical laboratories. In this review, we characterize diagnostic performance of these markers and their diagnostic and prognostic utility for prostate cancer.

Prostate Cancer Markers

Diagnostic biomarkers derived from blood, urine, or prostate tissue provide additional information beyond clinical calculators to determine the risk of detecting high-grade prostate cancer. Once diagnosed, multiple markers leverage prostate cancer biopsy tissue to prognosticate clinical outcomes, including adverse pathology at radical prostatectomy, disease recurrence, and prostate cancer mortality; however the clinical utility of some outcomes to patient decision making is unclear. Markers using tissue from radical prostatectomy specimens provide additional information about the risk of biochemical recurrence, development of metastatic disease, and subsequent mortality beyond existing multivariable clinical calculators (the use of a marker to simply sub-stratify risk groups such as the NCCN groups is of minimal value). No biomarkers currently available for prostate cancer have been prospectively validated to be predict an improved clinical outcome for a specific therapy based on the test result; however, further research and development of these tests may produce a truly predictive biomarker for prostate cancer treatment.

Clinical utility of the Prostate Health Index (phi) for biopsy decision management in a large group urology practice setting

Background

Deciding when to biopsy a man with non-suspicious DRE findings and tPSA in the 4–10 ng/ml range can be challenging, because two-thirds of such biopsies are typically found to be benign. The Prostate Health Index (phi) exhibits significantly improved diagnostic accuracy for prostate cancer detection when compared to tPSA and %fPSA, however only one published study to date has investigated its impact on biopsy decisions in clinical practice.

Methods

An IRB approved observational study was conducted at four large urology group practices using a physician reported two-part questionnaire. Physician recommendations were recorded before and after receiving the phi test result. A historical control group was queried from each site's electronic medical records for eligible men who were seen by the same participating urologists prior to the implementation of the phi test in their practice. 506 men receiving a phi test were prospectively enrolled and 683 men were identified for the historical control group (without phi). Biopsy and pathological findings were also recorded for both groups.

Results

Men receiving a phi test showed a significant reduction in biopsy procedures performed when compared to the historical control group (36.4% vs. 60.3%, respectively, P < 0.0001). Based on questionnaire responses, the phi score impacted the physician’s patient management plan in 73% of cases, including biopsy deferrals when the phi score was low, and decisions to perform biopsies when the phi score indicated an intermediate or high probability of prostate cancer (phi ≥36).

Conclusions

phi testing significantly impacted the physician’s biopsy decision for men with tPSA in the 4–10 ng/ml range and non-suspicious DRE findings. Appropriate utilization of phi resulted in a significant reduction in biopsy procedures performed compared to historical patients seen by the same participating urologists who would have met enrollment eligibility but did not receive a phi test.

Validity of Prostate Health Index and Percentage of [-2] Pro-Prostate-Specific Antigen as Novel Biomarkers in the Diagnosis of Prostate Cancer: Omani Tertiary Hospitals Experience

OBJECTIVES

Prostate cancer is the leading cancer in older men. The Ministry of Health Oman Cancer Incidence Registry 2013 lists cancer of the prostate as the first most common cancer in males. Therefore, early detection is important and prostate-specific antigen (PSA) is widely used as an established laboratory test. However, despite its wide use, its value in screening, particularly in asymptomatic males, is controversial when considering the risks and benefits of early detection.

METHODS

This prospective, observational study included 136 males (67.0±8.9 years; range 45-90) who were scheduled for a prostate biopsy in two different tertiary care teaching hospitals in Oman: the Royal Hospital and Sultan Qaboos University Hospital. Blood specimens from these patients were collected at the same setting before obtaining a prostatic biopsy. Three PSA markers (total PSA (tPSA), free PSA (fPSA), and [-2]proPSA (p2PSA)) were measured and the Prostate Health Index (phi) calculated. The histopathological report of the prostatic biopsy for each patient was obtained from the histopathology laboratory of the concerned hospital along with clinical and laboratory data through the hospital information system.

RESULTS

Phi has the highest validity markers compared with other prostate markers, with a sensitivity of 82.1%, specificity of 80.6%, and area under the curve (AUC) value of 0.81 at a cutoff of 41.9. The other prostatic markers showed sensitivities and specificities of 78.6% and 25.9% for tPSA; 35.7% and 92.6% for %fPSA; and 64.3% and 82.4% for %p2PSA, respectively. The AUCs at the best cutoff values were 0.67 at 10.1 µg/L for tPSA; 0.70 at 11.6% for %fPSA; and 0.55 at 1.4% for %p2PSA. An association between phi values and aggressiveness of prostate malignancy was noted. Of the 28 patients with prostate cancer, 22 patients had tPSA > 4 µg/L. However, no patient had phi in the low-risk category, and five, six, and 17 patients had phi in the moderate-, high-, and very high-risk categories, respectively.

CONCLUSIONS

Phi outperforms tPSA and fPSA when used alone or in combination, and appears to be more accurate than both markers in excluding prostate cancer before biopsy. Use of this biomarker helps clinicians to avoid unnecessary biopsies, particularly in patients with gray-zone tPSA level. Phi is the strongest marker that correlates proportionally with Gleason Score; therefore, it is also useful in predicting the aggressiveness of the disease. This is the first reported experience for the use of p2PSA and phi in Oman, the Middle East, and North Africa.

Cost consideration in utilization of multiparametric magnetic resonance imaging in prostate cancer

The screening, evaluation and management of prostate cancer changed significantly in the last decade. The recommendations regarding prostate cancer screening continue to evolve with new revelations about existing data sets and longer followup of landmark trials. Robotics has gained the vast majority of the marketplace for surgically managed prostate cancer in rapid fashion. The need for intervention in low risk prostate cancer has been closely examined and more men are being expectantly managed than ever before. Amidst all these changes, prostate magnetic resonance imaging (MRI) has emerged as a disruptive technology. Through the use of dynamic contrast-enhanced and diffusion weighted series, prostate tumors that were previously not visible have become identifiable and quantifiable. The ability of MRI to improve staging and identification of clinically significant disease has resulted in increased utilization for different aspects of prostate cancer care. The best studied use is in men with a prior negative transrectal ultrasound guided (TRUS) prostate biopsy and the performance characteristics in this role match well with the clinical question raised. The role for MRI in initial biopsy, in pre-surgical planning before prostatectomy and in men on active surveillance is less well defined. A primary concern in the use of MRI is that of cost. MRI units are expensive, both in initial outlay and ongoing use. The availability of MRI varies widely between countries and even within regions of the same country. Different healthcare models have different approaches for allocating the use of expensive resources, including MRI, in times when they are scarce. Prostate MRI can be used at multiple points in the management algorithm of prostate cancer and each implies different cost concerns. In this review we present an overview of current research in cost and cost efficacy for the use of MRI in the management of prostate cancer. By examining what is known and highlighting areas of ongoing research we hope to provide the reader with a solid foundation for understanding these complex, ever-changing issues.

The role of prostate cancer biomarkers in undiagnosed men

PURPOSE OF REVIEW

This article intends to review biomarkers derived from blood, urine, and tissue that can aid in the diagnosis of prostate cancer (PCa).

RECENT FINDINGS

PCa screening requires tools that complement prostate-specific antigen (PSA) with a higher specificity for clinically significant disease. Novel blood biomarkers, such as the Prostate Health Index (phi) and 4Kscore, utilize isoforms of PSA to more accurately predict high-grade PCa than traditional tools such as PSA and the percentage free-to-total PSA. Several gene products associated with PCa can be detected in the urine through commercially available assays. PCa antigen 3 (PCA3), though approved for repeat biopsy decisions, appears inferior to other biomarkers such as phi for identifying aggressive disease. However, combinations of PCA3 with other urine assays have shown promising results. One tissue-based hypermethylation test, named ConfirmMDx, can also be used to determine the need for repeat biopsy in men with a prior negative biopsy.

SUMMARY

Several biomarkers have been developed to aid in the screening and diagnosis of PCa. Such tests are often indicated in men with moderately elevated PSA or history of a prior negative biopsy. Their use facilitates reduction of unnecessary biopsies without sacrificing the early diagnosis of clinically significant PCa.

Balancing Overdiagnosis and Early Detection of Prostate Cancer using the Stockholm-3 Model

The S3M (Stockholm-3 Model) test improves discrimination for high-grade (Gleason score ≥ 7) prostate cancer compared with prostate-specific antigen (PSA) testing. Published results from the Stockholm-3 study represent a snapshot of possible outcomes for prostate cancer detection using the S3M test. In this brief report, we show how the full range of cancer detection rates and percent saved biopsies depend on the chosen S3M cut-off for recommending prostate biopsy. Using data from the Stockholm-3 validation cohort (n=47 688), we calculated the cancer detection rates and percent saved biopsies for various S3M test cut-offs in men with PSA ≥1ng/ml. Cancer detection rates decline and fewer prostate biopsies have to be performed with increasing test cut-offs. Primarily, S3M test values between 7% and 14% can be considered for biopsy decision cut-offs (10% risk of Gleason score ≥ 7 corresponds to PSA=3 ng/ml); the exact cutoff can be chosen to fit different healthcare systems and, indeed, individual men. PATIENT SUMMARY: The Stockholm-3 Model test improves the detection of high-grade prostate cancer compared with prostate-specific antigen. In this brief report, we show how the cut-off used for recommending prostate biopsies affects the number of detected cancers and performed biopsies. The exact cut-off used can be chosen to fit different individuals and healthcare systems.

Clinical Utility of Biomarkers in Localized Prostate Cancer

A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emerging tests, with attention on studies addressing clinical utility.

Clarifying the PSA grey zone: The management of patients with a borderline PSA

INTRODUCTION

Prostate specific antigen is a marker for prostate cancer and a key diagnostic tool, yet when to refer patients with a borderline PSA is currently unclear. This review describes how to assess a patient with borderline PSA and provides an algorithm for management.

METHODS

Current literature on reference values, factors affecting PSA, indications for referral, non-invasive investigations and the role of MRI were reviewed. Medline and EMBASE were searched using MeSH terms.

RESULTS

The literature suggests that a PSA of over 1.5 ng/mL should be used as a cut-off to consider further testing for all age groups. There is strong evidence to show that adjuncts are useful when interpreting PSA results, most notably percentage free PSA and proPSA. Considerable weighting should also be given to the ERSPC risk calculator when deciding when to refer. Multi-parametric MRI is valuable in closely examining suspicious lesions to reduce the number of negative biopsies. MRI fusion biopsy (TRUS, transrectal ultrasonography or transperineal) should be considered over standard TRUS biopsy to detect more clinically significant disease.

CONCLUSIONS

Management of borderline PSA is not straightforward. A cut-off of 1.5 ng/mL should be used in conjunction with digital rectal exam, risk calculation and PSA adjuncts. Imaging and biopsy should utilise mpMRI to achieve improved diagnosis of clinically significant prostate cancer, with fewer unnecessary investigations.

The Prostate Health Index adds predictive value to multi-parametric MRI in detecting significant prostate cancers in a repeat biopsy population

Both multi-parametric MRI (mpMRI) and the Prostate Health Index (PHI) have shown promise in predicting a positive biopsy in men with suspected prostate cancer. Here we investigated the value of combining both tests in men requiring a repeat biopsy. PHI scores were measured in men undergoing re-biopsy with an mpMRI image-guided transperineal approach (n = 279, 94 with negative mpMRIs). The PHI was assessed for ability to add value to mpMRI in predicting all or only significant cancers (Gleason ≥7). In this study adding PHI to mpMRI improved overall and significant cancer prediction (AUC 0.71 and 0.75) compared to mpMRI + PSA alone (AUC 0.64 and 0.69 respectively). At a threshold of ≥35, PHI + mpMRI demonstrated a NPV of 0.97 for excluding significant tumours. In mpMRI negative men, the PHI again improved prediction of significant cancers; AUC 0.76 vs 0.63 (mpMRI + PSA). Using a PHI≥35, only 1/21 significant cancers was missed and 31/73 (42%) men potentially spared a re-biopsy (NPV of 0.97, sensitivity 0.95). Decision curve analysis demonstrated clinically relevant utility of the PHI across threshold probabilities of 5-30%. In summary, the PHI adds predictive performance to image-guided detection of clinically significant cancers and has particular value in determining re-biopsy need in men with a negative mpMRI.

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes

New markers based on PSA isoforms have recently been developed to improve prostate cancer (PCa) diagnosis. However, novel approaches are still required to differentiate aggressive from non-aggressive PCa to improve decision making for patients.

PSA glycoforms have been shown to be differentially expressed in PCa. In particular, changes in the extent of core fucosylation and sialylation of PSA N-glycans in PCa patients compared to healthy controls or BPH patients have been reported. The objective of this study was to determine these specific glycan structures in serum PSA to analyze their potential value as markers for discriminating between BPH and PCa of different aggressiveness.

In the present work, we have established two methodologies to analyze the core fucosylation and the sialic acid linkage of PSA N-glycans in serum samples from BPH (29) and PCa (44) patients with different degrees of aggressiveness. We detected a significant decrease in the core fucose and an increase in the α2,3-sialic acid percentage of PSA in high-risk PCa that differentiated BPH and low-risk PCa from high-risk PCa patients. In particular, a cut-off value of 0.86 of the PSA core fucose ratio, could distinguish high-risk PCa patients from BPH with 90% sensitivity and 95% specificity, with an AUC of 0.94. In the case of the α2,3-sialic acid percentage of PSA, the cut-off value of 30% discriminated between high-risk PCa and the group of BPH, low-, and intermediate-risk PCa with a sensitivity and specificity of 85.7% and 95.5%, respectively, with an AUC of 0.97. The latter marker exhibited high performance in differentiating between aggressive and non-aggressive PCa and has the potential for translational application in the clinic.