The Prostate Health Index: Its Utility in Prostate Cancer Detection

Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients' risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

Novel frontiers in urogenital cancers: from molecular bases to preclinical models to tailor personalized treatments in ovarian and prostate cancer patients

Over the last few decades, the incidence of urogenital cancers has exhibited diverse trends influenced by screening programs and geographical variations. Among women, there has been a consistent or even increased occurrence of endometrial and ovarian cancers; conversely, prostate cancer remains one of the most diagnosed malignancies, with a rise in reported cases, partly due to enhanced and improved screening efforts.Simultaneously, the landscape of cancer therapeutics has undergone a remarkable evolution, encompassing the introduction of targeted therapies and significant advancements in traditional chemotherapy. Modern targeted treatments aim to selectively address the molecular aberrations driving cancer, minimizing adverse effects on normal cells. However, traditional chemotherapy retains its crucial role, offering a broad-spectrum approach that, despite its wider range of side effects, remains indispensable in the treatment of various cancers, often working synergistically with targeted therapies to enhance overall efficacy.For urogenital cancers, especially ovarian and prostate cancers, DNA damage response inhibitors, such as PARP inhibitors, have emerged as promising therapeutic avenues. In BRCA-mutated ovarian cancer, PARP inhibitors like olaparib and niraparib have demonstrated efficacy, leading to their approval for specific indications. Similarly, patients with DNA damage response mutations have shown sensitivity to these agents in prostate cancer, heralding a new frontier in disease management. Furthermore, the progression of ovarian and prostate cancer is intricately linked to hormonal regulation. Ovarian cancer development has also been associated with prolonged exposure to estrogen, while testosterone and its metabolite dihydrotestosterone, can fuel the growth of prostate cancer cells. Thus, understanding the interplay between hormones, DNA damage and repair mechanisms can hold promise for exploring novel targeted therapies for ovarian and prostate tumors.In addition, it is of primary importance the use of preclinical models that mirror as close as possible the biological and genetic features of patients' tumors in order to effectively translate novel therapeutic findings "from the bench to the bedside".In summary, the complex landscape of urogenital cancers underscores the need for innovative approaches. Targeted therapy tailored to DNA repair mechanisms and hormone regulation might offer promising avenues for improving the management and outcomes for patients affected by ovarian and prostate cancers.

Clinical assessment of TGFB1 and HP Relative Gene Expression in the Peripheral Blood of Prostate Cancer Patients

OBJECTIVE

This study aimed to assess the relative gene expression level of transforming growth factor-β1 (TGFB1) and haptoglobin (HP) in the peripheral blood of prostate cancer (PCa) patients and evaluate their diagnostic ability.

METHODS

A total of 125 participants were enrolled in the present study. Among them, 75 PCa patients, 25 benign prostatic hyperplasia (BPH) patients, and 25 healthy volunteers served as the control group. The relative TGFB1 and HP gene expression level was quantified using real-time polymerase chain reaction. Further, free and total PSA levels were determined using electrochemiluminescence assays.

RESULTS

TGFB1 was significantly over-expressed, whereas HP was significantly downregulated in the peripheral blood of PCa patients compared to BPH and control groups (p-value ranges from 0.034 to <0.001). Moreover, the high expression level of TGFB1 was associated with an increased risk of PCa development with OR=1.412 (95%CI: 1.081-1.869, p= 0.012). TGFB1 and HP relative expression levels had lower diagnostic performance to differentiate PCa from normal and BPH individuals compared to PSA, however, the combination of the tested parameters improved the diagnostic efficacy.

CONCLUSIONS

TGFB1 and HP relative expression have moderate diagnostic efficacy in discriminating patients with PCa from BPH and healthy subjects. Furthermore, over-expression of TGFB1 may contribute to the pathogenesis of PCa.

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.

Comparison of Prostate-Specific Antigen and Its Density and Prostate Health Index and Its Density for Detection of Prostate Cancer

As the incidence of prostate cancer (PCa) has increased, screening based on prostate-specific antigen (PSA) has become controversial due to the low specificity of PSA. Therefore, we investigated the diagnostic performance of prostate health index (PHI) density (PHID) for the detection of PCa and clinically significant PCa (csPCa) compared to PSA, PSA density (PSAD), and PHI as a triaging test. We retrospectively reviewed 306 men who underwent prostate biopsy for PSA levels of 2.5 to 10 ng/mL between January 2020 and April 2023. Of all cohorts, 86 (28.1%) and 48 (15.7%) men were diagnosed with PCa and csPCa, respectively. In ROC analysis, the highest AUC was identified for PHID (0.812), followed by PHI (0.791), PSAD (0.650), and PSA (0.571) for PCa. A similar trend was observed for csPCa: PHID (AUC 0.826), PHI (AUC 0.796), PSAD (AUC 0.671), and PSA (0.552). When the biopsy was restricted to men with a PHID ≥ 0.56, 26.5% of unnecessary biopsies could be avoided; however, 9.3% of PCa cases and one csPCa case (2.1%) remained undiagnosed. At approximately 90% sensitivity for csPCa, at the given cut-off values of PHI ≥ 36.4, and PHID ≥ 0.91, 48.7% and 49.3% of unnecessary biopsies could be avoided. In conclusion, PHID had a small advantage over PHI, about 3.6%, for the reduction in unnecessary biopsies for PCa. The PHID and PHI showed almost the same diagnostic performance for csPCa detection. PHID can be used as a triaging test in a clinical setting to pre-select the risk of PCa and csPCa.

Insurer coverage of prostate cancer biomarkers

INTRODUCTION

Several recently-developed prostate cancer (CaP) biomarkers are recommended per national guidelines, yet feasibility of obtaining these tests is unknown. We used a national database to assess insurance coverage of CaP biomarkers.

MATERIALS AND METHODS

Insurance policies regarding 4K Score, ExoDx, My Prostate Score, Prostate Cancer Antigen 3, Prostate Health Index, and SelectMDx as of January 1, 2022 were extracted from the policy reporter database. Coverage was defined as a biomarker being deemed medically necessary, conditionally covered, or covered with prior authorization. Overall rates of biomarker coverage were compared by insurance type and region using Chi-squared test. SelectMDx was not covered by any queried policies and was omitted from analysis.

RESULTS

A total of 186 insurance plans were identified among 131 payers. Of the 186 plans, 109 (59%) covered at least one biomarker, with prior authorization required for 38 (35%) of these plans. Prostate Cancer Antigen 3 and 4K Score had higher rates of coverage compared to ExoDx, Prostate Health Index, and My Prostate Score (52% and 43% vs. 26%, 26%, and 5%, respectively, P < 0.01). Medicare plans had higher rates of coverage compared to non-Medicare plans (80% Medicare vs. 17% commercial, 15% federal employer, and 13% Medicaid, P < 0.01), and nationwide plans had higher coverage rates compared to regional plans (43% nationwide vs. 32% midwest, 27% northeast, 25% south, 24% west, P < 0.01). Covered biomarkers under Medicare plans were less likely to require prior authorization compared to those covered by non-Medicare plans (12% Medicare vs. 63% commercial, 100% federal employer, 70% Medicaid, P < 0.01).

CONCLUSIONS

Coverage of novel CaP biomarkers are relatively robust for Medicare plans but sparse for non-Medicare plans, with the majority of non-Medicare plans requiring prior authorization. Non-Medicare eligible men may face significant barriers to obtaining these tests.

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.

An overview of prostate cancer (PCa) diagnosis: Potential role of miRNAs

Prostate cancer is the second most frequently diagnosed cancer among men worldwide, with the estimated sixth leading cause of cancer death. Despite major advancements in clinical biology and imaging, digital rectal examination (DRE), prostate-specific antigen (PSA), and biopsies indication remain the keystone for screening. Several kits are used to detect genomic changes and non-coding RNAs in the sample. However, its indication remains controversial for screening purposes. There is an urged need for non-invasive biomarkers to implement precision medicine. Recent research shows that miRNAs have an important role in the diagnostic, prognostic, and therapeutic agents as non-invasive biomarkers. Though prostate cancer data remains controversial in other cancer types, such as breast cancer, miR-21 expression is upregulated. Here, we reported a prolonged revision of miRNAs as prostate cancer prognostic, diagnostic, and predictive tools, including data on androgen receptor (AR) signaling, epithelial-mesenchymal transition (EMT) process, and cancer stem cells (CSCs) regulation. The combined utilization of miRNAs with other tests will help patients and clinicians to select the most appropriate personalized treatment and to avoid overdiagnosis and unnecessary biopsies. Future clinical applications of our reported novel miRNAs have a substantial role in the primary diagnosis of prostate cancer to help treatment decisions.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Clinical Utility of Prostate Health Index for Diagnosis of Prostate Cancer in Patients with PI-RADS 3 Lesions

The risk of prostate cancer (PCa) in prostate imaging reporting and data system version 2 (PI-RADSv2) score-3 lesions is equivocal; it is regarded as an intermediate status of presented PCa. In this study, we evaluated the clinical utility of the prostate health index (PHI) for the diagnosis of PCa and clinically significant PCa (csPCa) in patients with PI-RADSv2 score-3 lesions. The study cohort included patients who underwent a transrectal ultrasound (TRUS)-guided, cognitive-targeted biopsy for PI-RADSv2 score-3 lesions between November 2018 and April 2021. Before prostate biopsy, the prostate-specific antigen (PSA) derivatives, such as total PSA (tPSA), [-2] proPSA (p2PSA) and free PSA (fPSA) were determined. The calculation equation of PHI is as follows: [(p2PSA/fPSA) × tPSA ½]. Using a receiver operating characteristic (ROC) curve analysis, the values of PSA derivatives measured by the area under the ROC curve (AUC) were compared. For this study, csPCa was defined as Gleason grade 2 or higher. Of the 392 patients with PI-RADSv2 score-3 lesions, PCa was confirmed in 121 (30.9%) patients, including 59 (15.1%) confirmed to have csPCa. Of all the PSA derivatives, PHI and PSA density (PSAD) showed better performance in predicting overall PCa and csPCa, compared with PSA (all p < 0.05). The AUC of the PHI for predicting overall PCa and csPCa were 0.807 (95% confidence interval (CI): 0.710−0.906, p = 0.001) and 0.819 (95% CI: 0.723−0.922, p < 0.001), respectively. By the threshold of 30, PHI was 91.7% sensitive and 46.1% specific for overall PCa, and was 100% sensitive for csPCa. Using 30 as a threshold for PHI, 34.4% of unnecessary biopsies could have been avoided, at the cost of 8.3% of overall PCa, but would include all csPCa.

Utility of serum biomarkers for predicting cancer in patients with previous negative prostate biopsy

PURPOSE

To review the role of serum biomarkers: prostate-specific antigen (PSA), PSA density (PSAD), free:total PSA ratio, prostate health index (PHI) and PHI density (PHID), along with magnetic resonance imaging (MRI) for identification of clinically significant prostate cancer (PCa), comparing their utility in patients with persistently raised PSA levels after a prior negative prostate biopsy (PNB).

METHODS

In this single-centre prospective observational study conducted from September 2015 to October 2020, patients underwent a saturation biopsy via the transperineal route. If a Prostate Imaging Reporting and Data System version 2 (PIRADS) 3 and above lesion was seen on MRI, targeted biopsies were also obtained. Information on clinical history, lesion characteristics, PIRADS classification and follow-up was collected. The sensitivity, specificity and area under curve (AUC) for each of the biomarkers were calculated.

RESULTS

351 men underwent saturation biopsy with or without targeted biopsies. 103 patients had a PNB. Among this PNB cohort, 43 (41.7%) men had a benign outcome, while 60 (58.3%) men had histopathologically diagnosed PCa, of which 41 (39%) were clinically significant. All patients underwent multiparametric MRI scans prior to biopsy. Within this cohort, PHI and PHID had the best abilities to predict for clinically significant PCa with an AUC of 0.73 and 0.70 respectively, compared to 0.65 for PSAD, 0.34 for free:total PSA and 0.56 for PSA.

CONCLUSION

A significant proportion of patients are diagnosed with PCa after a PNB. This study shows that PHI and PHI densities may be suitable adjuncts predicting for clinically significant PCa in patients with PNB.

Prostate health index (PHI) as a reliable biomarker for prostate cancer: a systematic review and meta-analysis

OBJECTIVES

Prostate cancer (PCa) represents the second most common solid cancer in men worldwide. In the last decades, the prostate health index (PHI) emerged as a reliable biomarker for detecting PCa and differentiating between non-aggressive and aggressive forms. However, before introducing it in clinical practice, more evidence is required. Thus, we performed a systematic review and meta-analysis for assessing the diagnostic performance of PHI for PCa and for detecting clinically significant PCa (csPCa).

METHODS

Relevant publications were identified by a systematic literature search on PubMed and Web of Science from inception to January 11, 2022.

RESULTS

Sixty studies, including 14,255 individuals, met the inclusion criteria for our meta-analysis. The pooled sensitivity and specificity of PHI for PCa detection was 0.791 (95%CI 0.739-0.834) and 0.625 (95%CI 0.560-0.686), respectively. The pooled sensitivity and specificity of PHI for csPCa detection was 0.874 (95%CI 0.803-0.923) and 0.569 (95%CI 0.458-0.674), respectively. Additionally, the diagnostic odds ratio was 6.302 and 9.206, respectively, for PCa and csPCa detection, suggesting moderate to good effectiveness of PHI as a diagnostic test.

CONCLUSIONS

PHI has a high accuracy for detecting PCa and discriminating between aggressive and non-aggressive PCa. Thus, it could be useful as a biomarker in predicting patients harbouring more aggressive cancer and guiding biopsy decisions.

Can we omit systematic biopsies in patients undergoing MRI fusion-targeted prostate biopsies?

Magnetic resonance imaging (MRI)-targeted prostate biopsy is the recommended investigation in men with suspicious lesion(s) on MRI. The role of concurrent systematic in addition to targeted biopsies is currently unclear. Using our prospectively maintained database, we identified men with at least one Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesion who underwent targeted and/or systematic biopsies from May 2016 to May 2020. Clinically significant prostate cancer (csPCa) was defined as any Gleason grade group ≥2 cancer. Of 545 patients who underwent MRI fusion-targeted biopsy, 222 (40.7%) were biopsy naïve, 247 (45.3%) had previous prostate biopsy(s), and 76 (13.9%) had known prostate cancer undergoing active surveillance. Prostate cancer was more commonly found in biopsy-naïve men (63.5%) and those on active surveillance (68.4%) compared to those who had previous biopsies (35.2%; both P < 0.001). Systematic biopsies provided an incremental 10.4% detection of csPCa among biopsy-naïve patients, versus an incremental 2.4% among those who had prior negative biopsies. Multivariable regression found age (odds ratio [OR] = 1.03, P = 0.03), prostate-specific antigen (PSA) density ≥0.15 ng ml^-2 (OR = 3.24, P < 0.001), prostate health index (PHI) ≥35 (OR = 2.43, P = 0.006), higher PI-RADS score (vs PI-RADS 3; OR = 4.59 for PI-RADS 4, and OR = 9.91 for PI-RADS 5; both P < 0.001) and target lesion volume-to-prostate volume ratio ≥0.10 (OR = 5.26, P = 0.013) were significantly associated with csPCa detection on targeted biopsy. In conclusion, for men undergoing MRI fusion-targeted prostate biopsies, systematic biopsies should not be omitted given its incremental value to targeted biopsies alone. The factors such as PSA density ≥0.15 ng ml^-2, PHI ≥35, higher PI-RADS score, and target lesion volume-to-prostate volume ratio ≥0.10 can help identify men at higher risk of csPCa.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Role of prostate health index to predict Gleason score upgrading and high-risk prostate cancer in radical prostatectomy specimens

We evaluated the role of prostate health index (PHI) in predicting Gleason score (GS) upgrading in International Society of Urological Pathology Grade Group (ISUP GG) 1 & 2 prostate cancer (PCa) or adverse pathologic outcomes at radical prostatectomy (RP). A total of 300 patients with prostate specific antigen ≥ 3 ng/mL, PHI and prostate biopsy (71 patients with RP included) were retrospectively included in the study. The primary study outcomes are PCa and clinically significant PCa (csPCa, defined as ISUP GG ≥ 2) diagnostic rate of PHI, and GS upgrading rate at RP specimen. The secondary outcomes are the comparison between GS upgrading and non-upgrading group, GS upgrading and high-risk PCa (ISUP GG ≥ 3 or ≥ pT3a) predictability of preoperative clinical factors. Overall, 139 (46.3%) and 92 (30.7%) were diagnosed with PCa and csPCa, respectively. GS upgrading rate was 34.3% in all patients with RP. Significant differences were shown in the total prostate volume (p = 0.047), the distribution of ISUP GG at biopsy (p = 0.001) and RP (p = 0.032), respectively. PHI values ≥ 55 [Odds ratio (OR): 3.64 (95% confidence interval (CI) = 1.05–12.68, p = 0.042] and presence of PI-RADS lesion ≥ 4 (OR: 7.03, 95% CI = 1.68–29.51, p = 0.018) were the significant predictors of GS upgrading in RP specimens (AUC = 0.737). PHI values ≥ 55 (OR: 9.05, 5% CI = 1.04–78.52, p = 0.046) is a significant factor for predicting adverse pathologic features in RP specimens (AUC = 0.781). PHI could predict GS upgrading in combination with PIRADS lesions ≥ 4 in ISUP GG 1 & 2. PHI alone could evaluate the possibility of high-risk PCa after surgery as well.

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.

Role of PCA3 and SelectMDx in the optimization of active surveillance in prostate cancer

INTRODUCTION & OBJECTIVES

A not negligible percentage of patients included in active surveillance (AS) for low and very low risk prostate cancer (PCa) are reclassified in the confirmatory biopsy or have disease progression during follow-up. Our aim is to evaluate the role of PCA3 and SelectMDx, in an individual and combined way, in the prediction of pathological progression (PP) in a standard AS program.

MATERIALS & METHODS

Prospective and observational study comprised of 86 patients enrolled in an AS program from 2009 to 2019, with results for PCA3 and SelectMDx previous to PCa diagnosis or during their confirmatory period. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinical and pathological variables with PP-free survival (PPFS). The most reliable cut-offs for both biomarkers in the context of AS were defined.

RESULTS

SelectMDx showed statistically significant differences related to PPFS (HR 1.035, 95%CI: 1.012-1.057) (p = 0.002) with a C-index of 0.670 (95%CI: 0.529-0.810) and AUC of 0.714 (95%CI: 0.603-0.825) at 5 years. In our series, the most reliable cut-off point for SelectMDx was 5, with a sensitivity and specificity for PP of 69.8% and 67.4%, respectively. Same figure for PCA3 was 65, with a sensitivity and specificity for PP of 51.16% and 74.42%, respectively. The combination of both biomarkers did not improve the prediction of PP, C-index 0.630 (95%CI: 0.455-0.805).

CONCLUSIONS

In the context of low or very low risk PCa, SelectMDx > 5 predicted 5 years PP free survival with a moderate discrimination ability outperforming PCA3. The combination of both tests did not improved outcomes.

Role of PCA3 and SelectMDx in the optimization of active surveillance in prostate cancer

INTRODUCTION AND OBJECTIVES

A not negligible percentage of patients included in active surveillance (AS) for low and very low risk prostate cancer (PCa) are reclassified in the confirmatory biopsy or have disease progression during follow-up. Our aim is to evaluate the role of PCA3 and SelectMDx, in an individual and combined way, in the prediction of pathological progression (PP) in a standard AS program.

MATERIALS AND METHODS

Prospective and observational study comprised of 86 patients enrolled in an AS program from 2009 to 2019, with results for PCA3 and SelectMDx previous to PCa diagnosis or during their confirmatory period. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinical and pathological variables with PP-free survival (PPFS). The most reliable cut-offs for both biomarkers in the context of AS were defined.

RESULTS

SelectMDx showed statistically significant differences related to PPFS (HR: 1.035; 95%CI: 1.012-1.057) (P=.002) with a C-index of 0.670 (95%CI: 0.529-0.810) and AUC of 0.714 (95%CI: 0.603-0.825) at 5years. In our series, the most reliable cut-off point for SelectMDx was 5, with a sensitivity and specificity for PP of 69.8% and 67.4%, respectively. Same figure for PCA3 was 65, with a sensitivity and specificity for PP of 51.16% and 74.42%, respectively. The combination of both biomarkers did not improve the prediction of PP, C-index 0.630 (95%CI: 0.455-0.805).

CONCLUSIONS

In the context of low or very low risk PCa, SelectMDx >5 predicted 5years PP free survival with a moderate discrimination ability outperforming PCA3. The combination of both tests did not improved outcomes.

Review of novel liquid-based biomarkers for prostate cancer: towards personalised and targeted medicine

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortalities in both American and Canadian men. At present, serum prostate-specific antigen levels remain the most commonly used test to detect prostate cancer, and the standard and definitive diagnosis of the disease is via prostate biopsy. Conventional tissue biopsies are usually invasive, expensive, painful, time-consuming, and unsuitable for screening and need to be consistently evaluated by expert pathologists and have limited repeatability. Consequently, liquid biopsies are emerging as a favourable alternative to conventional tissue biopsies, providing a non-invasive and cost-effective approach for screening, diagnosis, treatment and monitoring of prostate cancer patients.

Materials and methods:

We searched several databases from August to December 2020 for relevant studies published in English between 2000 and 2020 and reporting on liquid-based biomarkers available in detectable quantities in patient bodily fluid samples. In this narrative review paper, we describe seven novel and promising liquid-based biomarkers that potentially account for individual patient variability as well as used in disease risk assessment, screening for early disease detection and diagnosis, identification of patients’ risk for metastatic disease and subsequent relapse, monitoring patient response to specific treatment and providing clinicians the potential to stratify patients likely to benefit from a particular treatment.

Conclusions:

The concept of precision medicine from prevention to treatment techniques that take individual patient variability into account will depend on the development of effective clinical biomarkers that interrogate key aberrant pathways potentially targetable with molecular targets or immunologic therapies. Liquid-based biomarkers with high sensitivity and specificity for prostate cancer are emerging as minimally invasive, lower risk, readily obtainable and easily repeatable technique for screening for early disease detection and diagnosis, patient stratification at diagnosis into different risk categories, identification of patients’ risk for metastatic disease and subsequent relapse, and real-time monitoring of patient response to specific treatment. Thus, effective liquid-based biomarkers will potentially shift the treatment paradigm of prostate cancer towards more personalised and targeted medicine.

miRNAs as Therapeutic Tools and Biomarkers for Prostate Cancer

Prostate cancer (PCa) is the fifth cause of tumor-related deaths in man worldwide. Despite the considerable improvement in the clinical management of PCa, several limitations emerged both in the screening for early diagnosis and in the medical treatment. The use of prostate-specific antigen (PSA)-based screening resulted in patients’ overtreatment and the standard therapy of patients suffering from locally advanced/metastatic tumors (e.g., radical prostatectomy, radiotherapy, and androgen deprivation therapy) showed time-limited efficacy with patients undergoing progression toward the lethal metastatic castration-resistant PCa (mCRPC). Although valuable alternative therapeutic options have been recently proposed (e.g., docetaxel, cabazitaxel, abiraterone, enzalutamide, and sipuleucel-T), mCRPC remains incurable. Based on this background, there is an urgent need to identify new and more accurate prostate-specific biomarkers for PCa diagnosis and prognosis and to develop innovative medical approaches to counteract mCRPC. In this context, microRNA (miRNAs) emerged as potential biomarkers in prostate tissues and biological fluids and appeared to be promising therapeutic targets/tools for cancer therapy. Here we overview the recent literature and summarize the achievements of using miRNAs as biomarkers and therapeutic targets/tools for fighting PCa.

The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer

To evaluate the performance of the Prostate Health Index (PHI) in magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion prostate biopsy for the detection of clinically significant prostate cancer (csPCa). We prospectively enrolled 164 patients with at least one Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) ≥ 3 lesions who underwent MRI-TRUS fusion prostate biopsy. Of the PSA-derived biomarkers, the PHI had the best performance in predicting csPCa (AUC 0.792, CI 0.707–0.877) in patients with PI-RADS 4/5 lesions. Furthermore, the predictive power of PHI was even higher in the patients with PI-RADS 3 lesions (AUC 0.884, CI 0.792–0.976). To minimize missing csPCa, we used a PHI cutoff of 27 and 7.4% of patients with PI-RADS 4/5 lesions could have avoided a biopsy. At this level, 2.0% of cases with csPCa would have been missed, with sensitivity and NPV rates of 98.0% and 87.5%, respectively. However, the subgroup of PI-RADS 3 was too small to define the optimal PHI cutoff. PHI was the best PSA-derived biomarker to predict csPCa in MRI-TRUS fusion prostate biopsies in men with PI-RADS ≥ 3 lesions, especially for the patients with PI-RADS 3 lesions who gained the most value.

Diagnostic Strategies for Treatment Selection in Advanced Prostate Cancer

Prostate Cancer (PCa) is a leading cause of morbidity and mortality among men worldwide. For most men with PCa, their disease will follow an indolent course. However, advanced PCa is associated with poor outcomes. There has been an advent of new therapeutic options with proven efficacy for advanced PCa in the last decade which has improved survival outcomes for men with this disease. Despite this, advanced PCa continues to be associated with a high rate of death. There is a lack of strong evidence guiding the timing and sequence of these novel treatment strategies. This paper focuses on a review of the strategies for diagnostic and the current evidence available for treatment selection in advanced PCa.

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

Background:

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

Materials and methods:

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

Conclusion:

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

Detection and Prognosis of Prostate Cancer Using Blood-Based Biomarkers

Prostate cancer (PCa) is second only to lung cancer as a cause of death. Clinical assessment of patients and treatment efficiency therefore depend on the disease being diagnosed as early as possible. However, due to issues regarding the use of prostate-specific antigen (PSA) for screening purposes, PCa management is among the most contentious of healthcare matters. PSA screening is problematic primarily because of diagnosis difficulties and the high rate of false-positive biopsies. Novel PCa biomarkers, such as the Prostate Health Index (PHI) and the 4Kscore, have been proposed in recent times to improve PSA prediction accuracy and have shown higher performance by preventing redundant biopsies. The 4Kscore also shows high precision in determining the risk of developing high-grade PCa, whereas elevated PHI levels suggest that the tumor is aggressive. Some evidence also supports the effectiveness of miRNAs as biomarkers for distinguishing PCa from benign prostatic hyperplasia and for assessing the aggressiveness of the disease. A number of miRNAs that possibly act as tumor inhibitors or oncogenes are impaired in PCa. These new biomarkers are comprehensively reviewed in the present study in terms of their potential use in diagnosing and treating PCa.

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

INTRODUCTION

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

OBJECTIVE

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

SETTING

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

METHODS AND PARTICIPANTS

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

RESULTS

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

CONCLUSIONS

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

A novel fluorescent probe for the early detection of prostate cancer based on endogenous zinc sensing

BACKGROUND

The early detection of prostate cancer can significantly optimize the prognosis, prolong patient lifespan, and improve quality of life. It has been well documented that prostate cancer tissues have lower zinc content than normal prostate tissues due to an impairment of the zinc accumulation mechanism.

METHODS

A novel diketopyrrolopyrrole (DPP)-based fluorescent zinc ion probe named DPP-C2 was prepared. The fluorescent intensity of this novel molecule is in direct proportion to environmental zinc concentration. Malignant (DU145 and PC3 cells) and normal prostate epithelial RWPE-1 cells were tested. Prostate cancer tissues were also cultured and observed as tissue sections. The probe was also intravenously administered to tumor-bearing (DU145 and PC3 cells) nude mice and observed under a whole-body fluorescence live-imaging system.

RESULTS

The probe showed minimal cytotoxicity to malignant and normal prostate cells. The RWPE-1 cells showed not only stronger baseline fluorescence but also a significant increase in signal intensity after culturing in a zinc-supplemented medium. In human prostate sections, the pathologically confirmed cancer tissues exhibited weaker fluorescence signals than normal and benign hyperplastic tissues. With proper excitation, prostate tissues revealed more intense fluorescence signals than tumor tissues, whereas other surrounding tissues showed almost no fluorescence.

CONCLUSIONS

The novel zinc ion fluorescent probe DPP-C2 is low toxic and showed potential application for the early detection of prostate cancer based on endogenous zinc sensing.

Diagnosis of prostate cancer

Diagnosis of prostate cancer (PCa) and adequate staging play a fundamental role for clinical and patient care. Despite major advances in biology and imaging, rectal examination and prostate-specific antigen (PSA) blood test remain the cornerstone for screening, and multiparametricmagnetic resonance imaging (mpMRI) for local staging. Recent advances in mpMRI lead to standardised interpretation and increased prescription by clinicians in order to improve detection of clinically significant PCa and select patients requiring targeted biopsies. However its indication remains controversial in biopsy-naïve patients. Nuclear medicine is also in a continuous evolution and utilisation of new radiopharmaceutical agent like choline or 68gallium with computed tomography or magnetic resonance imaging has led to the improvement in the detection of lymph nodes, distant metastases and prostate recurrence. Considering this very heterogneneous disease, combined utilisation of these tools will help clinicians and patients in choosing the most appropriate and personalised treatment.

The Ability of Prostate Health Index (PHI) to Predict Gleason Score in Patients With Prostate Cancer and Discriminate Patients Between Gleason Score 6 and Gleason Score Higher Than 6-A Study on 320 Patients After Radical Prostatectomy

Aim:

The purpose of this study was to investigate the Prostate Health Index as a marker for tumor aggressiveness in prostate biopsy and the optimization of indication for treatment options.

Methods:

Our cohort consisted of 320 patients indicated for radical prostatectomy with preoperative measurements of total prostate-specific antigen, free prostate-specific antigen, [-2]proPSA, calculated %freePSA, and Prostate Health Index. The Gleason score was determined during biopsy and after radical prostatectomy. Using the Gleason score, we divided the group of patients into the 2 subgroups: Gleason score ≤6 and Gleason score >6. This division was performed according to the biopsy Gleason score and according to the postoperative Gleason score. We compared total prostate-specific antigen, [-2]proPSA, %freePSA, and Prostate Health Index in the subgroups Gleason score ≤6 and Gleason score >6 after biopsy and the definitive score.

Results:

On evaluation of the subgroups created by Gleason score ≤6 and Gleason score >6, we observed agreement between biopsy Gleason score and definitive Gleason score in only 45.3% of cases. Of the calculated biopsy, Gleason score ≤6 and Gleason score >6 subgroups, [-2]proPSA, and Prostate Health Index (P = .0003 and P = .0005) were statistically significant. Of the definitive Gleason score ≤6 and Gleason score >6 subgroups, Prostate Health Index, [-2]proPSA, %freePSA, and PSA (P < .0001, P < .0001, P = .0003, and P = .0043) were statistically significant. The best area under the curve value (0.7496) was achieved by Prostate Health Index when the subgroups were established according to the postoperative Gleason score.

Conclusion:

Prostate Health Index is the best of the tested markers for the categorization of Gleason score 6 tumors and for facilitating the management of patients with prostate cancer. Prostate Health Index can be a helpful marker for indication of active surveillance or radical prostatectomy. Prostate health index can also simplify the decision of whether to perform nerve-sparing radical prostatectomy.

Are localized prostate cancer biomarkers useful in the clinical practice?

Prostate cancer presents itself in a heterogeneous way with both aggressive and indolent forms. Despite the controversy surrounding its use, prostate-specific antigen screening ultimately leads to a greater number of diagnosed patients. One of the biggest challenges in clinical practice is to select the right patients for biopsy and, among diagnosed patients, to differentiate tumors with an indolent course from those with an unfavorable prognosis, in order to determine the best therapeutic decision for each case, avoiding unnecessary interventions. Currently, several types of biomarkers are available for clinical use in patients with prostate cancer, which include blood-based (prostate-specific antigen, Prostate Health Index®, 4K score®); urine sample-based (PCA3, SelectMDx®, ExoDx Prostate IntelliScore®); and biopsy, transurethral resection, or radical prostatectomy tissue-based (ConfirmMDx®, Oncotype®, Prolaris®, Decipher®). The aim of this review is to provide an overview of the current state of evidence and to highlight recent advances in the evaluation and diagnosis of prostate cancer, with emphasis on biomarkers related to diagnosis and to prognostic evaluation of localized prostate cancer.

A Q-Probes Study Involving Utilization of Free Prostate-Specific Antigen, Factor V Leiden, and Hepatitis A Serology Tests

Context.—

Managing the utilization of laboratory tests is an important quality improvement activity that adds value to health care.

Objective.—

To examine utilization of 3 laboratory tests and identify factors that impact performance.

Design.—

Test utilization performance was evaluated by determining the frequency with which appropriate preconditions for testing were met. This included 30 testing episodes each involving (1) free prostate-specific antigen (PSA) when total PSA was within an appropriate interpretable range, (2) total anti–hepatitis A virus antibody when previous anti–hepatitis A virus antibody results were either negative or not done, and (3) factor V Leiden mutation when a previous result was not already available. Participants also provided information regarding some of their utilization policies and procedures for these 3 tests.

Results.—

The overall frequency with which testing criteria were met was 20.6% (163 of 790), 91.5% (649 of 709), and 95.2% (799 of 839) for free PSA, anti–hepatitis A virus antibody, and factor V Leiden, respectively. Utilization review was infrequent and done by 20.7% (6 of 29) of participants for factor V Leiden, 3.6% (1 of 28) for anti–hepatitis A virus antibody, and 3.6% (1 of 28) for free PSA. No practice or demographic characteristics were significantly associated with utilization performance for any test.

Conclusions.—

Utilization review was infrequent for the 3 tests examined. Variable amounts of unnecessary testing were observed for all tests, most frequently for free PSA, for which reporting results carried the added risk of diagnostic error from misinterpretation of results.

Plasma ghrelin O-acyltransferase (GOAT) enzyme levels: A novel non-invasive diagnosis tool for patients with significant prostate cancer

Early detection of PCa faces severe limitations as PSA displays poor‐specificity/sensitivity. As we recently demonstrated that plasma ghrelin O‐acyltransferase (GOAT)‐enzyme is significantly elevated in PCa‐patients compared with healthy‐controls, using a limited patients‐cohort, we aimed to further explore the potential of GOAT to improve PCa diagnosis using an ample patients‐cohort (n = 312) and defining subgroups (i.e. significant PCa/metastatic patients, etc.) that could benefit from this biomarker. Plasma GOAT‐levels were evaluated by ELISA in patients with (n = 183) and without (n = 129) PCa. Gleason Score ≥ 7 was considered clinically significant PCa. GOAT‐levels were higher in PCa patients vs control patients, and in those with significant PCa vs non‐significant PCa. GOAT‐levels association with the diagnoses of significant PCa was independent from traditional clinical variables (i.e. PSA/age/DRE). Remarkably, GOAT outperformed PSA in patients with PSA‐levels ranging 3‐20 ng/mL for the significant PCa diagnosis [GOAT‐AUC = 0.612 (0.531‐0.693) vs PSA‐AUC = 0.494 (0.407‐0.580)]. A panel of key variables including GOAT/age/DRE/testosterone also outperformed the same panel but with PSA [AUC = 0.720 (0.710‐0.730) vs AUC = 0.705 (0.695‐0.716), respectively]. Notably, GOAT‐levels could also represent a novel predictive biomarker of aggressiveness, as its levels are positively associated with Gleason Score and the presence of metastasis at the time of diagnoses. Altogether, our data reveal that GOAT‐levels can be used as a non‐invasive biomarker for significant PCa diagnosis in patients at risk of PCa (with PSA: 3‐20 ng/mL).

A multiparametric approach to improve upon existing prostate cancer screening and biopsy recommendations

PURPOSE OF REVIEW

To provide an overview of how genetic, serum, and urine biomarkers can help identify men at high risk for prostate cancer (PCa) and aggressive disease and men who would benefit from prostate biopsy.

RECENT FINDINGS

Screening for PCa is controversial because of concerns about overdiagnosis and overtreatment of nonlife-threatening tumors. Therefore, an approach to screening that includes a detailed family history with genetic testing of risk single nucleotide polymorphisms and high-penetrance genetic variants should be considered. After an elevated serum prostate-specific antigen (PSA) level has been confirmed, obtaining additional information (family history, biomarkers, and imaging) should be considered before recommending a prostate biopsy.

SUMMARY

There are now genetic tests that can help identify men who would benefit from PSA testing. Additional biomarker and imaging tests should be offered to those men who are confirmed to have elevated PSA values. These new biomarkers and imaging tests can improve the specificity of PSA testing while missing a small percentage of high-grade tumors. The path forward involves a multiparametric risk assessment based on clinical data and these new tests.

Combining Prostate Health Index density, magnetic resonance imaging and prior negative biopsy status to improve the detection of clinically significant prostate cancer

OBJECTIVES

To determine the performance of Prostate Health Index (PHI) density (PHID) combined with MRI and prior negative biopsy (PNB) status for the diagnosis of clinically significant prostate cancer (PCa).

PATIENTS AND METHODS

Patients without a prior diagnosis of PCa, with elevated prostate-specific antigen and a normal digital rectal examination who underwent PHI testing prospectively prior to prostate biopsy were included in this study. PHID was calculated retrospectively using prostate volume derived from transrectal ultrasonography at biopsy. Univariable and multivariable logistic regression modelling, along with receiver-operating characteristic (ROC) curve analysis, was used to determine the ability of serum biomarkers to predict clinically significant PCa (defined as either grade group [GG] ≥2 disease or GG1 PCa detected in >2 cores or >50% of any one core) on biopsy. Age, PNB status and Prostate Imaging Reporting and Data System (PI-RADS) score were incorporated into the regression models.

RESULTS

Of the 241 men who qualified for the study, 91 (37.8%) had clinically significant PCa on biopsy. The median (interquartile range) PHID was 0.74 (0.44-1.24); it was 1.18 (0.77-1.83) and 0.55 (0.38-0.89) in those with and without clinically significant PCa on biopsy, respectively (P < 0.001). On univariable logistic regression, age and PNB status were associated with clinically significant cancer. Of the tested biomarkers, PHID demonstrated the highest discriminative ability for clinically significant disease (area under the ROC curve [AUC] 0.78 for the univariable model). That continued to be the case in multivariable logistic regression models incorporating age and PNB status (AUC 0.82). At a threshold of 0.44, representing the 25th percentile of PHID in the cohort, PHID was 92.3% sensitive and 35.3% specific for clinically significant PCa; the sensitivity and specificity were 93.0% and 32.4% and 97.4% and 29.1% for GG ≥2 and GG ≥3 disease, respectively. In the 104 men who underwent MRI, PI-RADS score was complementary to PHID, with a PI-RADS score ≥3 or, if PI-RADS score ≤2, a PHID ≥0.44, detecting 100% of clinically significant disease. For that subgroup, of the biomarkers tested, PHID (AUC 0.90) demonstrated the highest discriminative ability for clinically significant disease on multivariable logistic regression incorporating age, PNB status and PI-RADS score.

CONCLUSIONS

In this contemporary cohort of men undergoing prostate biopsy for the diagnosis of PCa, PHID outperformed PHI and other PSA derivatives in the diagnosis of clinically significant cancer. Incorporating age, PNB status and PI-RADS score led to even further gains in the diagnostic performance of PHID. Furthermore, PI-RADS score was found to be complementary to PHID. Using 0.44 as a threshold for PHID, 35.3% of unnecessary biopsies could have been avoided at the cost of missing 7.7% of clinically significant cancers. Despite these encouraging results, prospective validation is needed.

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.

Biomarkers for Prostate Biopsy and Risk Stratification of Newly Diagnosed Prostate Cancer Patients

INTRODUCTION

Many new markers are now available as an aid for decisions about prostate biopsy for men without prostate cancer, and/or to improve risk stratification for men with newly diagnosed prostate cancer.

METHODS

A literature review was performed on currently available markers for use in decisions about prostate biopsy and initial prostate cancer treatment.

RESULTS

Although total prostate-specific antigen cutoffs were traditionally used for biopsy decisions, PSA elevations are not specific. Repeating the PSA test, and adjusting for factors like age, prostate volume and changes over time can increase specificity for biopsy decisions. The Prostate Health Index (phi) and 4K Score are new PSA-based markers that can be offered as second-line tests to decide on initial or repeat prostate biopsy. The PCA3 urine test and ConfirmMDx tissue test are additional options for repeat biopsy decisions. For men with newly diagnosed prostate cancer, genomic tests are available to refine risk classification and may influence treatment decisions.

CONCLUSIONS

Numerous secondary testing options are now available that can be offered to patients deciding whether to undergo prostate biopsy and those with newly diagnosed prostate cancer.

Role of mpMRI of the prostate in screening for prostate cancer

Prostate cancer screening offers the opportunity to significantly reduce morbidity and mortality from this disease. Currently, serum prostate-specific antigen (PSA) testing is the most widely used screening modality. However, PSA testing continues to have low positive and negative predictive value leading to unnecessary invasive prostate biopsy while missing patients with aggressive forms of the disease. Magnetic resonance imaging (MRI) has been gaining an increasingly large role in the management of patients with early stage prostate cancer including diagnosis in patients with abnormal PSA levels, monitoring of patients on active surveillance, and staging prior to definitive interventions. MRI-based prostate cancer risk assessment has been shown to better distinguish between clinically-significant and insignificant tumors than PSA testing alone or from nomograms. Preliminary data indicate that, among unselected patients, MRI outperforms PSA in the identification of patients with clinically significant prostate cancer. Further work is needed to examine the role of mpMRI in prostate cancer screening.

Prostate Health Index density improves detection of clinically significant prostate cancer

OBJECTIVES

To explore the utility of Prostate Health Index (PHI) density for the detection of clinically significant prostate cancer (PCa) in a contemporary cohort of men presenting for diagnostic evaluation of PCa.

PATIENTS AND METHODS

The study cohort included patients with elevated prostate-specific antigen (PSA; >2 ng/mL) and negative digital rectal examination who underwent PHI testing and prostate biopsy at our institution in 2015. Serum markers were prospectively measured per standard clinical pathway. PHI was calculated as ([{-2}proPSA/free PSA] × [PSA]^½ ), and density calculations were performed using prostate volume as determined by transrectal ultrasonography. Logistic regression was used to assess the ability of serum markers to predict clinically significant PCa, defined as any Gleason score ≥7 cancer or Gleason score 6 cancer in >2 cores or >50% of any positive core.

RESULTS

Of 118 men with PHI testing who underwent biopsy, 47 (39.8%) were found to have clinically significant PCa on biopsy. The median (interquartile range [IQR]) PHI density was 0.70 (0.43-1.21), and was 0.53 (0.36-0.75) in men with negative biopsy or clinically insignificant PCa and 1.21 (0.74-1.88) in men with clinically significant PCa (P < 0.001). Clinically significant PCa was detected in 3.6% of men in the first quartile of PHI density (<0.43), 36.7% of men in the IQR of PHI density (0.43-1.21), and 80.0% of men with PHI density >1.21 (P < 0.001). Using a threshold of 0.43, PHI density was 97.9% sensitive and 38.0% specific for clinically significant PCa, and 100% sensitive for Gleason score ≥7 disease. Compared with PSA (area under the curve [AUC] 0.52), PSA density (AUC 0.70), %free PSA (AUC 0.75), the product of %free PSA and prostate volume (AUC 0.79), and PHI (AUC 0.76), PHI density had the highest discriminative ability for clinically significant PCa (AUC 0.84).

CONCLUSIONS

Based on the present prospective single-centre experience, PHI density could be used to avoid 38% of unnecessary biopsies, while failing to detect only 2% of clinically significant cancers.

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.

Development of a Single Stranded DNA Aptamer as a Molecular Probe for LNCap Cells Using Cell-SELEX

BACKGROUND

Nowadays, highly specific aptamers generated by cell SELEX technology (systematic evolution of ligands by exponential enrichment) are being applied for early detection of cancer cells. Prostate Specific Membrane Antigen (PSMA), over expressed in prostate cancer, is a highly specific marker and therefore can be used for diagnosis of the prostate cancer cells. The aim of the present study was to select single-stranded DNA aptamers against LNCap cells highly expressing PSMA, using cell-SELEX method which can be used as a diagnostic tool for the detection of prostate cancer cells.

METHODS

After 10 rounds of cell-SELEX, DNA aptamers were isolated against PSMA using LNCaP cells as a target and PC-3 cell lines for counter SELEX. Five DNA aptamers with more than 70% affinity were selected up on flow cytometry analysis of positive clones.

RESULTS

Dissociation constants of two selected sequences (A12-B1) were estimated in the range of 33.78±3.77 and 57.49±2.214 pmol, respectively. Conserved secondary structures of A12 and B1 sequences suggest the necessity of these structures for binding with high affinity to native PSMA. Comparison of the secondary structures of our isolated aptamers and aptamer A10 obtained by protein SELEX showed similar stem-loop structures which could be responsible for the recognition of PSMA on LNCap cell surface.

CONCLUSION

Our results indicated that selected aptamers may turn out to be ideal candidates for the development of a detection tool and also can be used in targeted drug delivery for future smart drugs.