Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL.

PURPOSE: The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort. METHODS: This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort. RESULTS: In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed. CONCLUSION: PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Serum (-2)proPSA/freePSAratio, (-2)proPSA/freePSA density, prostate health index, and prostate health index density as clues to reveal postoperative clinically significant prostate cancer in men with prostate-specific antigen 2-10 ng/mL.

BACKGROUND: There is a strong clinical need to fill the gap of identifying clinically significant prostate cancer (csPCa) in men with prostate-specific antigen (PSA) gray zone values. Promising, but not definitive results have been obtained using PSA derivatives such as prostate health index (PHI) and PHI density (PHID) and the percentage (-2)proPSA/free PSA (%p2PSA/fPSA). Thus, this study aimed to compare the diagnostic value of PHI, PHID, %proPSA/fPSA, and (-2)proPSA/freePSA density (-2pPSA/fPSAD) for csPCa in the patients with PSA within 2-10 ng/mL. METHODS: Serum samples and clinicopathological features were prospectively collected from 142 patients who underwent robot-assisted radical prostatectomy  between September 2021 and December 2023. According to the inclusion criteria, the patients with total PSA  within 2 and 10 ng/mL and negative or suspicious digital rectal examination  were enrolled. We used two different classifications for csPCa: 1) patients with Gleason score (GS) ≥ 7(4 + 3) and 2) patients with GS ≥ 7(3 + 4). The receiver operating characteristic curves and the area under the curve (AUC) values were used to assess the diagnostic performance. RESULTS: Of the 142 men included, 116 (82%) patients were diagnosed with csPCa as GS ≥ 3 + 4 and 107 (75%) defined as csPCa as GS ≥ 7(4 + 3), respectively. We found that p2PSA/fPSA, p2PSA/fPSAD, PHI, and PHID were significantly higher in csPCa classified as GS ≥ 7(3 + 4) as well as GS ≥ 7(4 + 3), with p-values 0.027, 0.054, 0.0016, and 0.0027, respectively. AUCs of the analyzed variables were higher when used to predict csPCa as GS ≥ 6 compared to csPCa as GS ≥7(4 + 3), with an AUC equal, respectively, to 0.679 (95% CI: 0.571-0.786), 0.685 (95% CI: 0.571-0.799), 0.737 (95% CI: 0.639-0.836), and 0.736 (95% CI: 0.630-0.841) in the first subgroup and with an AUC equal, respectively, to 0.653 (95% CI: 0.552-0.754), 0.665 (95% CI: 0.560-0.770), 0.668 (95% CI: 0.568-0.769), and 0.670 (95% CI: 0.567-0.773) in the second, respectively. Both PHID and p2PSA/fPSAD allowed improvement in the diagnostic accuracy with respect to PHI and p2PSA/fPSA ratio, however the differences were not statistically significant (p = 0.409, 0.180 for csPCa as G ≥ Gleason grade (GG) 2 and 0.558 and 0.087 for csPCa as G ≥ GG3, respectively). We found that PHI, PHID, p2PSA/fPSA ratio, and p2PSA/fPSAD showed higher sensitivity, specificity, and positive predictive value when used to predict csPCa as GG ≥ 2, whereas negative predictive value of all four parameters was higher when used to predict GG ≥ 3. CONCLUSIONS: In men with a PSA level between 2 and 10 ng/mL, PHI and PHID, p2PSA/fPSA, and p2PSA/fPSAD showed good diagnostic performance for postoperative csPCa. However, PHID and p2PSA/fPSAD had a small advantage over PHI which needs to be further investigated for the reduction of unnecessary surgical interventions. This finding suggests that it could be a promising biomarker for making the treatment-decision strategy.

Preanalytical stability of molecular forms of prostate-specific antigen in serum samples (PSA, free PSA, [-2]proPSA) and their impact on fPSA/tPSA ratio and PHI.

BACKGROUND: Prostate cancer is a common cancer in men. Detection methods include the measurement of biomarkers: prostate-specific antigen (PSA), free PSA, [-2]proPSA, and the calculated indices: fPSA/tPSA ratio and Prostate Health Index (PHI). Proper preanalytical conditions are crucial for precise measurement and failure to adhere to protocols or regulations can influence the diagnostic algorithm. We assessed the stability of the above-mentioned biomarkers, fPSA/tPSA ratio and PHI, under various pre-analytical conditions. METHODS: Serum samples from 45 males were collected and stored under specific conditions before tPSA, fPSA, and [-2]proPSA were measured. Subsequently, the fPSA/tPSA and PHI were calculated. RESULTS: tPSA, fPSA, and [-2]proPSA remained stable during the two freeze-thaw cycles. Storage at 4°C and 22°C resulted in stable tPSA concentrations. However, fPSA levels decreased and [-2]proPSA levels increased over time. The fPSA/tPSA ratio remained stable for 72 h, at which point a decrease was observed in the samples kept at 4°C and 22°C. A gradual increase in PHI was observed in the samples kept at 4°C and 22°C. CONCLUSIONS: All biomarkers remained stable during two freeze-thaw cycles. tPSA was the most stable analyte when stored at 4°C, as well as at RT. A gradual increase of [-2]proPSA and a slight decrease in fPSA were observed during the storage test. This led to a decrease in the fPSA/tPSA ratio and an elevation in the PHI. We therefore recommend measuring prostate biomarkers promptly following blood collection. IMPACT: Understanding the pre-analytical stability of prostate biomarkers helps prevent false positive results and improve the accuracy of diagnostics for prostate cancer.

Utility of Prostate Health Index Density for Biopsy Strategy in Biopsy-Naïve Patients With PI-RADS v2.1 Category 3 Lesions.

BACKGROUND: Category 3 lesions in PI-RADSv2.1 pose diagnostic challenges, complicating biopsy decisions. Recent biomarkers like prostate health index (PHI) have shown higher specificity in detecting clinically significant prostate cancer (csPCa) than prostate-specific antigen (PSA). Yet their integration with MRI remains understudied. PURPOSE: To evaluate the utility of PSA and PHI with its derivatives for detecting csPCa in biopsy-naïve patients with category 3 lesion on initial prostate MRI scan. STUDY TYPE: Retrospective. POPULATION: One hundred ninety-three biopsy-naïve patients who underwent MRI, PSA, and PHI testing, followed by both targeted and systematic biopsies. FIELD STRENGTH/SEQUENCE: Turbo spin-echo T2-weighted imaging, diffusion-weighted single-shot echo-planar imaging, and dynamic contrast-enhanced T1-weighted fast field echo sequence imaging in 3 T. ASSESSMENT: PHI density (PHID) and PSA density (PSAD) derived by dividing serum PHI and PSA with prostate volume (MRI based methodology suggested by PI-RADSv2.1). Risk-stratified models to evaluate the utility of markers in triaging patients for biopsy, including low-, intermediate-, and high-risk groups. STATISTICAL TESTS: Independent t-test, Mann-Whitney U test, Mantel-Haenszel test, generalized estimating equation, and receiver operating characteristic (ROC) curve analysis were used. Statistical significance defined as P < 0.05. RESULTS: CsPCa was found in 16.6% (32/193) of patients. PHID had the highest area under the ROC curve (AUROC) of 0.793, followed by PHI of 0.752, PSAD of 0.750, and PSA of 0.654. PHID with two cut-off points (0.88/mL and 1.82/mL) showed the highest potential biopsy avoidance of 47.7% (92/193) with 5% missing csPCa, and the lowest intermediate-risk group (borderline decision group) at 38.9% (75/193), compared to PSA and PHI. DATA CONCLUSION: PHID demonstrated better potential in triaging patients with category 3 lesions, possibly aiding more selective and confident biopsy decisions for csPCa detection, than traditional markers. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 5.

A 2-year prospective evaluation of the Prostate Health Index in guiding biopsy decisions in a large cohort.

OBJECTIVES: To prospectively evaluate how the Prostate Health Index (PHI) impacts on clinical decision in a real-life setting for men with a prostate-specific antigen (PSA) level between 4 and 10 ng/mL and normal digital rectal examination. PATIENTS AND METHODS: Since 2016, the PHI has been available at no cost to eligible men in all Hong Kong public hospitals. All eligible patients who received PHI testing in all public Urology units (n = 16) in Hong Kong between May 2016 and August 2017 were prospectively included and followed up. All included men had a PHI test, with its result and implications explained; the subsequent follow-up plan was then decided via shared decision-making with urologists. Patients were followed up for 2 years, with outcomes including prostate biopsy rates and biopsy findings analysed in relation to the initial PHI measurements. RESULTS: A total of 2828 patients were followed up for 2 years. The majority (82%) had PHI results in the lower risk range (score <35). Knowing the PHI findings, 83% of the patients with elevated PSA decided not to undergo biopsy. In all, 11% and 45% opted for biopsy in the PHI score <35 and ≥35 groups, respectively. The initial detection rate of International Society of Urological Pathology (ISUP) Grade Group (GG) ≥2 cancer was higher in the PHI score ≥35 group (23%) than in the PHI score <35 group (7.9%). Amongst patients with no initial positive biopsy findings, the subsequent positive biopsy rate for ISUP GG ≥2 cancer was higher in the PHI score ≥35 group (34%) than the PHI score <35 group (13%) with a median follow-up of 2.4 years. CONCLUSION: In a real-life setting, with the PHI incorporated into the routine clinical pathway, 83% of the patients with elevated PSA level decided not to undergo prostate biopsy. The PHI pathway also improved the high-grade prostate cancer detection rate when compared to PSA-driven strategies. Higher baseline PHI predicted subsequent biopsy outcome at 2 years. The PHI can serve as a tool to individualise biopsy decisions and frequency of follow-up visits.

Incorporating PHI in decision making: external validation of the Rotterdam risk calculators for detection of prostate cancer.

PURPOSE: External validation of existing risk calculators (RC) to assess the individualized risk of detecting prostate cancer (PCa) in prostate biopsies is needed to determine their clinical usefulness. The objective was to externally validate the Rotterdam Prostate Cancer RCs 3 and 4 (RPCRC-3/4) and that incorporating PHI (RPCRC-PHI) in a contemporary Spanish cohort. METHODS: Multicenter prospective study that included patients suspicious of harboring PCa. Men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate the performance of the prediction models: discrimination (receiver operating characteristic (ROC) curves), calibration and net benefit [decision curve analysis (DCA)] were calculated. These analyses were carried out for detection of any PCa and clinically significant (cs)PCa, defined as ISUP grade ≥ 2. RESULTS: Among the 559 men included, 337 (60.28%) and 194 (34.7%) were diagnosed of PCa and csPCa, respectively. RPCRC-PHI had the best discrimination ability for detection of PCa and csPCa with AUCs of 0.85 (95%CI 0.82-0.88) and 0.82 (95%CI 0.78-0.85), respectively. Calibration plots showed that RPCRC-3/4 underestimates the risk of detecting PCa showing the need for recalibration. In DCA, RPCRC-PHI shows the highest net benefit compared to biopsy all men. CONCLUSIONS: The RPCRC-PHI performed properly in a contemporary clinical setting, especially for prediction of csPCa.

Clinical value of prostate health index as an indicator for recommending magnetic resonance imaging in patients with gray-zone prostate-specific antigen level.

PURPOSE: To evaluate the usefulness of prostate health index (PHI) as an indicator for recommending magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) gray zone level < 10 ng/mL. METHODS: 443 patients who underwent prostate biopsy (PB) after serum PHI test and MRI between April 2019 and December 2022 were enrolled. For patients with visible lesion on MRI with Prostate Imaging Reporting and Data System Score (PI-RADS) ≥ 3, MRI-targeted PB was performed in addition to systematic 12-core PB. RESULTS: The optimal cutoff value of PHI for predicting PI-RADS ≥ 3 lesions was 39.6, which was significantly associated with overall prostate cancer (OR 3.07, p = 0.018) and clinically significant prostate cancer (csPCa) (OR 4.15, p = 0.006) at MRI-targeted PB cores. When MRI was restricted to patients with PHI ≥ 39.6 alone, 28.7% of unnecessary MRI could be saved at the cost of missing 13.6% of csPCa. When omitting MRI for patients with PHI < 39.6 and PSAD < 0.12 ng/mL2, unnecessary MRI could be reduced by 20.1% with the risk of missing 6.2% of csPCa. With addition of systematic PB, 21.0% of patients with negative MRI-targeted PB were diagnosed as csPCa. CONCLUSIONS: For patients in PSA gray zone, PHI of 39.6 might be an indicator for MRI and further MRI-targeted PB in additional to PSAD of 0.12 ng/mL2, reducing 20.1% of unnecessary MRI with the minimal risk of missing 6.2% of csPCa. To maximize csPCa detection, combining both MRI-targeted and systematic PB should be also considered.

The function of Prostate Health Index in detecting clinically significant prostate cancer in the PI-RADS 3 population: a multicenter prospective study.

PURPOSE: The purpose of this study is to identify patients in the prostate imaging reporting and data system (PI-RADS) 3 population who need biopsy by using prostate health index (PHI) and other clinical parameters in order to avoid unnecessary biopsies. METHODS: A total of 302 patients from four hospital were enrolled, and 92 patients with PI-RADS 3 were included finally. All patients were biopsy-naïve and had suspicion of prostate cancer (PCa) with PSA level in 4-20 ng/ml and a normal digital rectal exam. Univariable and stepwise forward multivariable logistic regression analyses were used to evaluated the risk factors. The sensitivity, specificity, and positive and negative predictive values of different cut-off value of PHI were calculated for the diagnosis of clinically significant prostate cancer (CSPCa). RESULTS: The overall patient's mean age was 65.65 ± 9.55 years, median PSA was 7.68 (5.28-12.07) ng/ml and median PHI was 43.80 (33.09-64.69). PCa was identified in 32.61% (30/92) of PI-RADS 3 and CSPCa was identified in 28.26% (26/92) of PI-RADS 3. The risk factors for detecting PCa and CSPCa in multivariable regression analysis were age and PHI. When the biopsy was restricted to those PHI ≥ 43.5, 42.39% unnecessary biopsied could avoid. The sensitivity, specificity, positive predictive value and negative predictive value for the detection of CSPCa in the PHI ≥ 43.5 were 92.31%, 63.64%, 50% and 95.45% respectively. CONCLUSION: The inclusion of PHI in the diagnosis of the PI-RADS 3 population may avoid many unnecessary biopsies. The multivariable models could increase the detection of cancer.

Clinical utility of multiple secondary combined tests in prostate cancer screening.

INTRODUCTION: The clinical utility of concurrent Prostate Health Index (PHI) and ExosomeDx Prostate Intelliscore (EPI) testing is unclear. We sought to examine the performance of combined PHI and EPI testing on men undergoing elevated PSA work up. MATERIALS AND METHODS: Patients who received both EPI and PHI testing were identified from an institutional database of men referred to urology for an elevated total PSA. Cut points of EPI > 15.6 and PHI ≥ 36 were used to denote a positive test. Patients were placed into one of four groups determined by combination of EPI and PHI results. Demographic variables and biopsy recommendations were compared between groups. The concordance of test positivity between EPI and PHI was compared by Cohen's kappa. Demographic variables and secondary testing results were compared between patients' compliant and non-compliant with prostate biopsy recommendation. Biopsy pathology was compared between groups. RESULTS: A total of 162 patients had both EPI and PHI testing. Median age was 65 years, with a median PSA of 6.64 ng/mL. Age (p = 0.001), PSA (< 0.001) and biopsy recommendation (< 0.001) differed between combined secondary screening test result groups. Seventy-five percent of patients with both a positive EPI and PHI were found to have prostate cancer, with 54.2% being ≥ Gleason 7. Cohen's kappa was 0.19, indicating poor concordance. The AUC of EPI and PHI for clinically significant cancer was 0.563 (95% CI: 0.4331-0.6923) and 0.685 (95% CI: 0.569-0.8) (p = 0.147). CONCLUSIONS: Concurrently positive EPI and PHI indicate increased prostate cancer risk, with combined usage potentially influencing biopsy recommendation and compliance.

The Value of the Prostate Health Index and Derived Indexes in the Diagnosis of Prostate Cancer with PI-RADS-3 Lesions.

INTRODUCTION: The purpose of this article was to evaluate the diagnostic value of prostate health index (PHI) and its derivatives in prostate cancer (PCa) with prostate imaging reporting and data system (PI-RADS)-3 lesions. METHODS: Patients with benign prostatic hyperplasia (BPH) (n = 155) were included in the BPH group, while all patients with PCa (n = 49) were enrolled in the PCa group. Between the groups, the serum concentrations of total prostate-specific antigen (TPSA), percent-free prostate-specific antigen (%fPSA), prostate health index (PHI), prostate health index density (PHID), and prostate-specific antigen density (PSAD) were compared. RESULTS: On average, 49 (24%) of 204 men had PCa on biopsy, with 81.63% of those cases being clinically serious. Age, prostate volume, TPSA, and PSAD did not significantly differ between the PCa group and the BPH group. In contrast, [-2]pro prostate-specific antigen (p2PSA) (17.10 ± 4.77 vs. 13.93 ± 3.22, p < 0.001), PHI (33.88 ± 8.81 vs. 25.83 ± 5.63, p < 0.001), and PHID (0.52 ± 0.15 vs. 0.38 ± 0.11, p < 0.001) showed a statistically significant difference between the two groups. Compared to conventional PSA, PHI (AUC = 0.786, 95% CI: 0.705-0.867) and PHID (AUC = 0.763, 95% CI: 0.684-0.843) were considerably better predictors of all PCa. The TPSA, %fPSA, p2PSA, PHI, PHID, and PSAD areas under the receiver operating characteristic for clinically significant PCa (csPCa) were 0.587, 0.650, 0.696, 0.823, 0.796, and 0.614, respectively. Out of all the various parameters, PHI and PHID performed very well in this cohort's biopsy outcome prediction. CONCLUSION: PHI offers the best diagnostic value for detecting PCa in cases of PI-RADS-3 lesions. Additionally, PHID raised the possibility of csPCa PI-RADS-3 lesions. However, more investigation is required to confirm our results by using multicenter collaboration.

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.

Comparison of PHI and PHI Density for Prostate Cancer Detection in a Large Retrospective Caucasian Cohort.

BACKGROUND: Beyond prostate-specific antigen (PSA), other biomarkers for prostate cancer (PCa) detection are available and need to be evaluated for clinical routine. OBJECTIVE: The aim of the study was to evaluate the Prostate Health Index (PHI) density (PHID) in comparison with PHI in a large Caucasian group >1,000 men. METHODS: PHID values were used from available patient data with PSA, free PSA, and [-2]pro-PSA and prostate volume from 3 former surveys from 2002 to 2014. Those 1,446 patients from a single-center cohort included 701 men with PCa and 745 with no PCa. All patients received initial or repeat biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing area under the ROC curves (AUCs), precision-recall approach, and decision curve analysis (DCA). RESULTS: PHID medians differed almost 2-fold between PCa (1.12) and no PCa (0.62) in comparison to PHI (48.6 vs. 33; p always <0.0001). However, PHID and PHI were equal regarding the AUC (0.737 vs. 0.749; p = 0.226), and the curves of the precision-recall analysis also overlapped in the sensitivity range between 70 and 100%. DCA had a maximum net benefit of only ∼5% for PHID versus PHI between 45 and 55% threshold probability. Contrary, in the 689 men with a prostate volume ≤40 cm3, PHI (AUC 0.732) showed a significant larger AUC than PHID (AUC 0.69, p = 0.014). CONCLUSIONS: Based on DCA, PHID had only a small advantage in comparison with PHI alone, while ROC analysis and precision-recall analysis showed similar results. In smaller prostates, PHI even outperformed PHID. The increment for PHID in this large Caucasian cohort is too small to justify a routine clinical use.

Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer.

BACKGROUND: Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility. METHODS: We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index. RESULTS: We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (Pcombined = 5.73 × 10-9 ), was also associated with phi values (Pcombined = 3.20 × 10-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01). CONCLUSION: Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.

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

BACKGROUND: The role of isoforms of prostate specific antigen (PSA) and other kallikrein-related markers in early detection of biochemical recurrence (BCR) after radical prostatectomy (RP) is not well known and serum PSA is currently used in preoperative risk nomograms. OBJECTIVE: The aim of this research was to study pre- and early postoperative levels of important PSA isoforms and human kallikrein-2 to determine their ability to predict BCR and identify disease persistence (DP). METHODS: This study included 128 consecutive patients who underwent RP for clinically localized prostate cancer. PSA, fPSA, %fPSA, [-2]proPSA, PHI and hK2 were measured preoperatively, at 1 and 3 months after RP. We determined the ability of these markers to predict BCR and identify DP. RESULTS: The DP and BCR rate were 11.7%and 20.3%respectively and the median follow up was 64 months (range 3-76 months). Preoperatively, the independent predictors of BCR were PSA (p-value 0.029), [-2]proPSA (p-value 0.002) and PHI (p-value 0.0003). Post-RP, PSA was the single marker correlating with BCR, both at one (p-value 0.0047) and 3 months (p-value 0.0004). PSA, fPSA, [-2]proPSA and PHI significantly correlated to DP at 1 and 3 months post-RP (p-value <  0.05), although PSA had the most significant existing correlation (p-value <  0.0001). CONCLUSIONS: [-2]proPSA and PHI are preoperative predictors of BCR and DP that outperform the currently used serum PSA. At the early postoperative period there is no additional benefit of the other markers tested.

PHI density prospectively improves prostate cancer detection.

PURPOSE: To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort. METHODS: PHID values were calculated from prostate-specific antigen (PSA), free PSA and [- 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate cancer (PCa) and 505 with no evidence of malignancy (NEM). In detail, 562 patients were biopsied at the Charité Hospital Berlin and 495 patients at the Sana Hospital Offenbach. All patients received systematic or magnetic resonance imaging (MRI)/ultrasound fusion-guided biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing areas under the ROC-curves (AUC). The decision curve analysis (DCA) was performed with the MATLAB Neural Network Toolbox. RESULTS: PHID provided a significant larger AUC than PHI (0.835 vs. 0.801; p = 0.0013) in our prospective cohort of 1057 men from 2 centers. The DCA had a maximum net benefit of ~ 5% for PHID vs. PHI between 35 and 65% threshold probability. In those 698 men within the WHO-calibrated PSA grey-zone up to 8 ng/ml, PHID was also significantly better than PHI (AUC 0.819 vs. 0.789; p = 0.0219). But PHID was not different from PHI in the detection of significant PCa. CONCLUSIONS: Based on ROC analysis and DCA, PHID had an advantage in comparison with PHI alone to detect any PCa but PHI and PHID performed equal in detecting significant PCa.

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

PURPOSE: To compare the ability of Prostate Health Index (PHI) to diagnose csPCa, with that of total PSA, PSA density (PSAD) and the multiparametric magnetic resonance (mpMRI) of the prostate. METHODS: We analysed a group of 395 men planned for a prostate biopsy who underwent a mpMRI of the prostate evaluated using the PIRADS v1 criteria. All patients had their PHI measured before prostate biopsy. In patients with an mpMRI suspicious lesions, an mpMRI/ultrasound software fusion-guided biopsy was performed first, with 12 core systematic biopsy performed in all patients. A ROC analysis was performed for PCa detection for total PSA, PSAD, PIRADS score and PHI; with an AUC curve calculated for all criteria and a combination of PIRADS score and PHI. Subsequent sub-analyses included patients undergoing first and repeat biopsy. RESULTS: The AUC for predicting the presence of csPCa in all patients was 59.5 for total PSA, 69.7 for PHI, 64.9 for PSAD and 62.5 for PIRADS. In biopsy naive patients it was 61.6 for total PSA, 68.9 for PHI, 64.6 for PSAD and 63.1 for PIRADS. In patients with previous negative biopsy the AUC for total PSA, PHI, PSAD and PIRADS was 55.4, 71.2, 64.4 and 69.3, respectively. Adding of PHI to PIRADS increased significantly (p = 0.007) the accuracy for prediction of csPCa. CONCLUSION: Prostate Health Index could serve as a tool in predicting csPCa. When compared to the mpMRI, it shows comparable results. The PHI cannot, however, help us guide prostate biopsies in any way, and its main use may, therefore, be in pre-MRI or pre-biopsy triage.

The prostate health index and the percentage of [-2]proPSA maintain their diagnostic performance when calculated with total and free PSA from different manufacturers.

OBJECTIVES: To evaluate the diagnostic performance of the prostate health index (PHI) and of the percentage of [-2]proPSA (%[-2]proPSA) calculated with total and free PSA from non-Beckman Coulter manufacturers (Roche and Abbott), and compare it with the fully Beckman Coulter [-2]proPSA derivatives. METHODS: In this study, 237 men (PSA: 2-10 µg/L) scheduled for prostate biopsy were enrolled. %[-2]proPSA and PHI were calculated with total and free PSA from three manufacturers. Beckman Coulter PSA and [-2]proPSA were performed on the Access 2 analyzer (Hybritech calibration). Roche PSA was performed on the cobas e411 and the Abbott PSA on the Architect i2000sr. Statistical analysis was performed, considering prostate cancer (PCa) as the outcome. RESULTS: Univariate analysis showed that all indices were predictors of cancer, irrespective of the manufacturer (p<0.001). The AUC was similar for all manufacturers, both for %[-2]proPSA (Beckman Coulter: 0.756; Roche: 0.770; Abbott: 0.756) and PHI (Beckman Coulter: 0.776; Roche: 0.785; Abbott: 0.778). When considering the cutoffs that allowed 90% sensitivity, [-2]proPSA derivatives calculated with Roche and Abbott PSA had similar specificities and predictive values when compared to Beckman Coulter. The percentage of missed cancers (8-9%) was the same between manufacturers. The percentage of spared biopsies was significantly higher with Roche's PHI (21.0%) and Abbott's PHI (20.6%) than with Beckman Coulter's PHI (17.2%). CONCLUSIONS: In the PSA range between 2 and 10 µg/L, [-2]proPSA derivatives maintain their diagnostic performance in PCa detection when calculated with PSA from Roche and Abbott. This can lead to a broader implementation of these indices in clinical laboratories worldwide.

Usefulness of the prostate health index in predicting the presence and aggressiveness of prostate cancer among Korean men: a prospective observational study.

BACKGROUND: We aimed to evaluate the usefulness of the Beckman Coulter prostate health index (PHI) and to compare it with total prostate-specific antigen (PSA) levels and related derivatives in predicting the presence and aggressiveness of prostate cancer (PCa) in the Korean population. METHODS: A total of 140 men who underwent their first prostate biopsy for suspected PCa were included in this prospective observational study. The diagnostic performance of total PSA, free PSA, %free PSA, [-2] proPSA (p2PSA), %p2PSA, and PHI in detecting and predicting the aggressiveness of PCa was estimated using the receiver operating characteristic curve (ROC) and logistic multivariate regression analyses. RESULTS: Of 140 patients, PCa was detected in 63 (45%) of participants, and 48 (76.2%) of them had significant cancer with a Gleason score (GS) ≥ 7. In the whole group, the area under the curve (AUC) for ROC analysis of tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.63, 0.57, 0.69, 0.69, 0.72, and 0.76, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p = 0.005). For PCa with GS ≥ 7, the AUCs for tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.62, 0.58, 0.41, 0.79, 0.86, and 0.87, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p < 0.001). In the subgroup with tPSA 4-10 ng/mL, both %p2PSA and PHI were strong independent predictors for PCa (p = 0.007, p = 0.006) and significantly improved the predictive accuracy of a base multivariable model, including age, tPSA, fPSA and %fPSA, using multivariate logistic regression analysis. (p = 0.054, p = 0.048). Additionally, at a cutoff PHI value > 33.4, 22.9% (32/140) of biopsies could be avoided without missing any cases of aggressive cancer. CONCLUSIONS: This study shows that %p2PSA and PHI are superior to total PSA and %fPSA in predicting the presence and aggressiveness (GS ≥ 7) of PCa among Korean men. Using PHI, a significant proportion of unnecessary biopsies can be avoided.

Combining prostate health index and multiparametric magnetic resonance imaging in estimating the histological diameter of prostate cancer.

BACKGROUND: Although multiparametric magnetic resonance imaging (mpMRI) is widely used to assess the volume of prostate cancer, it often underestimates the histological tumor boundary. The aim of this study was to evaluate the feasibility of combining prostate health index (PHI) and mpMRI to estimate the histological tumor diameter and determine the safety margin during treatment of prostate cancer. METHODS: We retrospectively enrolled 72 prostate cancer patients who underwent radical prostatectomy and had received PHI tests and mpMRI before surgery. We compared the discrepancy between histological and radiological tumor diameter stratified by Prostate Imaging-Reporting and Data System (PI-RADS) score, and then assessed the influence of PHI on the discrepancy between low PI-RADS (2 or 3) and high PI-RADS (4 or 5) groups. RESULTS: The mean radiological and histological tumor diameters were 1.60 cm and 2.13 cm, respectively. The median discrepancy between radiological and histological tumor diameter of PI-RADS 4 or 5 lesions was significantly greater than that of PI-RADS 2 or 3 lesions (0.50 cm, IQR (0.00-0.90) vs. 0.00 cm, IQR (-0.10-0.20), p = 0.02). In the low PI-RADS group, the upper limit of the discrepancy was 0.2 cm; so the safety margin could be set at 0.1 cm. In the high PI-RADS group, the upper limits of the discrepancy were 1.2, 1.6, and 2.2 cm in men with PHI < 30, 30-60, and > 60; so the safety margin could be set at 0.6, 0.8, and 1.1 cm, respectively. CONCLUSIONS: Radiological tumor diameter on mpMRI often underestimated the histological tumor diameter, especially for PI-RADS 4 or 5 lesions. Combining mpMRI and PHI may help to better estimate the histological tumor diameter.