A multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer

Consistent predictive ability of prostate-specific antigen density prediction model for clinically significant prostate cancer across age strata

BACKGROUND

Prebiopsy prostate-specific antigen density (PSAD) is a well-known predictor of clinically significant prostate cancer (csPCa). Since prostate-specific antigen (PSA) and prostate volume (PV) increase normally with aging, PSAD thresholds may vary. The purpose of the study was to determine if PSAD was predictive of csPCa in different age strata.

METHODS

We retrospectively reviewed our institutional database for patients who underwent multiparametric magnetic resonance imaging (MRI) between January 2016 and December 2021. We included patients who had post-MRI prostate biopsies. Based on age, we divided our cohort into four subgroups (groups 1-4): <55, 55-64, 65-74, and ≥75 years old. PSAD accuracy was estimated by the area under the curve (AUC) as a predictive model for differentiating csPCa between the groups. CsPCa was defined as a Gleason Grade Group 2 or higher. Three different PSAD thresholds (0.1, 0.15, and 0.2) were tested across the groups for sensitivity, specificity, and positive predictive value (PPV) and negative predictive value (NPV). Chi-square and analysis of variance tests were used for bivariate analysis. All analys were completed using R 4.3 (R Core Team, 2023).

RESULTS

Among 1913 patients, 883 (46.1%) had prostate biopsies. In groups 1, 2, 3, and 4, there were 62 (7%), 321 (36.4%), 404 (45.8%), and 96 (10.9%) patients, respectively. Median PSA was 5.6 (interquartile range 3.4-8.1), 6.2 (4.8-9), 6.8 (5.1-9.7), and 9 (5.6-13), respectively (p < 0.01). Median PV was 42.3 (30-62), 51 (36-77), 55.5 (38-85.9), and 59.3 (42-110) mL, respectively (p < 0.01). No difference was observed in median PSAD between age groups 1-4 (0.1 [0.07-0.16], 0.11 [0.08-0.18], 0.1 [0.07-0.19], and 0.1 [0.07-0.2]), respectively (p = 0.393). CsPCa was diagnosed in 241 (27.3%) patients, of which 10 (16.1%), 65 (20.2%), 121 (30%), and 45 (46.7%) were in groups 1-4, respectively (p < 0.001). For groups 1-4, the PSAD AUC for predicting csPCa was 0.75, 0.68, 0.71, and 0.74. While testing PSAD threshold of 0.15 across the different age groups (1-4), the PPV vs. NPV was 39.1 vs. 93.2, 33.6 vs. 87, 50.9 vs. 80.8, and 66.1 vs. 64.7, respectively.

CONCLUSIONS

PSAD prediction model was found to be similar among different age groups. In young patients, PSAD had a high NPV but low PPV. With increasing age, the opposite trend was observed, likely due to higher disease prevalence. While PSAD thresholds may be less useful in older patients to rule out higher-grade prostate cancer, the clinical consequences of these diagnoses require a case-by-case evaluation.

Established and emerging liquid biomarkers for prostate cancer detection: A review

Prostate cancer remains one of the most frequently diagnosed cancers among men in the world today. Since its introduction in 1987 and FDA approval in 1994, prostate specific antigen (PSA) has reduced prostate cancer specific mortality considerably. However, the positive and negative predictive value of PSA is less than ideal and can lead to the over-detection of clinically insignificant prostate cancer. In the search for better screening measures to identify this cohort, liquid biomarkers for prostate cancer have emerged. In this review we will explore the commonly used urine and blood based prostate cancer liquid biomarkers. We detail the mechanism of each test and the validation studies that underscore their efficacy. Additionally, we will examine each test's effect on shared decision making as well as their cost efficacy in clinical practice.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer

Importance

Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater).

Objective

To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers.

Design, Setting, and Participants

RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023.

Exposure

Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy.

Main Outcomes and Measures

Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily.

Results

Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater.

Conclusions and Relevance

In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Prostate cancer screening in Switzerland: a literature review and consensus statement from the Swiss Society of Urology

Over a decade ago, the United States Preventive Services Taskforce (USPSTF) recommended against prostate-specific antigen (PSA)-based screening for prostate cancer in all men, which considerably influenced prostate cancer screening policies worldwide after that. Consequently, the world has seen increasing numbers of advanced stages and prostate cancer deaths, which later led the USPSTF to withdraw its initial statement. Meanwhile, the European Union has elaborated a directive to address the problem of implementing prostate cancer screening in "Europe's Beating Cancer Plan". In Switzerland, concerned urologists formed an open Swiss Prostate Cancer Screening Group to improve the early detection of prostate cancer. On the 20th of September 2023, during the annual general assembly of the Swiss Society of Urology (SGU/SSU) in Lausanne, members positively voted for a stepwise approach to evaluate the feasibility of implementing organised prostate cancer screening programs in Switzerland. The following article will summarise the events and scientific advances in the last decade during which evidence and promising additional modalities to complement PSA-based prostate cancer screening have emerged. It also aims to provide an overview of contemporary strategies and their potential harms and benefits.

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

BACKGROUND AND OBJECTIVE

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

METHODS

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

KEY FINDINGS AND LIMITATIONS

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

CONCLUSIONS AND CLINICAL IMPLICATIONS

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

PATIENT SUMMARY

In this study, 4Kscore, a blood-based biomarker, as a reflex test for men with elevated prostate-specific antigen (PSA), reduces the need for magnetic resonance imaging and biopsy. These results support the inclusion of new blood-based biomarkers in addition to PSA.

Assessing the Clinical Utility of Published Prostate Cancer Polygenic Risk Scores in a Large Biobank Data Set

BACKGROUND AND OBJECTIVE

Polygenic risk scores (PRSs) have been developed to identify men with the highest risk of prostate cancer. Our aim was to compare the performance of 16 PRSs in identifying men at risk of developing prostate cancer and then to evaluate the performance of the top-performing PRSs in differentiating individuals at risk of aggressive prostate cancer.

METHODS

For this case-control study we downloaded 16 published PRSs from the Polygenic Score Catalog on May 28, 2021 and applied them to Michigan Genomics Initiative (MGI) patients. Cases were matched to the Michigan Urological Surgery Improvement Collaborative (MUSIC) registry to obtain granular clinical and pathological data. MGI prospectively enrolls patients undergoing surgery at the University of Michigan, and MUSIC is a multi-institutional registry that prospectively tracks demographic, treatment, and clinical variables. The predictive performance of each PRS was evaluated using the area under the covariate-adjusted receiver operating characteristic curve (aAUC), and the association between PRS and disease aggressiveness according to prostate biopsy data was measured using logistic regression.

KEY FINDINGS AND LIMITATIONS

We included 18 050 patients in the analysis, of whom 15 310 were control subjects and 2740 were prostate cancer cases. The median age was 66.1 yr (interquartile range 59.9-71.6) for cases and 56.6 yr (interquartile range 42.6-66.7) for control subjects. The PRS performance in predicting the risk of developing prostate cancer according to aAUC ranged from 0.51 (95% confidence interval 0.51-0.53) to 0.67 (95% confidence interval 0.66-0.68). By contrast, there was no association between PRS and disease aggressiveness.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Prostate cancer PRSs have modest real-world performance in identifying patients at higher risk of developing prostate cancer; however, they are limited in distinguishing patients with indolent versus aggressive disease.

PATIENT SUMMARY

Risk scores using data for multiple genes (called polygenic risk scores) can identify men at higher risk of developing prostate cancer. However, these scores need to be refined to be able to identify men with the highest risk for clinically significant prostate cancer.

Phage Biosensor for the Classification of Metastatic Urological Cancers from Urine

Most of the annual 10 million cancer-related deaths are caused by metastatic disease. Survival rates for cancer are strongly dependent on the type of cancer and its stage at detection. Early detection remains a challenge due to the lack of reliable biomarkers and cost-efficient screening methods. Phage biosensors can offer a solution for early detection using non-invasive liquid biopsies. Here, we report the first results of the bifunctional phage biosensor to detect metastatic urological cancers from urine. A dye-sensitized phage library was used to select metastasis-related phage binders. After selection rounds, the most promising phage candidate was used to classify metastatic cancer from controls. Additionally, we applied one chemical sensor (phenoxazine non-fluorescent dye) to classify cancer from urine. A statistical significance (p = 0.0002) was observed between metastatic and non-metastatic cancer, with sensitivity of 70% and specificity of 79%. Furthermore, the chemical sensor demonstrated significance in detecting cancer (p < 0.0001) with a sensitivity of 71% and a specificity of 75%. Our data suggest a new promising field for urine biomarker research, and further evaluation with prospectively collected samples is ongoing. In conclusion, we report, for the first time, the potential of a chemical- and phage-based biosensor method to detect metastatic cancer using urine.

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 value of a three-microRNA panel in serum for prostate cancer screening

BACKGROUND

Globally, prostate cancer is the second most common malignancy in males. Serum microRNAs (miRNAs) may function as non-invasive and innovative biomarkers for various cancers. Our study aimed to determine potential miRNAs for prostate cancer screening.

METHODS

A three-stage study was accomplished to ascertain crucial miRNAs as markers. In the screening stage, we searched PubMed for aberrantly expressed miRNAs relevant to prostate cancer and selected them as candidate miRNAs. In training and validation stages, with serum specimens from 112 prostate cancer patients and 112 healthy controls, expressions of candidate miRNAs were identified through quantitative reverse transcription-polymerase chain reaction. The diagnostic capabilities of miRNAs were determined by receiver operating characteristic curves. Bioinformatic analysis was utilized to explore the function of the critical miRNAs.

RESULTS

Expression of six serum miRNAs (miR-34b-3p, miR-556-5p, miR-200c-3p, miR-361-5p, miR-369-3p, miR-485-3p) were significantly altered in prostate cancer patients contrasted with healthy controls. The optimal combination of critical miRNAs is a three-miRNA panel (miR-34b-3p, miR-200c-3p, and miR-361-5p) with good diagnostic capability. FLRT2, KIAA1755, LDB3, and NTRK3 were identified as the potential genes targeted by the three-miRNA panel.

CONCLUSIONS

The three-miRNA panel may perform as an innovative and promising serum marker for prostate cancer screening.

Prostate tumor markers: diagnosis, prognosis and management

Prostate cancer (PCA) is the second most common type of cancer in the world. Nevertheless, diagnosis is still based on nonspecific methods, or invasive methods which makes clinical decision and diagnosis difficult, generating risk of both underdiagnosis and overdiagnosis. Given the high prevalence, morbidity and mortality of PCA, new strategies are needed for its diagnosis. A review of the literature on available biomarkers for PCA was performed, using the following terms: prostate cancer AND marker OR biomarker. The search was carried out in Pubmed, Science Direct, Web of Science and Clinical Trial. A total of 35 articles were used, and PHI (Prostate Health Index) and the 4Kscore tests were identified as the best well-established serum markers. These tests are based on the evaluation of expression levels of several molecules. For analysis of urine samples, Progensa, ExoDXProstate, and Mi Prostate Score Urine Test are available. All these tests have the potential to help diagnosis, avoiding unnecessary biopsies, but they are used only in association with digital rectal examination and PSA level data. The search for biomarkers that can help in the diagnosis and therapeutic management of PCA is still in its initial phase, requiring more efforts for an effective clinical application.

A meta-analysis for the diagnostic accuracy of SelectMDx in prostate cancer

To overview the diagnostic accuracy of SelectMDx for the detection of clinically significant prostate cancer and to review sources of methodologic variability. Four electronic databases, including PubMed, Embase, Web of Science, and Cochrane Library were searched for eligible studies investigating the diagnostic value of SelectMDx compared with the gold standard. The pooled sensitivity, specificity, and positive and negative predictive values were calculated. Included studies were assessed according to the Standards for Quality Assessment of Diagnostic Accuracy Studies 2 tool. The review identified 14 relevant publications with 2579 patients. All reports constituted phase 1 biomarker studies. Pooled analysis of findings found an area under the receiver operating characteristic analysis curve of 70% [95% CI, 66%-74%], a sensitivity of 81% [95% CI, 69%-89%], and a specificity of 52% [95% CI, 41%-63%]. The positive likelihood ratio was 1.68, and the negative predictive value is 0.37. Factors that may influence variability in test results included the breath collection method, the patient's physiologic condition, the test environment, and the method of analysis. Considerable heterogeneity was observed among the studies owing to the difference in the sample size. SelectMDx appears to have moderate to good diagnostic accuracy in differentiating patients with clinically significant prostate cancer from people at high risk of developing prostate cancer. Higher-quality clinical studies assessing the diagnostic accuracy of SelectMDx for clinically significant cancer are still needed.

Utility of noninvasive biomarker testing and MRI to predict a prostate cancer diagnosis

PURPOSE

To assess the diagnostic performance and utility of the ExoDx IntelliScore and an OPKO4K score to predict prostate cancer in men presenting with elevated PSA-both as independent predictors and in combination with clinical/MRI characteristics.

METHODS

Patients with elevated PSA were retrospectively reviewed. Abnormal tests were defined as an OPKO4K score ≥ 7.5% and an ExoDx IntelliScore ≥ 15.6. Four regression models and ROC curves were generated based on: (1) age, PSA, and DRE, (2) model 1 + OPKO4K 4Kscore ≥ 7.5%, (3) model 2 + ExoDx IntelliScore ≥ 15.6, and (4) model 3 + MRI PIRADS 4-5.

RESULTS

359 men received an OPKO4K test, 307 had MRI and 113 had ExoDx tests. 163 men proceeded to prostate biopsy and 196 (55%) were saved from biopsy. Mean age was 65.0 ± 8.7 years and mean PSA was 7.1 ± 6.1 ng/mL. Positive biopsies were found in 84 (51.5%) men. The sensitivity and negative predictive value of an OPKO4K score were 86.7% and 72.3%; values for an ExoDx test were 76.5% and 77.1%, respectively. On regression analysis, clinical markers (Age, PSA, DRE) generated an AUC of 0.559. The addition of an OPKO4K score raised the AUC to 0.653. The stepwise addition of an ExoDx score raised the AUC to 0.766. The combined use of both biomarkers, patient characteristics, and MRI yielded an AUC of 0.825.

CONCLUSION

This analysis demonstrates the high negative predictive value of both the OPKO4K score and ExoDX IntelliScore independently while demonstrating that the combination of an OPKO4K score, an ExoDX IntelliScore, and MRI increases predictive capability for biopsy confirmed prostate cancer.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

Clinical Biofluid Assays for Prostate Cancer

This mini review summarizes the currently available clinical biofluid assays for PCa. The second most prevalent cancer worldwide is PCa. PCa is a heterogeneous disease, with a large percentage of prostate tumors being indolent, and with a relatively slow metastatic potential. However, due to the high case numbers, the absolute number of PCa-related deaths is still high. In fact, it causes the second highest number of cancer deaths in American men. As a first step for the diagnosis of PCa, the PSA test has been widely used. However, it has low specificity, which results in a high number of false positives leading to overdiagnosis and overtreatment. Newer derivatives of the original PSA test, including the Food and Drug Administration (FDA)-approved 4K (four kallikreins) and the PHI (Prostate Health Index) blood tests, have higher specificities. Tissue-based PCa tests are problematic as biopsies are invasive and have limited accuracy due to prostate tumor heterogeneity. Liquid biopsies offer a minimally or non-invasive choice for the patients, while providing a more representative reflection of the spatial heterogeneity in the prostate. In addition to the abovementioned blood-based tests, urine is a promising source of PCa biomarkers, offering a supplementary avenue for early detection and improved tumor classification. Four urine-based PCa tests are either FDA- or CLIA-approved: PCA3 (PROGENSA), ExoDX Prostate Intelliscore, MiPS, and SelectMDx. We will discuss these urine-based, as well as the blood-based, clinical PCa tests in more detail. We also briefly discuss a few promising biofluid marker candidates (DNA methylation, micro-RNAs) which are not in clinical application. As no single assay is perfect, we envision that a combination of biomarkers, together with imaging, will become the preferred practice.

Artificial intelligence-aided detection for prostate cancer with multimodal routine health check-up data: an Asian multi-center study

BACKGROUND

The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, the authors aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa.

PATIENTS AND METHODS

A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses.

RESULTS

Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74-0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13-0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively.

CONCLUSIONS

The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.

Therapeutic, diagnostic and prognostic values of TRIM proteins in prostate cancer

Prostate cancer is the second most prevalent cancer in men worldwide. The TRIM (tripartite motif) family of proteins is involved in the regulation of various cellular processes, including antiviral immunity, apoptosis, and cancer progression. In recent years, several TRIM proteins have been found to play important roles in prostate cancer initiation and progression. TRIM proteins have indicated oncogenic activity in prostate cancer by enhancing androgen or estrogen receptor signaling and promoting cancer cell growth. Inhibition of TRIM proteins has been raised as a potential therapeutic strategy for the treatment of prostate cancer. Overall, these studies suggest that TRIM family proteins exert tumor-promoting effects in prostate cancer, and targeting these proteins can provide a promising therapeutic strategy for prostate cancer treatment. On the other hand, some TRIM proteins can be differentially expressed in prostate cancer cells compared to normal cells, thus providing novel diagnostic/prognostic biomarkers for 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.

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

BACKGROUND

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

OBJECTIVES

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

DESIGN, SETTINGS, AND PARTICIPANTS

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

METHODS

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

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

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

RESULTS

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

CONCLUSIONS

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

Prediction of clinically significant prostate cancer through urine metabolomic signatures: A large-scale validated study

PURPOSE

Currently, there are no accurate markers for predicting potentially lethal prostate cancer (PC) before biopsy. This study aimed to develop urine tests to predict clinically significant PC (sPC) in men at risk.

METHODS

Urine samples from 928 men, namely, 660 PC patients and 268 benign subjects, were analyzed by gas chromatography/quadrupole time-of-flight mass spectrophotometry (GC/Q-TOF MS) metabolomic profiling to construct four predictive models. Model I discriminated between PC and benign cases. Models II, III, and GS, respectively, predicted sPC in those classified as having favorable intermediate risk or higher, unfavorable intermediate risk or higher (according to the National Comprehensive Cancer Network risk groupings), and a Gleason sum (GS) of ≥ 7. Multivariable logistic regression was used to evaluate the area under the receiver operating characteristic curves (AUC).

RESULTS

In Models I, II, III, and GS, the best AUCs (0.94, 0.85, 0.82, and 0.80, respectively; training cohort, N = 603) involved 26, 24, 26, and 22 metabolites, respectively. The addition of five clinical risk factors (serum prostate-specific antigen, patient age, previous negative biopsy, digital rectal examination, and family history) significantly improved the AUCs of the models (0.95, 0.92, 0.92, and 0.87, respectively). At 90% sensitivity, 48%, 47%, 50%, and 36% of unnecessary biopsies could be avoided. These models were successfully validated against an independent validation cohort (N = 325). Decision curve analysis showed a significant clinical net benefit with each combined model at low threshold probabilities. Models II and III were more robust and clinically relevant than Model GS.

CONCLUSION

This urine test, which combines urine metabolic markers and clinical factors, may be used to predict sPC and thereby inform the necessity of biopsy in men with an elevated PC risk.

A multi-institutional study of 1,111 men with 4K score, multiparametric magnetic resonance imaging, and prostate biopsy

OBJECTIVE

Prostate magnetic resonance imaging (MRI) and biomarkers are often used in conjunction to enhance the selection process for prostate biopsy. However, the optimal sequence of ordering these tests has not been established. A comprehensive evaluation was conducted on a large multi-institutional cohort of patients who underwent MRI, 4K score, and biopsy of the prostate to examine the impact of utilizing both tests vs. either test alone and to determine if the order in which these tests are administered affects the ability to detect clinically significant prostate cancer (csCaP).

METHODS AND MATERIALS

We evaluated men from 8 different institutions who were referred for prostate cancer evaluation and underwent MRI, 4K score test, and prostate biopsy. The primary outcome was the presence of csCaP, defined as grade group 2 or higher cancer on a biopsy of the prostate. We used logistic regression, calibration plots, and decision curve analysis to evaluate using a 4K score or MRI alone vs. both tests together for detecting csCaP. In addition, we evaluated several strategies using one or both tests for selecting men for biopsy and compared them based on the proportion of biopsies avoided and the csCaP's missed.

RESULTS

Among the 1,111 men who formed the final cohort, 553 (49.8%) had prostate cancer, and 353 (31.8%) had csCaP. We found that using MRI and 4K score together had better discrimination, calibration, and a higher clinical utility on decision curve analysis compared to using either test individually. Using both tests together resulted in fewer biopsies avoided and missed cancers compared to using either test alone. Strategies that sequence MRI and 4K score tests resulted in the largest biopsy reduction, with no appreciable difference between starting with an MRI vs. a biomarker.

CONCLUSIONS

We found that using both an MRI and 4K score together was superior to using either test alone but found no appreciable difference between starting with an MRI vs. starting with a 4K score. Prospective studies are needed to identify the best strategy to sequence MRI and biomarkers in the evaluation of csCaP.

Biosensors for prostate cancer detection

Prostate cancer (PC) is one of the most common tumors and a leading cause of mortality among men, resulting in ~375 000 deaths annually worldwide. Various analytical methods have been designed for quantitative and rapid detection of PC biomarkers. Electrochemical (EC), optical, and magnetic biosensors have been developed to detect tumor biomarkers in clinical and point-of-care (POC) settings. Although POC biosensors have shown potential for detection of PC biomarkers, some limitations, such as the sample preparation, should be considered. To tackle such shortcomings, new technologies have been utilized for development of more practical biosensors. Here, biosensing platforms for the detection of PC biomarkers such as immunosensors, aptasensors, genosensors, paper-based devices, microfluidic systems, and multiplex high-throughput platforms, are discussed.

Is Active Surveillance Too Active?

PURPOSE OF REVIEW

Many prostate cancer active surveillance protocols mandate serial monitoring at defined intervals, including but certainly not limited to serum PSA (often every 6 months), clinic visits, prostate multiparametric MRI, and repeat prostate biopsies. The purpose of this article is to evaluate whether current protocols result in excessive testing of patients on active surveillance.

RECENT FINDINGS

Multiple studies have been published in the past several years evaluating the utility of multiparametric MRI, serum biomarkers, and serial prostate biopsy for men on active surveillance. While MRI and serum biomarkers have promise with risk stratification, no studies have demonstrated that periodic prostate biopsy can be safely omitted in active surveillance. Active surveillance for prostate cancer is too active for some men with seemingly low-risk cancer. The use of multiple prostate MRIs or additional biomarkers do not always add to the prediction of higher-grade disease on surveillance biopsy.

Recent advances and future perspectives in the therapeutics of prostate cancer

Prostate cancer (PC) is one of the most common cancers in males and the fifth leading reason of death. Age, ethnicity, family history, and genetic defects are major factors that determine the aggressiveness and lethality of PC. The African population is at the highest risk of developing high-grade PC. It can be challenging to distinguish between low-risk and high-risk patients due to the slow progression of PC. Prostate-specific antigen (PSA) is a revolutionary discovery for the identification of PC. However, it has led to an increase in over diagnosis and over treatment of PC in the past few decades. Even if modifications are made to the standard PSA testing, the specificity has not been found to be significant. Our understanding of PC genetics and proteomics has improved due to advances in different fields. New serum, urine, and tissue biomarkers, such as PC antigen 3 (PCA3), have led to various new diagnostic tests, such as the prostate health index, 4K score, and PCA3. These tests significantly reduce the number of unnecessary and repeat biopsies performed. Chemotherapy, radiotherapy, and prostatectomy are standard treatment options. However, newer novel hormone therapy drugs with a better response have been identified. Androgen deprivation and hormonal therapy are evolving as new and better options for managing hormone-sensitive and castration-resistant PC. This review aimed to highlight and discuss epidemiology, various risk factors, and developments in PC diagnosis and treatment regimens.

Optimum threshold of the 4Kscore for biopsy in men with negative or indeterminate multiparametric magnetic resonance imaging

Objective

The study aims to identify the optimal 4Kscore thresholds to determine the need for a prostate biopsy when multiparametric magnetic resonance imaging (MRI) (mpMRI) is negative or indeterminate.

Materials and methods

We analysed retrospective data from men in eight different institutions who underwent an mpMRI, 4Kscore and prostate biopsy for evaluation of prostate cancer. We selected men with a negative (PIRADS ≤2) or indeterminate (PIRADS 3) mpMRI. 4Kscore values were categorized into ranges of 1-7, 8-19, 20-32 and greater than 32. We evaluated the proportion of men with grade group 2 or higher (GG2+) cancer in groups defined by PIRADS and 4Kscore. We also evaluated the number of biopsies avoided and GG2+ cancer missed in each group reported depend on 4Kscore cutoff points.

Results

Among 1111 men who had an mpMRI, 4Kscore and biopsy, 625 of them had PIRADS ≤3 on mpMRI: 374 negative (PIRADS ≤2) and 251 indeterminate (PIRADS 3). In men with a negative mpMRI, we found a 4Kscore cut-point of 33 resulted in an increased risk of GG2+ cancer on biopsy. In patients with an equivocal lesion on mpMRI, men with a 4Kscore cutoff ≥8 had a greater risk of GG2+ cancer on biopsy. Decision curve analysis supported the proposed cut-points in each mpMRI group.

Conclusions

In men with negative and indeterminate mpMRI, we found the best 4Kscore threshold to determine the need for biopsy to be 33 and 8 respectively. Future prospective studies in independent populations are needed to confirm these findings.

Development and validation of a nomogram based on biparametric MRI PI-RADS v2.1 and clinical parameters to avoid unnecessary prostate biopsies

BACKGROUND

Biparametric MRI (bpMRI) is a faster, contrast-free, and less expensive MRI protocol that facilitates the detection of prostate cancer. The aim of this study is to determine whether a biparametric MRI PI-RADS v2.1 score-based model could reduce unnecessary biopsies in patients with suspected prostate cancer (PCa).

METHODS

The patients who underwent MRI-guided biopsies and systematic biopsies between January 2020 and January 2022 were retrospectively analyzed. The development cohort used to derive the prediction model consisted of 275 patients. Two validation cohorts included 201 patients and 181 patients from 2 independent institutions. Predictive models based on the bpMRI PI-RADS v2.1 score (bpMRI score) and clinical parameters were used to detect clinically significant prostate cancer (csPCa) and compared by analyzing the area under the curve (AUC) and decision curves. Spearman correlation analysis was utilized to determine the relationship between International Society of Urological Pathology (ISUP) grade and clinical parameters/bpMRI score.

RESULTS

Logistic regression models were constructed using data from the development cohort to generate nomograms. By applying the models to the all cohorts, the AUC for csPCa was significantly higher for the bpMRI PI-RADS v2.1 score-based model than for the clinical model in both cohorts (p < 0.001). Considering the test trade-offs, urologists would agree to perform 10 fewer bpMRIs to avoid one unnecessary biopsy, with a risk threshold of 10-20% in practice. Correlation analysis showed a strong correlation between the bpMRI score and ISUP grade.

CONCLUSION

A predictive model based on the bpMRI score and clinical parameters significantly improved csPCa risk stratification, and the bpMRI score can be used to determine the aggressiveness of PCa prior to biopsy.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Risk-stratified multi-round PSA screening for prostate cancer integrating the screening reference level and subgroup-specific progression indicators

BACKGROUND

Although prostate-specific antigen (PSA) is widely used in prostate cancer (PCa) screening, nearly half of PCa cases are missed and less than one-third of cases are non-lethal. Adopting diagnostic criteria in population-based screening and ignoring PSA progression are presumed leading causes.

METHODS

A total of 31,942 participants with multi-round PSA tests from the PLCO trial were included. Time-dependent receiver-operating-characteristic curves and area under curves (tdAUCs) were performed to determine the screening reference level and the optimal subgroup-specific progression indicator. Effects of risk-stratified multi-round PSA screening were evaluated with multivariable Cox regression and measured with hazard ratio [HR (95%CIs)].

RESULTS

After a median follow-up of 11.6 years, a total of 3484 PCa cases and 216 PCa deaths were documented. The tdAUC of 10-year incidence PCa with PSA was 0.816, and the cut-off value was 1.61 ng/ml. Compared to subgroup with stable negative PSA in both first-round (FR) and last-round (LR) tests [FR(-)/LR(-)], HRs (95%CI) of PCa incidence were 1.66 (1.20-2.29), 8.29 (7.25-9.48), and 14.52 (12.95-16.28) for subgroups with loss of positive PSA[FR(+)/LR(-)], gain of positive PSA[FR(-)/LR(+)], and stable positive PSA[FR(+)/LR(+)]; while HRs(95%CI) of PCa mortality were 1.47 (0.52-4.15), 5.71 (3.68-8.86), and 5.01 (3.41-7.37). After excluding regressive PSA [(namely FR(+)/LR(-)], absolute velocity was the shared optimal progression indicator for subgroups with FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), with tdAUCs of 0.665, 0.681 and 0.741, and cut-off values of 0.07, 0.21, and 0.33 ng/ml/year. After reclassifying participants into groups with positive and negative progression based on subgroup-specific progression indicators, incidence HR (95%CI) were 2.41 (1.87-3.10), 2.91 (2.43-3.48), and 3.16 (2.88-3.46) for positive progression compared to negative progression within subgroups of FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), while mortality HR (95%CI) were 2.22 (0.91-5.38), 2.37 (1.28-4.38), and 2.98 (1.94-4.59). To improve screening performances by excluding regressive PSA and low-risk positive progression in FR(-)/LR(-), optimized screening strategy not only significantly reduce 32.4% of missed PCa (54.0% [1881/3484] vs. 21.6% [754/3484], P < 0.001), but also detected additional 8.0% of high-grade PCa (Gleason score 7-10: 36.0% [665/1849] vs. 28.0% [206/736], P < 0.001) than traditional screening strategy.

CONCLUSIONS

Risk-stratified multi-round PSA screening strategy integrating the screening reference level and the optimal subgroup-specific progression indicator of PSA could be recommended as a fundamental strategy to reduce missed diagnosis and improve the detection of high-grade PCa cases.

Outcomes of Grade Group 2 and 3 Prostate Cancer on Initial Versus Confirmatory Biopsy: Implications for Active Surveillance

BACKGROUND

Active surveillance (AS) is recommended as the preferred treatment for men with low-risk disease. In order to optimize risk stratification and exclude undiagnosed higher-grade disease, most AS protocols recommend a confirmatory biopsy.

OBJECTIVE

We aimed to compare outcomes among men with grade group (GG) 2/3 prostate cancer on initial biopsy with those among men whose disease was initially GG1 but was upgraded to GG2/3 on confirmatory biopsy.

DESIGN, SETTING, AND PARTICIPANTS

We reviewed patients undergoing radical prostatectomy (RP) in two cohorts: "immediate RP group," with GG2/3 cancer on diagnostic biopsy, and "AS group," with GG1 cancer on initial biopsy that was upgraded to GG2/3 on confirmatory biopsy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Probabilities of biochemical recurrence (BCR) and salvage therapy were determined using multivariable Cox regression models with risk adjustment. Risks of adverse pathology at RP were also compared using logistic regression.

RESULTS AND LIMITATIONS

The immediate RP group comprised 4009 patients and the AS group comprised 321 patients. The AS group had lower adjusted rates of adverse pathology (27% vs 35%, p = 0.003). BCR rates were lower in the AS group, although this did not reach conventional significance (hazard ratio [HR] 0.73, 95% confidence interval [CI] 0.50-1.06, p = 0.10) compared with the immediate RP group. Risk-adjusted 1- and 5-yr BCR rates were 4.6% (95% CI 3.0-6.5%) and 10.4% (95% CI 6.9-14%), respectively, for the AS group compared with 6.3% (95% CI 5.6-7.0%) and 20% (95% CI 19-22%), respectively, in the immediate RP group. A nonsignificant association was observed for salvage treatment-free survival favoring the AS group (HR 0.67, 95% CI 0.42, 1.06, p = 0.087).

CONCLUSIONS

We found that men with GG1 cancer who were upgraded on confirmatory biopsy tend to have less aggressive disease than men with the same grade found at initial biopsy. These results must be confirmed in larger series before recommendations can be made regarding a more conservative approach in men with upgraded pathology on surveillance biopsy.

PATIENT SUMMARY

We studied men with low-risk prostate cancer who were initially eligible for active surveillance but presented with more aggressive cancer on confirmatory biopsy. We found that outcomes for these men were better than the outcomes for those diagnosed initially with more serious cancer.

Relationship between Proclarix and the Aggressiveness of Prostate Cancer

INTRODUCTION

Proclarix is a CE-marked test that provides the risk of clinically significant prostate cancer (csPCa), ranging from 0% to 100%, based on the serum measurement of Thrombospondin-1, cathepsin D, prostate-specific antigen (PSA), and percentage of free PSA in addition to age. We hypothesize that Proclarix could be correlated with PCa aggressiveness. We analyzed the association of this new biomarker with four surrogates of aggressiveness: grade group (GG) in the biopsy, clinical stage, risk of biochemical recurrence after primary treatment of localized PCa, and pathology in the surgical specimen.

MATERIAL AND METHODS

This is a retrospective study from 606 men with suspicion of PCa [PSA of ≥ 3.0 ng/mL and/or abnormal digital rectal examination (DRE)], in whom Proclarix was assessed (0-100%). The GG was defined by the International Society of Urological Pathology categories. The TNM was used for clinical staging (cT based on DRE, whereas cN and cM were established with computed tomography and 99-technetium bone scintigraphy). The risk of biochemical recurrence of localized PCa after primary treatment was defined by combining PSA, GG, and cT. Finally, an unfavorable pathology in a surgical specimen was defined as GG > 2 or pT ≥ 3.

RESULTS

The median age of the cohort was 67 years old, with a median PSA of 7 ng/mL and a rate of abnormal DRE of 23.3%. CsPCa was detected in 254 men (41.9%), with a median Proclarix of 60.1% compared with 37.3% obtained in patients with insignificant PCa and 20.7% in men without PCa. Among patients with GG > 3, Proclarix was significantly higher (58.2%) than in those with GG of 3 or lower (33.1%, p < 0.001). Men with localized tumors exhibited a Proclarix median of 37.3% compared with those with advanced disease (60.1%, p < 0.001). Proclarix levels among 197 patients with low and intermediate risk of biochemical recurrence were 24.9% and 35.0%, respectively, significantly lower compared with patients with high-risk disease (58.7%, p < 0.001). Unfavorable pathology was observed in 35 patients out of the 79 who underwent radical prostatectomy, with a Proclarix median of 35.7% compared with 23.7% obtained in patients with favorable pathology (p = 0.013). Proclarix and magnetic resonance imaging were independent predictors of the four surrogates of aggressiveness analyzed.

CONCLUSION

There is a correlation between Proclarix and the aggressiveness of PCa.

Implementation of 4Kscore as a Secondary Test Before Prostate Biopsy: Impact on US Population Trends for Prostate Cancer

Prostate cancer screening using prostate-specific antigen (PSA) reduces prostate cancer mortality at the cost of unnecessary prostate biopsy, overdiagnosis, and overtreatment. Several secondary tests have been developed to restrict biopsy to men at the greatest risk of high-grade disease. 4Kscore is a widely used secondary test that has been shown to reduce biopsy rates by approximately two-thirds in routine clinical practice. We estimated how 4Kscore implementation has affected cancer trends in the US population. We combined data from the US validation study of 4Kscore with data from the diagnostic test impact study, using a basis of 70 000 on-label 4Kscore tests performed annually. We estimate that each year, 4Kscore leads to 45 200 fewer biopsies and 9400 fewer overdiagnoses of low-grade cancer, at the cost of delayed diagnosis of high-grade prostate cancer for 3450 patients, of whom two-thirds have International Society of Urological Pathology grade group 2 disease. These findings need to be taken into consideration when studying epidemiologic trends in prostate cancer. They also suggest that high levels of overdiagnosis and overtreatment are not inevitable characteristics of PSA screening, but can be mitigated by additional tests.

Patient summary

We estimate that use of a test called 4Kscore to predict the probability that a patient has high-grade prostate cancer has significantly reduced the number of unnecessary biopsies and overdiagnosis of low-grade cancer in the USA. These decisions may result in delayed diagnosis of high-grade cancer in some patients. 4Kscore is a useful additional test in the management of prostate cancer.

Urinary exosomal prostate-specific antigen is a noninvasive biomarker to detect prostate cancer: Not only old wine in new bottles

The study aimed at evaluating the performance of urinary exosomal prostate-specific antigen (UE-PSA) to predict the results of initial prostate biopsies and discriminate clinically significant prostate cancer (Gleason score ≥ 7, csPCa) from nonsignificant PCa (Gleason score < 7, nsPCa) plus benign patients. Two hundred seventy-two consecutive participants were admitted who underwent a prostate biopsy. The UE-PSA expression was detected by enzyme-linked immunosorbent assay (ELISA). The predictive power and clinical value of UE-PSA was assessed by receiver operating characteristic (ROC), decision curve analysis (DCA) and waterfall plots. UE-PSA was upregulated in PCa compared to benign patients (P < .001) and csPCa compared to nsPCa plus benign patients (P < .001). UE-PSA achieved an AUC of 0.953 (0.905-0.989) in distinguishing PCa from benign patients and an AUC of 0.879 (0.808-0.941) in predicting csPCa from nsPCa plus benign patients. These results were validated in an additional multicenter cohort. In addition, DCA showed that UE-PSA achieved the highest net benefit at almost any threshold probability compared to tPSA and %fPSA. As the waterfall plot showed, the UE-PSA assay could avoid 57.6% (155 cases) and 34.6% (93 cases) unnecessary biopsies while only missing 2.6% (7 cases) and 1.5% (4 cases) of the cases of csPCa at the cutoff value of 90% and 95% sensitivity, respectively. We validated that UE-PSA presented great diagnostic power and clinical utility to diagnose PCa and csPCa. UE-PSA could be a promising noninvasive biomarker to improve PCa detection.

Accurate prostate cancer detection based on enrichment and characterization of prostate cancer specific circulating tumor cells

BACKGROUND

The low specificity of serum PSA resulting in the inability to effectively differentiate prostate cancer from benign prostate conditions is a persistent clinical challenge. The low sensitivity of serum PSA results in false negatives and can miss high-grade prostate cancers. We describe a non-invasive test for detection of prostate cancer based on functional enrichment of prostate adenocarcinoma associated circulating tumor cells (PrAD-CTCs) from blood samples followed by their identification by immunostaining for pan-cytokeratins (PanCK), prostate specific membrane antigen (PSMA), alpha methyl-acyl coenzyme-A racemase (AMACR), epithelial cell adhesion molecule (EpCAM), and common leucocyte antigen (CD45).

METHODS

Analytical validation studies were performed to establish the performance characteristics of the test using VCaP prostate cancer cells spiked into healthy donor blood (HDB). The clinical performance characteristics of the test were evaluated in a case-control study with 160 known prostate cancer cases and 800 healthy males, followed by a prospective clinical study of 210 suspected cases of prostate cancer.

RESULTS

Analytical validation established analyte stability as well as acceptable performance characteristics. The test showed 100% specificity and 100% sensitivity to differentiate prostate cancer cases from healthy individuals in the case control study and 91.2% sensitivity and 100% specificity to differentiate prostate cancers from benign prostate conditions in the prospective clinical study.

CONCLUSIONS

The test accurately detects PrAD-CTCs with high sensitivity and specificity irrespective of stage, serum PSA or Gleason score, which translates into low risks of false negatives or overdiagnosis. The high accuracy of the test could offer advantages over PSA based prostate cancer detection.

Artificial Intelligence Applications in Clinical Chemistry

Artificial intelligence (AI) applications are an area of active investigation in clinical chemistry. Numerous publications have demonstrated the promise of AI across all phases of testing including preanalytic, analytic, and postanalytic phases; this includes novel methods for detecting common specimen collection errors, predicting laboratory results and diagnoses, and enhancing autoverification workflows. Although AI applications pose several ethical and operational challenges, these technologies are expected to transform the practice of the clinical chemistry laboratory in the near future.

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.

Long noncoding RNA as a potential diagnostic tool for prostate cancer: a systematic review and meta-analysis

PURPOSE

To identify consistently expressed lncRNAs and suitable lncRNAs with high sensitivity and specificity from multiple independent studies as potential biomarkers for PCa diagnostics.

METHODS

We searched multiple electronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, CQVIP, Wanfang, and CBMdisc for studies published up to July 2022. The quality of the included studies was assessed by two independent reviewers based on the QUADAS-2 tool using Review Manager 5.3. A vote-counting method was used based on the ranking of potential molecular biomarkers. The top-ranked lncRNAs were further assessed for diagnostic value using Meta-disc version 1.4 software.

RESULTS

Among the 26 included studies, 2 circulating lncRNAs (PCA3 and MALAT-1) were reported 3 or more times in PCa patients versus non-PCa patients. In further analysis, the areas under the curve of the summary receiver operating characteristic curves for PCA3 and MALAT-1 distinguishing PCa patients were 0.775 and 0.771, respectively.

CONCLUSIONS

Based on the current evidence, PCA3 and MALAT-1 are reliable lncRNAs for the diagnosis of PCa.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

Urinary extracellular vesicles miRNA-A new era of prostate cancer biomarkers

Prostate cancer is the second most common male cancer worldwide showing the highest rates of incidence in Western Europe. Although the measurement of serum prostate-specific antigen levels is the current gold standard in PCa diagnosis, PSA-based screening is not considered a reliable diagnosis and prognosis tool due to its lower sensitivity and poor predictive score which lead to a 22%-43% overdiagnosis, unnecessary biopsies, and over-treatment. These major limitations along with the heterogeneous nature of the disease have made PCa a very unappreciative subject for diagnostics, resulting in poor patient management; thus, it urges to identify and validate new reliable PCa biomarkers that can provide accurate information in regard to disease diagnosis and prognosis. Researchers have explored the analysis of microRNAs (miRNAs), messenger RNAs (mRNAs), small proteins, genomic rearrangements, and gene expression in body fluids and non-solid tissues in search of lesser invasive yet efficient PCa biomarkers. Although the presence of miRNAs in body fluids like blood, urine, and saliva initially sparked great interest among the scientific community; their potential use as liquid biopsy biomarkers in PCa is still at a very nascent stage with respect to other well-established diagnostics and prognosis tools. Up to date, numerous studies have been conducted in search of PCa miRNA-based biomarkers in whole blood or blood serum; however, only a few studies have investigated their presence in urine samples of which less than two tens involve the detection of miRNAs in extracellular vesicles isolated from urine. In addition, there exists some discrepancy around the identification of miRNAs in PCa urine samples due to the diversity of the urine fractions that can be targeted for analysis such as urine circulating cells, cell-free fractions, and exosomes. In this review, we aim to discuss research output from the most recent studies involving the analysis of urinary EVs for the identification of miRNA-based PCa-specific biomarkers.

Ultrasound-based radiomics score for pre-biopsy prediction of prostate cancer to reduce unnecessary biopsies

BACKGROUND

Patients undergoing prostate biopsies (PBs) suffer from low positive rates and potential risk for complications. This study aimed to develop and validate an ultrasound (US)-based radiomics score for pre-biopsy prediction of prostate cancer (PCa) and subsequently reduce unnecessary PBs.

METHODS

Between December 2015 and March 2018, 196 patients undergoing initial transrectal ultrasound (TRUS)-guided PBs were retrospectively enrolled and randomly assigned to the training or validation cohort at a ratio of 7:3. A total of 1044 radiomics features were extracted from grayscale US images of each prostate nodule. After feature selection through the least absolute shrinkage and selection operator (LASSO) regression model, the radiomics score was developed from the training cohort. The prediction nomograms were developed using multivariate logistic regression analysis based on the radiomics score and clinical risk factors. The performance of the nomograms was assessed and compared in terms of discrimination, calibration, and clinical usefulness.

RESULTS

The radiomics score consisted of five selected features. Multivariate logistic regression analysis demonstrated that the radiomics score, age, total prostate-specific antigen (tPSA), and prostate volume were independent factors for prediction of PCa (all p < 0.05). The integrated nomogram incorporating the radiomics score and three clinical risk factors reached an area under the curve (AUC) of 0.835 (95% confidence interval [CI], 0.729-0.941), thereby outperforming the clinical nomogram which based on only clinical factors and yielded an AUC of 0.752 (95% CI, 0.618-0.886) (p = 0.04). Both nomograms showed good calibration. Decision curve analysis indicated that using the integrated nomogram would add more benefit than using the clinical nomogram.

CONCLUSION

The radiomics score was an independent factor for pre-biopsy prediction of PCa. Addition of the radiomics score to the clinical nomogram shows incremental prognostic value and may help clinicians make precise decisions to reduce unnecessary PBs.

A high serum dehydroepiandrosterone concentration is a predictor of candidates for active surveillance in men with serum prostate-specific antigen < 10 ng/mL

Background

There is no consensus on the role of serum dehydroepiandrosterone (DHEA) concentrations in the detection of prostate cancer. This study examined the effectiveness of serum DHEA in predicting candidate patients for active surveillance (AS) prior to prostate biopsy.

Methods

A systematic prostate needle biopsy was performed in 203 men with serum PSA levels of < 10 ng/mL to detect prostate cancer. Serum DHEA concentrations were measured with liquid chromatography-tandem mass spectrometry (LC–MS/MS) just before biopsy. Patient’s age, serum prostate-specific antigen (PSA) levels, prostate volume, and serum DHEA concentrations were compared with pathological findings in multivariate analyses.

Results

The median patient’s age, PSA, serum DHEA concentration and prostate volume were 68 years, 5.5 ng/mL, 1654.7 pg/mL, and 31.2 mL, respectively. In a multivariate analysis, low PSA values, high serum DHEA concentrations, and large prostate volume were significant predictors of the patients with benign prostatic hyperplasia (BPH) or prostate cancer with a Gleason score of ≤ 3 + 4 who are candidate for AS. The DHEA cut-off point for predicting BPH or prostate cancer with a Gleason score of ≤ 3 + 4 was 2188 pg/mL, with a sensitivity, specificity, positive predictive value, and negative predictive value of 33.7%, 96.0%, 98.4%, and 16.9%, respectively.

Conclusion

The study indicated that higher serum DHEA concentrations prior to prostate biopsy might predict the patients with BPH or prostate cancer with a Gleason score ≤ 3 + 4 who are candidate for AS, in men with PSA of < 10 ng/mL.

Predicting Grade group 2 or higher cancer at prostate biopsy by 4Kscore in blood and uCaP microRNA model in urine

Elevated prostate-specific antigen (PSA) levels often lead to unnecessary and possibly harmful transrectal ultrasound guided biopsy, e.g. when the biopsy is negative or contains only low-grade insignificant cancer, unlikely to become symptomatic in the man's normal lifespan. A model based on four-kallikrein markers in blood (commercialized as 4Kscore) predicts risk of Grade group 2 or higher prostate cancer at biopsy, reducing unnecessary biopsies. We assessed whether these results extend to a single institution prostate biopsy cohort of Danish men and are enhanced by three microRNAs from urine (referred to as uCaP). The 4Kscore measured in cryopreserved blood from 234 men referred for 10+ core biopsy to Aarhus University Hospital, 29 with PSA > 25 ng/ml. We explored uCaP in urine from 157 of these men. Combined with age and DRE findings, both 4Kscore and uCaP could accurately predict Grade group 2 or higher prostate cancer (all patients: AUC = 0.802 and 0.797; PSA ≤ 25: AUC = 0.763 and 0.759). There was no additive effect when combining the 4Kscore and uCaP. Limitations include a study cohort with higher risk than commonly reported for biopsy cohorts. Our findings further support the clinical use of the 4Kscore to predict Grade group 2 or higher cancers in men being considered for biopsy.

Volatilomics: An Emerging and Promising Avenue for the Detection of Potential Prostate Cancer Biomarkers

Simple Summary

The lack of highly specific and sensitive biomarkers for the early detection of prostate cancer (PCa) is a major barrier to its management. Volatilomics emerged as a non-invasive, simple, inexpensive, and easy-to-use approach for cancer screening, characterization of disease progression, and follow-up of the treatment’s success. We provide a brief overview of the potential of volatile organic metabolites (VOMs) for the establishment of PCa biomarkers from non-invasive matrices. Endogenous VOMs have been investigated as potential biomarkers since changes in these VOMs can be characteristic of specific disease processes. Recent studies have shown that the conjugation of the prostate-specific antigen (PSA) screening with other methodologies, such as risk calculators, biomarkers, and imaging tests, can attenuate overdiagnosis and under-detection issues. This means that the combination of volatilomics with other methodologies could be extremely valuable for the differentiation of clinical phenotypes in a group of patients, providing more personalized treatments.

Abstract

Despite the spectacular advances in molecular medicine, including genomics, proteomics, transcriptomics, lipidomics, and personalized medicine, supported by the discovery of the human genome, prostate cancer (PCa) remains the most frequent malignant tumor and a leading cause of oncological death in men. New methods for prognostic, diagnostic, and therapy evaluation are mainly based on the combination of imaging techniques with other methodologies, such as gene or protein profiling, aimed at improving PCa management and surveillance. However, the lack of highly specific and sensitive biomarkers for its early detection is a major hurdle to this goal. Apart from classical biomarkers, the study of endogenous volatile organic metabolites (VOMs) biosynthesized by different metabolic pathways and found in several biofluids is emerging as an innovative, efficient, accessible, and non-invasive approach to establish the volatilomic biosignature of PCa patients, unravelling potential biomarkers. This review provides a brief overview of the challenges of PCa screening methods and emergent biomarkers. We also focus on the potential of volatilomics for the establishment of PCa biomarkers from non-invasive matrices.

Urinary MyProstateScore (MPS) to Rule out Clinically-Significant Cancer in Men with Equivocal (PI-RADS 3) Multiparametric MRI: Addressing an Unmet Clinical Need

OBJECTIVE

To evaluate the complementary value of urinary MyProstateScore (MPS) testing and multiparametric MRI (mpMRI) and assess outcomes in patients with equivocal mpMRI.

MATERIALS AND METHODS

Included patients underwent mpMRI followed by urine collection and prostate biopsy at the University of Michigan between 2015 -2019. MPS values were calculated from urine specimens using the validated model based on serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. In the PI-RADS 3 population, the discriminative accuracy of PSA, PSAD, and MPS for GG≥2 cancer was quantified by the AUC curve. Decision curve analysis was used to assess net benefit of MPS relative to PSAD.

RESULTS

There were 540 patients that underwent mpMRI and biopsy with MPS available. The prevalence of GG≥2 cancer was 13% for PI-RADS 3, 56% for PI-RADS 4, and 87% for PI-RADS 5. MPS was significantly higher in men with GG≥2 cancer [median 44.9, IQR (29.4 -57.5)] than those with negative or GG1 biopsy [median 29.2, IQR (14.8 -44.2); P <.001] in the overall population and when stratified by PI-RADS score. In the PI-RADS 3 population (n = 121), the AUC for predicting GG≥2 cancer was 0.55 for PSA, 0.62 for PSAD, and 0.73 for MPS. MPS provided the highest net clinical benefit across all pertinent threshold probabilities.

CONCLUSION

In patients that underwent mpMRI and biopsy, MPS was significantly associated with GG≥2 cancer across all PI-RADS scores. In the PI-RADS 3 population, MPS significantly outperformed PSAD in ruling out GG≥2 cancer. These findings suggest a complementary role of MPS testing in patients that have undergone mpMRI.

Multi-marker risk-based screening for prostate cancer

OBJECTIVE

To determine prostate cancer screening performance using prostate specific antigen (PSA) along with other markers, expressing markers in age-specific multiples of the median (MoM), and age.

METHODS

A prospective nested case-control study used stored serum from 571 men who died of, or with history of, prostate cancer (cases), and 2169 matched controls. Total, free and intact PSA, human kallikrein-related peptidase 2 (hK2), and microseminoprotein were measured and converted into MoM values. Screening marker distribution parameters were estimated in cases and controls. Monte Carlo simulation used these in a risk-based algorithm to estimate screening performance (detection rates [DRs] and false-positive rates [FPRs]).

RESULTS

Almost all (99%) cases occurred aged ≥55. Marker values were similar in cases who did and did not die of prostate cancer. Combining age, total PSA and hK2 MoM values (other markers added little or no discrimination) yielded a 1.2% FPR (95% CI 0.2-4.8%) for a 90% DR (59-98%) in men who died of or with a prostate cancer diagnosis within 5 years of blood collection (risk cut-off 1 in 20), two-thirds less than the 4.5% FPR using total PSA alone measured in ng/ml for the same 90% DR (cut-off 3.1 ng/ml). Screening performance over 10 years yielded a 33% (22-46%) FPR for a 90% DR.

CONCLUSION

Screening performed up to every 5 years from age 55 using the multi-marker risk-based screening algorithm for future prostate cancer achieves a high DR and a much lower FPR than using PSA alone, resulting in reductions in overdiagnosis and overtreatment.

Concordance of MRI-Guided Fusion and Systematic 12-Core Prostate Biopsy for the Detection of Prostate Cancer

Background

MRI-guided fusion biopsy is increasingly utilized over systematic 12-core biopsy for men with MRI-visible prostate lesions.

Patients and Methods

Patients with MRI visible lesions who underwent MRI-guided fusion and systematic 12-core biopsy from 2016-2020 in the Intermountain Healthcare (IHC) system were consecutively analyzed. This was in the setting of a continuous quality assurance initiative among the reading radiologists. Primary outcome was prostate cancer (PCa) detection defined by Gleason grade group (GGG) 1 or higher. Clinically significant cancer (CSC) was defined as GGG 2 or higher. Patients were stratified by biopsy date, 2016-2017 and 2018-2021, and lesions were stratified by PI-RADS v2 category.

Results

A total of 184 patients with 324 MRI-detectable lesions underwent both biopsy modalities in the IHC system from 2016 to 2021. CSC was detected in 23.5% of MRI-guided fusion biopsies. Comparing PI-RAD v2 categories 1-3 to categories 4-5, rate of CSC was 10% and 42% respectively. MRI-guided fusion and systematic 12-core biopsies were concordant for PCa in 77% of men and CSC in 83%. MRI-guided fusion biopsy detected PCa in 26/103 and CSC in 20/131 men in whom systematic 12-core biopsy was negative. Systematic 12-core biopsy detected PCa in 17/94 and CSC in 11/122 men in whom MRI-guided fusion was negative.

Conclusions

Omitting MRI-guided fusion or systematic 12-core biopsy would have resulted in underdiagnosis of CSC in 11% or 6% of patients respectively. Combining biopsies increased detection rate of CSC. This was in the setting of a continuous quality assurance program at a large community-based hospital.

Access and Representation: A Narrative Review of the Disparities in Access to Clinical Trials and Precision Oncology in Black men with Prostate Cancer

OBJECTIVE

To provide commentary on the disparities in access to clinical trials and precision oncology specific to Black men with Prostate Cancer (PCa) in the United States and lend a general framework to aid in closing these gaps.

MATERIALS AND METHODS

The ideas, commentaries and data presented in this narrative review were synthesized by utilizing qualitative and quantitative studies, reviews, and randomized control trials performed between 2010 and 2021. We searched PubMed using the key words "Medicaid", "Medicare", "clinical trials", "African Americans", "Black", "underrepresentation", "access", "Prostate Cancer", "minority recruitment", "racial disparities", "disparity", "genomics", "biomarkers", "diagnostic" "prognostic", "validation", "precision medicine", and "precision oncology" to identify important themes, trends and data described in the current review. Keywords were used alone and combination with both "AND" and "OR" terms.

RESULTS

Black men with prostate cancer (PCa) in the United States have earlier onset of disease, present with more advanced stages, and worse prostate cancer-specific survival than their White counterparts. Potential causative factors vary from disparities in health care access to differences in tumor immunobiology and genomics along with disparate screening rates, management patterns and underrepresentation in clinical and translational research such as clinical trials and precision oncology.

CONCLUSION

To avoid increasing the racial disparity in PCa outcomes for Black men, we must increase inclusion of Black men into precision oncology and clinical trials, using multilevel change. Underrepresentation in clinical and translational research may potentiate poorly validated risk calculators and biomarkers, leading to poor treatment decisions in high-risk populations. Relevant actions include funding to include minority-serving institutions as recruitment sites, and inclusion of evidence based recruitment methods in funded research to increase Black representation in clinical trials and translational research.

Prostate cancer polygenic risk score and prediction of lethal prostate cancer

Polygenic risk scores (PRS) for prostate cancer incidence have been proposed to optimize prostate cancer screening. Prediction of lethal prostate cancer is key to any stratified screening program to avoid excessive overdiagnosis. Herein, PRS for incident prostate cancer was evaluated in two population-based cohorts of unscreened middle-aged men linked to cancer and death registries: the Västerbotten Intervention Project (VIP) and the Malmö Diet and Cancer study (MDC). SNP genotypes were measured by genome-wide SNP genotyping by array followed by imputation or genotyping of selected SNPs using mass spectrometry. The ability of PRS to predict lethal prostate cancer was compared to PSA and a commercialized pre-specified model based on four kallikrein markers. The PRS was associated with incident prostate cancer, replicating previously reported relative risks, and was also associated with prostate cancer death. However, unlike PSA, the PRS did not show stronger association with lethal disease: the hazard ratio for prostate cancer incidence vs. prostate cancer metastasis and death was 1.69 vs. 1.65 in VIP and 1.25 vs. 1.25 in MDC. PSA was a much stronger predictor of prostate cancer metastasis or death with an area-under-the-curve of 0.78 versus 0.63 for the PRS. Importantly, addition of PRS to PSA did not contribute additional risk stratification for lethal prostate cancer. We have shown that a PRS that predicts prostate cancer incidence does not have utility above and beyond that of PSA measured at baseline when applied to the clinically relevant endpoint of prostate cancer death. These findings have implications for public health policies for delivery of prostate cancer screening. Focusing polygenic risk scores on clinically significant endpoints such as prostate cancer metastasis or death would likely improve clinical utility.