Different diagnostic strategies combining prostate health index and magnetic resonance imaging for predicting prostate cancer: A multicentre study

OBJECTIVE

To explore how prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) should be used in concert to improve diagnostic capacity for clinically significant prostate cancers (CsCaP) in patients with prostate-specific antigen (PSA) between 4 and 20 ng/ml.

METHODS

About 426 patients fulfilling the inclusion criteria were included in this study. Univariable and multivariable logistic analyses were performed to analyze the association between the clinical indicators and CaP/CsCaP. We used the Delong test to compare the differences in the area under the curve (AUC) values of four models for CaP and CsCaP. Decision curve analysis (DCA) and calibration plots were used to assess predictive performance. We compared clinical outcomes of different diagnostic strategies constructed using different combinations of the models by the chi-square test and the McNemar test.

RESULTS

The AUC of PHI-MRI (a risk prediction model based on PHI and mpMRI) was 0.859, which was significantly higher than those of PHI (AUC = 0.792, P < 0.001) and mpMRI (AUC = 0.797, P < 0.001). PHI-MRI had a higher net benefit on DCA for predicting CaP and CsCaP in comparison to PHI and mpMRI. Adding the PHI-MRI in diagnostic strategies for CsCaP, such as use PHI-MRI alone or sequential use of PHI followed by PHI-MRI, could reduce the number of biopsies by approximately 20% compared to use PHI followed by mpMRI (256 vs 316, 257 vs 316, respectively).

CONCLUSIONS

The PHI-MRI model was superior to PHI and MRI alone. It may reduce the number of biopsies and ensure the detection rate of CsCaP under an appropriate sensitivity at the cost of an increased number of MRI scans.

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.

Baseline prostate health index risk category and risk category changes during active surveillance predict grade reclassification

BACKGROUND

It is not known whether baseline prostate health index (PHI) at the initiation of active surveillance (AS) or repeated PHI testing during AS is of clinical value after confirmatory biopsy in AS men followed with multiparametric magnetic resonance imaging (mpMRI).

METHODS

We identified 382 AS patients with no greater than Grade Group 1 (GG1) prostate cancer on diagnostic and confirmatory biopsy, at least one mpMRI and PHI test, of which 241 had at least 2 PHI tests. Grade reclassification (GR) was defined as ≥GG2 on surveillance biopsy. PHI risk categories 1 to 4 were as defined by the manufacturer. Associations between baseline PHI risk category or baseline PSA density (PSAD), change in PHI risk categories over time or PSAD changes over time and GR were evaluated with multivariable Cox proportional hazard regression models adjusted for age, Prostate Imaging-Reporting and Data System score and number of positive cores.

RESULTS

Men with baseline PHI scores in the highest risk categories had lower rates of GR-free survival (log-rank P < 0.001), as did those who increased in PHI risk category or remained in a high PHI risk category during surveillance (log-rank P = 0.032). On multivariable regression, baseline PHI risk category was a predictor of GR (risk category 4 [vs. 1] hazard ratio [HR] 2.74, 95% confidence interval [CI] 1.32-5.66, P = 0.002, model C-index 0.764, Akaike Information Criterion [AIC] 797), as were PHI risk category changes over time (risk category 4 [vs. 1] HR 4.20, 95% CI 1.76-10.05, P = 0.002, C-index 0.759, AIC 489). Separate models with baseline PSAD and PSAD changes over time yielded C-indices of 0.709 (AIC 809) and 0.733 (AIC 495) respectively.

CONCLUSIONS

Baseline PHI risk category and PHI changes over time were both independent predictors of GR after confirmatory biopsy, but the added benefit over PSAD seemed modest. However, baseline PHI and PHI risk category changes provided clinically useful risk stratification for time to GR, so further evaluation of PHI's ability to help reduce the frequency of mpMRI and/or surveillance biopsies with more PHI data points over time may be warranted.

Prostate health index (PHI) as an accurate prostate cancer predictor

PURPOSE

This study aims to compare the ability of the PHI versus tPSA test to predict the presence of PCa in our population.

METHODS

A prospective observational study was performed. We included patients with tPSA ≥ 2.5 ng/ml, biopsy naïve or previous negative biopsy, undergoing a blood test, which includes tPSA, fPSA, and p2PSA, and a prostate biopsy between March 2019 and March 2022. Patients with PCa found in the biopsy-Group A-were compared with patients with a negative biopsy result-Group B. Diagnostic accuracy of tPSA and PHI was assessed by receiver operating characteristic [ROC] curves and logistic regression.

RESULTS

140 men were included. Fifty-seven (40.7%) had a positive prostate biopsy result (Group A), and 83 (59.3%) had a negative biopsy result (Group B). The mean age was similar in both groups (mean ± standard deviation), 66.86 ± 6.61 years. No difference was found in the tPSA value between the groups (Group A PSA: 6.11 ng/ml (3.56-17.01); Group B: 6.42 ng/ml (2.46-19.45), p = 0.41). The mean value of PHI was statistically different between groups (Group A 65.50 (29-146) vs. Group B 48 (16-233), p = 0.0001). The area under the curve 0.44 for tPSA and 0.77 for PHI. The multivariate logistic regression model applied to PHI showed a significant increase in its predictive accuracy: 72.14% in the model without PHI, 76.09% with PHI.

CONCLUSION

The PHI test improves PCa detection compared to tPSA in our population.

A prospective evaluation of the effect of finasteride on prostate health index (phi)

PURPOSE

5-alpha reductase inhibitor (5ARI) reduces prostate-specific antigen (PSA) by half but its effect on prostate health index (phi) is unknown. This study aims to investigate this effect and to enable accurate interpretation of phi in men with elevated PSA and on 5ARI.

METHODS

This is a prospective study evaluating the effect of finasteride on PSA, free PSA (fPSA), [ - 2]proPSA (p2PSA) and phi at 6 and 12 moths in men with PSA 4-20 ng/mL, no prior 5ARI use, and one negative prostate biopsy within 6 months before recruitment. The 5ARI Finasteride (5 mg/day) for 1 year was offered if International Prostatic Symptom Score (IPSS) was ≥ 8 at baseline. 5ARI group included patients taking finasteride, while control group included patients not on finasteride. The blood results were compared with t-test between baseline and different time points in each group and between groups at 1 year.

RESULTS

164 men fit the inclusion criteria and 150 were analyzed. In 5ARI group (n = 100) at 1 year, mean PSA reduced by 51.4% from 8.9(± SD 3.7) to 4.4(± SD 2.8)ng/mL (paired t-test, p < 0.001), fPSA reduced by 52.4% from 1.6(± 0.6) to 0.8(± 0.4)ng/mL (p < 0.001), p2PSA reduced by 55.3% from 18.4(± 8.8) to 8.3(± 5.6)pg/mL (p < 0.001), and phi reduced by 34.2% from 33.7(± 11.9) to 22.4(± 12.5) (p < 0.001). PSA and phi values in the control group remained static over 1 year and significantly higher than those in 5ARI group.

CONCLUSION

This study demonstrated p2PSA and phi are reduced by about 55% and 34% in men on 5ARI. A conversion factor of division by 0.66 is needed for phi in men on finasteride to allow the interpretation and use of phi in men on 5ARI.

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.

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.

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.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-021-00897-2.

The prostate health index (PHI) density: Are there advantages over PHI or over the prostate-specific antigen density?

BACKGROUND AND AIMS

Overdiagnosis of prostate cancer (PCa) should be minimized. We wanted to evaluate the diagnostic performance of the prostate health index density (PHID) and compare it with that of the prostate health index (PHI) alone and of the prostate-specific antigen density (PSAD).

MATERIALS AND METHODS

232 men scheduled for a prostate biopsy (prostate-specific antigen level: 2-10 µg/L), were enrolled. PHI, PHID and PSAD were evaluated considering PCa and clinically significant PCa (csPCa) as the outcomes.

RESULTS

For PCa, the area under the curve (AUC) was higher for PHID (0.823) than for PHI (0.779) and PSAD (0.776). For csPCa, the AUC was also higher for PHID (0.851) but closer to that of PSAD (0.819) and PHI (0.813). For equal sensitivities (90%) for PCa, PHID and PSAD offered the highest specificities (37%), missing the same number of cancers (n = 11). Considering csPCa, PHI and PHID had similar specificities. PSAD reached the highest specificity (50.0%), sparing 32.8% of biopsies, while missing 9 cases of csPCa.

CONCLUSIONS

PHID has a better diagnostic performance than PHI for overall PCa detection, but very close to the PSAD performance. Considering csPCa, PHI and PHID perform almost equally, but PSAD has a better diagnostic performance.

Preoperative prostate health index predicts adverse pathology and Gleason score upgrading after radical prostatectomy for prostate cancer

BACKGROUND

We aimed to explore the utility of prostate specific antigen (PSA) isoform [- 2] proPSA and its derivatives for prediction of pathological outcome after radical prostatectomy (RP).

METHODS

Preoperative blood samples were prospectively and consecutivelyanalyzed from 472 patients treated with RP for clinically localized prostate cancerat four medical centers. Measured parameters were PSA, free PSA (fPSA), fPSA/PSA ratio, [- 2] proPSA (p2PSA), p2PSA/fPSA ratio and Prostate Health Index (PHI)(p2PSA/fPSA)*√PSA]. Logistic regression models were fitted to determine the accuracy of markers for prediction of pathological Gleason score (GS) ≥7, Gleason score upgrading, extracapsular extension of the tumor (pT3) and the presence of positive surgical margin (PSM). The accuracy of predictive models was compared using area under the receiver operating curve (AUC).

RESULTS

Of 472 patients undergoing RP, 339 (72%) were found to have pathologic GS ≥ 7, out of them 178 (53%) experienced an upgrade from their preoperative GS = 6. The findings of pT3 and PSM were present in 132 (28%) and 133 (28%) cases, respectively. At univariable analysis of all the preoperative parameters, PHI was the most accurate predictor of pathological GS ≥7 (OR 1.02, 95% CI 1.01-1.03, p<0.001), GS upgrading (OR 1.02, 95% CI 1.01-1.03, p<0.003), pT3 disease (OR 1.01, 95% CI 1.00-1.02, p<0.007) and the presence of PSM (OR 1.01, 95% CI 1.00-1.02, p<0.002). Adding of PHI into the base multivariable model increased significantly the accuracy for prediction of pathological GS by 4.4% to AUC = 66.6 (p = 0.015) and GS upgrading by 5.0% to AUC = 65.9 (p = 0.025), respectively.

CONCLUSIONS

Preoperative PHI levels may contribute significantly to prediction of prostate cancer aggressiveness and expansion of the tumor detected at final pathology.

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

PURPOSES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

Objective

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

Patients and methods

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

Result

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

Conclusion

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

[Use of prostate health index in diagnosing prostate cancer in Chinese men]

Objective: To investigate the value of prostate health index (PHI) in the diagnosis of prostate cancer in patients with total prostate specific antigen (tPSA) <20 μg/L. Methods: Totally 1 135 patients with tPSA<20 μg/L and prostate biopsy indications at Department of Urology, Fudan University Shanghai Cancer Center from March 2013 to April 2016 were enrolled in this study. They were tested for serum tPSA, free prostate specific antigen and prostate specific antigen isoform 2, from which PHI was calculated. Diagnostic efficacy of PHI and tPSA were evaluated using receiver operating characteristic (ROC) curve analysis. The detection rates of prostate cancer were calculated in different ranges of PHI. Subgroup analysis of 716 patients, who were aged 50 or above with tPSA in the range of 4 to 10 μg/L and digital rectal examination negative, was performed. Results: In the biopsied objects with tPSA<20 μg/L, PHI was significantly higher in prostate cancer patients than that in non-cancer patients (48.4(37.4) vs. 26.5(16.9), U=52 674.00, P=0.000), PHI was also significantly higher in high-grade prostate cancer patients than that of low-grade prostate cancer patients (44.5(30.8) vs. 56.4(42.5), U=23 314.00, P=0.000). The area under the curve (AUC) of PHI for diagnosing prostate cancer was significantly higher than that of tPSA (0.771 vs. 0.627, P=0.000). When PHI was in the range of <27, 27 to <36, 36 to <55 and ≥55, the probability of prostate cancer was 9.4% (95%CI: 7.0% to 12.2%), 16.3% (95%CI: 12.2% to 20.8%), 31.0% (95%CI: 25.9% to 37.3%) and 66.4% (95%CI: 58.9% to 74.2%), respectively. Subgroup analysis showed that the AUC of PHI in diagnosing prostate cancer was significantly higher than that of tPSA (0.764 vs. 0.569, P=0.000). When PHI was in the range of <27, 27 to <36, 36 to <55 and ≥55, the probability of prostate cancer was 8.1% (95%CI: 5.4% to 11.3%), 14.0% (95%CI: 9.1% to 19.9%), 30.8% (95%CI: 23.6% to 38.7%) and 78.8% (95%CI: 66.7% to 88.9%), respectively. Conclusion: PHI is superior to tPSA in the diagnosis of prostate cancer in Chinese men with tPSA<20 μg/L.

A Multicentre Evaluation of the Role of the Prostate Health Index (PHI) in Regions with Differing Prevalence of Prostate Cancer: Adjustment of PHI Reference Ranges is Needed for European and Asian Settings

Asians have a lower incidence of prostate cancer (PC). We compared the performance of the Prostate Health Index (PHI) for 2488 men in different ethnic groups (1688 Asian and 800 European men from 9 sites) with PSA 2-20ng/ml and PHI test and transrectal ultrasound-guided biopsy results available. Of these, 1652 men had PSA 2-10ng/ml and a normal digital rectal examination and underwent initial biopsy. The proportions of PC (Gleason ≥6) and higher-grade PC (HGPC, Gleason ≥7) across different PHI ranges were compared. The performance of PSA and PHI was compared using the area under the receiver operating characteristic curve (AUC) and decision curve analyses (DCA). Among Asian men, HGPC would be diagnosed in 1.0%, 1.9%, 13%, and 30% of men using PHI thresholds of <25, 25-35, 35-55, and >55, respectively. At 90% sensitivity for HGPC (PHI >30), 56% of biopsies and 33% of Gleason 6 PC diagnoses could have been avoided. Among European men, HGPC would be diagnosed in 4.1%, 4.3%, 30%, and 34% of men using PHI thresholds of <25, 25-35, 35-55, and >55, respectively. At 90% sensitivity for HGPC (PHI >40), 40% of biopsies and 31% of Gleason 6 PC diagnoses could have been avoided. AUC and DCA confirmed the benefit of PHI over PSA. The benefit of PHI was also seen at repeat biopsy (n=397) and for PSA 10-20ng/ml (n=439). PHI is effective in cancer risk stratification for both European and Asian men. However, population-specific PHI reference ranges should be used. PATIENT SUMMARY: The Prostate Health Index (PHI) blood test helps to identify individuals at higher risk of prostate cancer among Asian and European men, and could significantly reduce unnecessary biopsies and overdiagnosis of prostate cancer. Different PHI reference ranges should be used for different ethnic groups.

Validation of the prostate health index in a predictive model of prostate cancer

OBJECTIVES

To validate and analyse the clinical usefulness of a predictive model of prostate cancer that incorporates the biomarker «[-2] pro prostate-specific antigen» using the prostate health index (PHI) in decision making for performing prostate biopsies.

MATERIAL AND METHODS

We isolated serum from 197 men with an indication for prostate biopsy to determine the total prostate-specific antigen (tPSA), the free PSA fraction (fPSA) and the [-2] proPSA (p2PSA). The PHI was calculated as p2PSA/fPSA×√tPSA. We created 2 predictive models that incorporated clinical variables along with tPSA or PHI. The performance of PHI was assessed with a discriminant analysis using receiver operating characteristic curves, internal calibration and decision curves.

RESULTS

The areas under the curve for the tPSA and PHI models were 0.71 and 0.85, respectively. The PHI model showed a better ability to discriminate and better calibration for predicting prostate cancer but not for predicting a Gleason score in the biopsy ≥7. The decision curves showed a greater net benefit with the PHI model for diagnosing prostate cancer when the probability threshold was 15-35% and greater savings (20%) in the number of biopsies.

CONCLUSIONS

The incorporation of p2PSA through PHI in predictive models of prostate cancer improves the accuracy of the risk stratification and helps in the decision-making process for performing prostate biopsies.

Novel Biomarkers for Prostate Cancer Detection and Prognosis

Prostate cancer (PCa) remains as one of the most controversial issues in health care because of the dilemmas related to screening using Prostate Specific Antigen (PSA). A high number of false positive biopsies and an elevated rate of overdiagnosis are the main problems associated with PSA. New PCa biomarkers have been recently proposed to increase the predictive value of PSA. The published results showed that PCA3 score, Prostate Health Index and 4Kscore can reduce the number of unnecessary biopsies, outperforming better than PSA and the percentage of free PSA. Furthermore, 4Kscore provides with high accuracy an individual risk for high-grade PCa. High values of PHI are also associated with tumor aggressiveness. In contrast, the relationship of PCA3 score with aggressiveness remains controversial, with studies showing opposite conclusions. Finally, the development of molecular biology has opened the study of genes, among them TMPRSS2:ERG fusion gene and miRNAs, in PCa detection and prognosis.

Prostate health index (PHI) and prostate-specific antigen (PSA) predictive models for prostate cancer in the Chinese population and the role of digital rectal examination-estimated prostate volume

PURPOSE

To investigate PSA- and PHI (prostate health index)-based models for prediction of prostate cancer (PCa) and the feasibility of using DRE-estimated prostate volume (DRE-PV) in the models.

METHODS

This study included 569 Chinese men with PSA 4-10 ng/mL and non-suspicious DRE with transrectal ultrasound (TRUS) 10-core prostate biopsies performed between April 2008 and July 2015. DRE-PV was estimated using 3 pre-defined classes: 25, 40, or 60 ml. The performance of PSA-based and PHI-based predictive models including age, DRE-PV, and TRUS prostate volume (TRUS-PV) was analyzed using logistic regression and area under the receiver operating curves (AUC), in both the whole cohort and the screening age group of 55-75.

RESULTS

PCa and high-grade PCa (HGPCa) was diagnosed in 10.9 % (62/569) and 2.8 % (16/569) men, respectively. The performance of DRE-PV-based models was similar to TRUS-PV-based models. In the age group 55-75, the AUCs for PCa of PSA alone, PSA with DRE-PV and age, PHI alone, PHI with DRE-PV and age, and PHI with TRUS-PV and age were 0.54, 0.71, 0.76, 0.78, and 0.78, respectively. The corresponding AUCs for HGPCa were higher (0.60, 0.70, 0.85, 0.83, and 0.83). At 10 and 20 % risk threshold for PCa, 38.4 and 55.4 % biopsies could be avoided in the PHI-based model, respectively.

CONCLUSIONS

PHI had better performance over PSA-based models and could reduce unnecessary biopsies. A DRE-assessed PV can replace TRUS-assessed PV in multivariate prediction models to facilitate clinical use.

Clinical performance of prostate health index in men with tPSA>10ng/ml: Results from a multicentric European study

BACKGROUND

Evidence regarding the diagnostic accuracy of a [-2]proPSA derivative, namely, the prostate health index (PHI), to predict the presence of prostate cancer (PCa) in individuals with high total prostate-specific antigen (tPSA) levels is lacking. We tested the hypothesis that these markers could assist clinicians in the biopsy decision path of patients with tPSA>10ng/ml.

METHODS

The primary endpoint was to evaluate the sensitivity, specificity, and diagnostic accuracy of PHI in determining the presence of PCa at biopsy in comparison to tPSA, free PSA, and % of free to total PSA. We calculated the number of prostate biopsies that could have been spared by using this marker to decide whether or not to perform a biopsy. A secondary endpoint was to determine the relationship between PHI and PCa characteristics.

RESULTS

The PCa was diagnosed in 136 of 262 patients (51.9%). Total PSA and PHI values were significantly higher (P<0.005) and % of free to total PSA values significantly lower (P<0.0001) in patients with PCa relative to those with a negative biopsy. In multivariable logistic regression models, PHI achieved the independent predictor status and significantly increased the accuracy of the base multivariable model by an extent of 8.2% (P = 0.0005). The inclusion of PHI in the biopsy decision path would decrease the number of unnecessary biopsies by an extent of 50.0%, while missing only few cases with clinically significant PCa. Finally, Gleason score was significantly related to PHI levels.

CONCLUSIONS

The results of our study support the diagnostic effectiveness of PHI even in patients with tPSA >10ng/ml. Further validation studies with larger sample size are needed to corroborate our findings.

Prostate health index and prostate cancer gene 3 score but not percent-free Prostate Specific Antigen have a predictive role in differentiating histological prostatitis from PCa and other nonneoplastic lesions (BPH and HG-PIN) at repeat biopsy

OBJECTIVE

To determine if prostate health index (PHI), prostate cancer antigen gene 3 (PCA3) score, and percentage of free prostate-specific antigen (%fPSA) may be used to differentiate asymptomatic acute and chronic prostatitis from prostate cancer (PCa), benign prostatic hyperplasia (BPH), and high-grade prostate intraepithelial neoplasia (HG-PIN) in patients with elevated PSA levels and negative findings on digital rectal examination at repeat biopsy (re-Bx).

PATIENTS AND METHODS

In this prospective study, 252 patients were enrolled, undergoing PHI, PCA3 score, and %fPSA assessments before re-Bx. We used 3 multivariate logistic regression models to test the PHI, PCA3 score, and %fPSA as risk factors for prostatitis vs. PCa, vs. BPH, and vs. HG-PIN. All the analyses were performed for the whole patient cohort and for the "gray zone" of PSA (4-10ng/ml) cohort (171 individuals).

RESULTS

Of the 252 patients, 43 (17.1%) had diagnosis of PCa. The median PHI was significantly different between men with a negative biopsy and those with a positive biopsy (34.9 vs. 48.1, P<0.001), as for the PCA3 score (24 vs. 54, P<0.001) and %fPSA (11.8% vs. 15.8%, P = 0.012). The net benefit of using PCA3 and PHI to differentiate prostatitis and PCa was moderate, although it extended to a good range of threshold probabilities (40%-100%), whereas that from using %fPSA was negligible: this pattern was reported for the whole population as for the "gray zone" PSA cohort.

CONCLUSION

In front of a good diagnostic performance of all the 3 biomarkers in distinguishing negative biopsy vs. positive biopsy, the clinical benefit of using the PCA3 score and PHI to estimate prostatitis vs. PCa was comparable. PHI was the only determinant for prostatitis vs. BPH, whereas no biomarkers could differentiate prostate inflammation from HG-PIN.

Prostate Specific Antigen as a Tumor Marker in Prostate Cancer: Biochemical and Clinical Aspects

In this chapter the use of prostate specific antigen (PSA) as a tumor marker for prostate cancer is discussed. The chapter provides an overview of biological and clinical aspects of PSA. The main drawback of total PSA (tPSA) is its lack of specificity for prostate cancer which leads to unnecessary biopsies. Moreover, PSA-testing poses a risk of overdiagnosis and subsequent overtreatment. Many PSA-based markers have been developed to improve the performance characteristics of tPSA. As well as different molecular subforms of tPSA, such as proPSA (pPSA) and free PSA (fPSA), and PSA derived kinetics as PSA-velocity (PSAV) and PSA-doubling time (PSADT). The prostate health index (phi), PSA-density (PSAD) and the contribution of non PSA-based markers such as the urinary transcripts of PCA3 and TMPRSS-ERG fusion are also discussed. To enable further risk stratification tumor markers are often combined with clinical data (e.g. outcome of DRE) in so-called nomograms. Currently the role of magnetic resonance imaging (MRI) in the detection and staging of prostate cancer is being explored.

Clinical use of [-2]proPSA (p2PSA) and its derivatives (%p2PSA and Prostate Health Index) for the detection of prostate cancer: a review of the literature

Prostate-specific antigen (PSA) is recognized as an organ-specific marker with low specificity and sensitivity in discriminating prostate cancer (PCa) from other benign conditions, such as prostatic hyperplasia or chronic prostatitis. Thus, in the case of clinical suspicion, a PCa diagnosis cannot be made without a prostate biopsy. [-2]proPSA (p2PSA), a precursor of PSA, has been investigated as a new marker to accurately detect PCa. The aim of this systematic review was to discuss the available literature regarding the clinical validity and utility of p2PSA and its derivatives, p2PSA/fPSA (%p2PSA) and the Prostate Health Index (PHI). A systematic search of the PubMed and Scopus electronic databases was performed in accordance with the PRISMA statement (http://www.prisma-statement.org), considering the time period from January 1990 to January 2014 and using the following search terms: proprostate specific antigen, proenzyme PSA, proPSA, [-2]proPSA, p2PSA, Prostate Health Index, and PHI. To date, 115 studies have been published, but only 35 were considered for the qualitative analysis. These studies suggested that p2PSA is the most cancer-specific form of PSA, being preferentially expressed in PCa tissue and being significantly elevated in the serum of men with PCa. It is now evident that p2PSA, %p2PSA, and PHI measurements improve the specificity of the available tests (PSA and derivatives) in detecting PCa. Moreover, increasing PHI values seem to correlate with more aggressive disease. Some studies have compared p2PSA and its derivatives with other new biomarkers and found p2PSA to be significantly more accurate. Indeed, the implementation of these tests in clinical practice has the potential to significantly increase the physician's ability to detect PCa and avoid unnecessary biopsies, while also having an effective impact on costs. Further studies in large, multicenter, prospective trials are required to confirm these encouraging results on the clinical utility of these new biomarkers.

The influence of prostate volume in prostate health index performance in patients with total PSA lower than 10 μg/L

Prostate health index (phi), a measure calculated as p2PSA/fPSA × √tPSA, has shown valuable results in the detection of prostate cancer (PCa), improving the prediction of the aggressiveness of the tumor. The aim of our study was to test whether prostate volume influences phi performance using univariate and multivariate models. 220 patients with PSA<10 μg/L (102 with negative biopsy and 118 with PCa) were included in the study. Serum concentrations of tPSA, fPSA and p2PSA were measured on Access2 analyzer. The higher accuracy was found for phi, obtaining an AUC of 0.748. Bigger AUCs were obtained for phi, %p2PSA, %fPSA and tPSA in patients with small prostate volume (≤35 cc); meanwhile, the lowest AUCs were found in patients with large prostate volume (>50 cc). Including phi and %p2PSA in a multivariable analysis based on patient age, prostate volume, tPSA, and %fPSA accuracy increased from 0.762 to 0.802 (logistic regression model) or 0.815 (artificial neural network). Accuracy excluding prostate volume in these models was 0.762 and 0.775, respectively. The inclusion of phi and %p2PSA in a multivariate model identifies better men with PCa. Prostate volume remains a key factor in the interpretation of biomarkers used to detect PCa.

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa)

PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of (~)50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective.

Prostate-specific antigen and other serum and urine markers in prostate cancer

Prostate-specific antigen (PSA) is one of the most widely used tumor markers, and strongly correlates with the risk of harboring from prostate cancer (PCa). This risk is visible already several years in advance but PSA has severe limitations for PCa detection with its low specificity and low negative predictive value. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved Prostate Health Index (phi) shows improved specificity over percent free and total PSA. Other serum kallikreins or sarcosine in serum or urine show more diverging data. In urine, the FDA-approved prostate cancer gene 3 (PCA3) has also proven its utility in the detection and management of early PCa. However, some aspects on its correlation with aggressiveness and the low sensitivity at very high values have to be re-examined. The detection of a fusion of the androgen regulated TMPRSS2 gene with the ERG oncogene (from the ETS family), which acts as transcription factor gene, in tissue of ~50% of all PCa patients was one milestone in PCa research. When combining the urinary assays for TMPRSS2:ERG and PCA3, an improved accuracy for PCa detection is visible. PCA3 and phi as the best available PCa biomarkers show an equal performance in direct comparisons.