Prostate-specific Antigen Parameters and Prostate Health Index Enhance Prostate Cancer Prediction With the In-bore 3-T Magnetic Resonance Imaging-guided Transrectal Targeted Prostate Biopsy After Negative 12-Core Biopsy

Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

Prostate cancer: Novel genetic and immunologic biomarkers

Prostate cancer (PCa) is considered one of the most prevalent male malignancies worldwide with a global burden estimated to increase over the next two decades. Due to significant mortality and debilitation of survival, early diagnosis has been described as key. Unfortunately, current diagnostic serum-based strategies have low specificity and sensitivity. Histologic examination is invasive and not useful for treatment and monitoring purposes. Hence, a plethora of studies have been conducted to identify and validate an efficient noninvasive approach in the diagnosis, staging, and prognosis of PCa. These investigations may be categorized as genetic (non-coding biomarkers and gene markers), immunologic (immune cells, interleukins, cytokines, antibodies, and auto-antibodies), and heterogenous (PSA-related markers, PHI-related indices, and urinary biomarkers) subgroups. This review examines current approaches and potential strategies using biomarker panels in PCa.

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.

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.

Construction and Comparison of Different Models in Detecting Prostate Cancer and Clinically Significant Prostate Cancer

Background

With the widespread adoption of prostatic-specific antigen (PSA) screening, the detection rates of prostate cancer (PCa) have increased. Due to the low specificity and high false-positive rate of serum PSA levels, it was difficult to diagnose PCa accurately. To improve the diagnosis of PCa and clinically significant prostate cancer (CSPCa), we established novel models on the basis of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) in the Asian population.

Methods

We retrospectively collected the clinical indicators of patients with TPSA at 4–20 ng/ml. Furthermore, mpMRI was performed using a 3.0-T scanner and reported in the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS). Univariable and multivariable logistic analyses were performed to construct the models. The performance of different models based on PSA derivatives, PHI derivatives, PI-RADS, and a combination of PHI derivatives and PI-RADS was evaluated.

Results

Among the 128 patients, 47 (36.72%) patients were diagnosed with CSPCa and 81 (63.28%) patients were diagnosed with non-CSPCa. Of the 81 (63.28%) patients, 8 (6.25%) patients were diagnosed with Gleason Grade 1 PCa and 73 (57.03%) patients were diagnosed with non-PCa. In the analysis of the receiver operator characteristic (ROC) curves in TPSA 4–20 ng/ml, the multivariable model for PCa was significantly larger than that for the model based on the PI-RADS (p = 0.004) and that for the model based on the PHI derivatives (p = 0.031) in diagnostic accuracy. The multivariable model for CSPCa was significantly larger than that for the model based on the PI-RADS (p = 0.003) and was non-significantly larger than that for the model based on the PHI derivatives (p = 0.061) in diagnostic accuracy. For PCa in TPSA 4–20 ng/ml, a multivariable model achieved the optimal diagnostic value at four levels of predictive variables. For CSPCa in TPSA 4–20 ng/ml, the multivariable model achieved the optimal diagnostic value at a sensitivity close to 90% and 80%.

Conclusions

The models combining PHI derivatives and PI-RADS performed better in detecting PCa and CSPCa than the models based on either PHI or PI-RADS.

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.

Value of PHI and PHID in the detection of intermediate- and high-risk prostate cancer

BACKGROUND AND AIMS

PSA testing practice results in a large number of unnecessary prostate biopsies and the overdiagnosis of clinically insignificant prostate cancer (PCa). The aim of our study was to evaluate the value of PHI and PHID for the detection of PCa.

MATERIALS AND METHODS

We measured tPSA, fPSA and p2PSA in 455 patients scheduled for biopsy, including 243 patients with PCa. D'Amico criteria were used to classify these patients in three groups related to risk of progression. Intermediate- and high-risk PCa were considered as aggressive PCa.

RESULTS

The best area under the curve (AUC) value obtained in the detection of aggressive PCa was achieved for PHI and PHID (0.766 and 0.760, respectively). We found a relationship of the performance of by these tests with the calculated prostate volume or the estimated prostate size by digital rectal exam, obtaining the higher AUC in patients with a small prostate. Thus, the AUC for PHI was 0,843 for patients with small calculated prostate volume and 0,817 for patients with small estimated prostate size.

CONCLUSIONS

Our results underline that PHI and PHID outperforms the efficacy obtained with tPSA and %fPSA. Substantial differences in their value in relation to prostate volume were found.

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.

Diagnostic accuracy of [-2]proPSA versus Gleason score and Prostate Health Index versus Gleason score for the determination of aggressive prostate cancer: a systematic review

OBJECTIVE

The objective of this review was to determine the diagnostic accuracy of [-2]proPSA (p2PSA) and the Prostate Health Index compared to the Gleason score in determining the aggressiveness of prostate cancer.

INTRODUCTION

Prostate cancer is the most commonly diagnosed cancer in men. However, the utility of currently available biomarkers for determining the aggressive form of the disease remains unknown. This review sought to determine the diagnostic accuracy of two new biomarkers in determining the aggressive form of prostate cancer.

INCLUSION CRITERIA

Diagnostic accuracy studies that enrolled men of any age and any prostate specific antigen (PSA) level with histologically confirmed prostate cancer in which Prostate Health Index and p2PSA were assessed in comparison to Gleason score for the determination of aggressive prostate cancer were considered for inclusion. There was no time limitation on study inclusion.

METHODS

A three-step search strategy was utilized to identify both published and unpublished studies in the English language in the following sources: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Web of Science, Google Scholar, MedNar, and SIGLE. Databases were searched from inception to January 2019. Study selection, critical appraisal, data extraction, and data synthesis were done according to the approach recommended by JBI.

RESULTS

A total of 12 studies (n = 8462) that recruited men with aggressive prostate cancer were considered in this review. The majority of included subjects had a total PSA level of 2 to 10ng/mL. The sensitivity of the Prostate Health Index ranged from 67% to 97% while specificity ranged from 6% to 64%. At a Prostate Health Index threshold of 25 and below (three studies, n = 3222), pooled sensitivity was 97% (95% confidence interval [CI], 95% to 98%) and specificity was 10% (95% CI, 6% to 16%). At a Prostate Health Index threshold of between 26 and 35 (six studies, n = 6030), pooled sensitivity was 87% (95% CI, 8% to 91%) and specificity was 45% (95% CI, 39% to 50%). At a Prostate Health Index threshold of 36 and above (five studies, n = 1476), pooled sensitivity was 72% (95% CI, 64% to 79%) and specificity was 74% (95% CI, 68% to 80%). Only one study assessed p2PSA. Sensitivity ranged from 80% to 95%, and specificity ranged from 9.9% to 27.9% with increasing threshold values from 7.9 to 10.9ng/mL.

CONCLUSIONS

Overall, both Prostate Health Index and p2PSA have acceptable accuracy for the determination of the likelihood of aggressive prostate cancer. However, the inverse relationship between sensitivity and specificity makes it difficult to determine an optimum cut-off value for positivity. Further research is warranted to determine their utility in the management of prostate cancer.

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.

Positive Predictive Value of Prostate Imaging Reporting and Data System Version 2 for the Detection of Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The variability of the positive predictive value (PPV) represents a significant factor affecting the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI).

OBJECTIVE

To analyze published studies reporting mpMRI PPV and the reasons behind the variability of clinically significant prostate cancer (csPCa) detection rates on targeted biopsies (TBx) according to Prostate Imaging Reporting and Data System (PI-RADS) version 2 categories.

EVIDENCE ACQUISITION

A search of PubMed, Cochrane library's Central, EMBASE, MEDLINE, and Scopus databases, from January 2015 to June 2020, was conducted. The primary and secondary outcomes were to evaluate the PPV of PI-RADS version 2 in detecting csPCa and any prostate cancer (PCa), respectively. Individual authors' definitions for csPCa and PI-RADS thresholds for positive mpMRI were accepted. Detection rates, used as a surrogate of PPV, were pooled using random-effect models. Preplanned subgroup analyses tested PPV after stratification for PI-RADS scores, previous biopsy status, TBx technique, and number of sampled cores. PPV variation over cancer prevalence was evaluated.

EVIDENCE SYNTHESIS

Fifty-six studies, with a total of 16 537 participants, were included in the quantitative synthesis. The PPV of suspicious mpMRI for csPCa was 40% (95% confidence interval 36-43%), with large heterogeneity between studies (I² 94%, p < 0.01). PPV increased according to PCa prevalence. In subgroup analyses, PPVs for csPCa were 13%, 40%, and 69% for, respectively, PI-RADS 3, 4, and 5 (p < 0.001). TBx missed 6%, 6%, and 5% of csPCa in PI-RADS 3, 4, and 5 lesions, respectively. In biopsy-naïve and prior negative biopsy groups, PPVs for csPCa were 42% and 32%, respectively (p = 0.005). Study design, TBx technique, and number of sampled cores did not affect PPV.

CONCLUSIONS

Our meta-analysis underlines that the PPV of mpMRI is strongly dependent on the disease prevalence, and that the main factors affecting PPV are PI-RADS version 2 scores and prior biopsy status. A substantially low PPV for PI-RADS 3 lesions was reported, while it was still suboptimal in PI-RADS 4 and 5 lesions. Lastly, even if the added value of a systematic biopsy for csPCa is relatively low, this rate can improve patient risk assessment and staging.

PATIENT SUMMARY

Targeted biopsy of Prostate Imaging Reporting and Data System 3 lesions should be considered carefully in light of additional individual risk assessment corroborating the presence of clinically significant prostate cancer. On the contrary, the positive predictive value of highly suspicious lesions is not high enough to omit systematic prostate sampling.

Comparing Prostate Imaging-Reporting and Data System Version 2 (PI-RADSv2) Category 1 and 2 Groups: Clinical Implication of Negative Multiparametric Magnetic Resonance Imaging

Objectives

To evaluate the clinicopathological differences between Prostate Imaging-Reporting and Data System (PI-RADS) version 2 (v2) category 1 and 2 groups. Materials and Methods. We retrospectively reviewed our two institutional clinical databases: (1) transrectal ultrasound (TRUS)/magnetic resonance imaging (MRI) fusion biopsy cohort (n = 706) and (2) radical prostatectomy (RP) cohort (n = 1403). Subsequently, we performed comparative analyses between PI-RADSv2 category 1 and 2 groups. Clinically significant prostate cancer (csPCa) was defined as the presence of Gleason score (GS) ≥ 3 + 4 in a single biopsy core, and adverse pathology (AP) was defined as high-grade (primary Gleason pattern 4 or any pattern 5) and/or non-organ-confined disease (pT3/N1). We also performed multivariate logistic regression analyses for AP.

Results

In the TRUS/MRI fusion biopsy cohort, no significant differences in detection rates of all cancer (18.2% vs. 29.0%, respectively, P = 0.730) or csPCa (9.1% vs. 9.9%, respectively, P = 0.692) were observed between PI-RADSv2 category 1 and 2 groups. There were no significant differences in pathologic outcomes including Gleason score (≥4 + 3, 21.2% vs. 29.9%, respectively, P = 0.420) or detection rate of AP (27.3% vs. 33.8%, respectively, P = 0.561) between the two groups in the RP cohort either. PI-RADSv2 category 1 or 2 had no significant association with AP, even in univariate analysis (P = 0.299).

Conclusions

PI-RADSv2 categories 1 and 2 had similar performance to predict clinicopathological outcomes. Consequently, these two categories may be unified into a single category. Negative mpMRI does not guarantee the absence of AP, as with csPCa.

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.

The effect of 5 alpha-reductase inhibitor therapy on prostate cancer detection in the era of multi-parametric magnetic resonance imaging

We aimed to evaluate the effect of 5 alpha-reductase inhibitor (5-ARI) treatment on prostate cancer (PCa) and clinically significant PCa (csPCa) detection in patients undergoing transrectal ultrasound (TRUS)/magnetic resonance imaging (MRI) fusion biopsy in the current era of multi-parametric MRI (mpMRI). We retrospectively reviewed our TRUS/MRI fusion biopsy database (n = 706). Eighty (11.3%) patients who had used 5-ARI for more than one year at the time of biopsy were stratified as 5-ARI group. Subsequently, we performed comparative analyses of 5-ARI and non-5-ARI groups. csPCa was defined by a Gleason score ≥3 + 4 in a single biopsy core. Chi-squared test was used to evaluate the performance of mpMRI in predicting PCa/csPCa between the two groups. Multivariate logistic regression analyses were performed to evaluate the significant variables associated with PCa detection. There were no significant differences in PCa/csPCa detection rates between 5-ARI and non-5-ARI groups (all, P > 0.05). In multivariate logistic regression analyses for the evaluation of variables associated with csPCa detection, age (odds ratio [OR], 1.062; 95% confidence interval [CI], 1.035–1.090; P < 0.001), pre-biopsy PSA (OR, 1.062; 95% CI, 1.034–1.090; P < 0.001), prostate volume on TRUS (OR, 0.956; 95% CI, 0.943–0.970, P < 0.001), and PI-RADsV2 category (OR, 5.528; 95% CI, 3.017–10.131; P < 0.001) were found to be significant predictors. However, 5-ARI had no significant association with PCa detection (P = 0.384). Conclusively, 5-ARI therapy did not adversely affect PCa/csPCa detection after TRUS/MRI fusion biopsy, which suggests that exposure to 5-ARI may not impair the performance of mpMRI.

How Many Cores Does Systematic Prostate Biopsy Need?: A Large-Sample Retrospective Analysis

OBJECTIVES

To explore the best individualized systematic prostate biopsy method.

METHODS

We retrospectively analyzed the clinical data of 1211 patients who underwent 12-core systematic prostate biopsy guided by transrectal ultrasound from January 2011 to March 2018. Other biopsy core methods (6-, 8-, and 10-core) were estimated from the 12-core biopsy that was performed. Differences in the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) were compared.

RESULTS

A total of 498 cases of PCa (41.1%) were detected, and 423 cases (34.9%) were csPCa. There was no significant difference between the 12- and 10-core prostate biopsy strategies in the total detection rates of PCa and csPCa (P > .05). In the subgroup of patients with a maximal prostate cross-sectional area of less than 15 cm² , there was a significant difference between the 12-core method and the standard 6-core method (P = .03) but no significant differences between the other methods in the detection rate of PCa (P > .05), but in the detection rate of csPCa, the 12-core method differed significantly from the other methods (P = .02-.04) except for the 10-core method (P > .05). In patients with a prostate-specific antigen concentration of 20 ng/mL or higher, there were no significant differences between the 12-core method and all of the other methods (P > 0.05). In patients younger than 70 years and 70 years or older, the 12-core method differed significantly from the other methods (P < .01-.03) except for the 10-core method (P > .05).

CONCLUSIONS

Ten- or 12-core biopsy showed a higher detection rate than the other schemes. However, for patients with a prostate-specific antigen concentration of 20 ng/mL or higher, the 6-core systematic biopsy is preferred.

The Utility of Prostate Specific Antigen Density, Prostate Health Index, and Prostate Health Index Density in Predicting Positive Prostate Biopsy Outcome is Dependent on the Prostate Biopsy Methods

OBJECTIVE

To evaluate prognostic markers, prostate-specific antigen, prostate health index (PHI), and prostate volume indexed measures (prostate-specific antigen density and prostate health index density) for predicting positive prostate cancer biopsies in magnetic resonance (MR) transrectal ultrasound fused versus nonfused transrectal ultrasonography biopsy.

METHODS

A retrospective cohort of 211 patients that had at least 1 suspected MR lesion, Prostate Imaging-Reporting and Data System ≥3, and subsequent biopsy (2015-2017). Clinical characteristics and prognostic biomarkers were evaluated as predictors of prostate cancer detection by type of biopsy guidance (fused vs nonfused).

RESULTS

One-hundred twenty-one patients had nonfused and 90 had fused biopsies. PHI and PHID had greater area under the receiver operating characteristics curve (AUC) in predicting positive biopsies than prostate-specific antigen or PSAD for both nonfused and fused biopsy. PHI 0.78 (95% CI 0.67-0.88) and PHID 0.82 (95% CI 0.73-0.91) had the greatest AUC for predicting biopsy results for nonfused and fused biopsies, respectively. Multiple-variable models did not improve model fit compared to single variables. Based on Youden's index, a cut-off value of 45.9 for PHI in nonfused and 0.64 for PHID in fused biopsies would reduce the number of negative biopsies by 77.3% and 63.4%, respectively, but the percentage of missed clinically significant cancer biopsies would be 19% and 12%, respectively.

CONCLUSION

Our findings demonstrate that the choice of prognostic biomarkers for predicting positive biopsies is a function of the biopsy guidance method. Volume indexed derivatives appear to have greater value when a MRI-US fused method is used.

A narrative review and update on management following negative prostate biopsy

PURPOSE OF REVIEW

Prostate cancer has traditionally been diagnosed using systematic transrectal ultrasound-guided biopsy. However, given the inherent nature of sampling, a negative biopsy does not exclude clinically significant prostate cancer (csPCa), and continued controversy exists in the optimal management following initial biopsy. Numerous avenues for evaluation include multiparametric MRI (mpMRI), use of molecular biomarkers, repeat biopsy, and observation.

RECENT FINDINGS

mpMRI has shown promise in guiding further biopsy management: for individuals with identified target lesions, increased accuracy and detection using combination targeted and systematic sampling has been repeatedly demonstrated in the literature as an effective strategy. For those with negative MRIs and/or negative biomarker (blood, urinary, tissue) studies, increasing evidence has suggested that these individuals may be able to avoid biopsy altogether, albeit at a small risk of missing csPCa. Observation should be based on an individual's risk of csPCa versus their competing health risks, and saturation biopsy reserved for rare cases with high clinical suspicion.

SUMMARY

Management following an initial negative prostate biopsy requires careful discussion with the patient, their risk tolerance, and threshold for intervention. Although subject to availability, mpMRI and molecular biomarkers may better risk stratify patients, identify target lesions, and in certain cases, spare biopsy altogether.