Negative Biopsy Histology in Men With PI-RADS Score 5 in Daily Clinical Practice: Incidence of Granulomatous Prostatitis

IntroductionThe purpose of this study was to evaluate the biopsy histology of men who underwent transperineal multi-parametric magnetic resonance imaging (mpMRI)/transrectal ultrasound fusion biopsy for Prostate Imaging Reporting and Data System (PI-RADS) score 5 lesions.Patients and MethodsFrom January 2016 to June 2019, 105 men with PI-RADS score 5 underwent mpMRI/transrectal ultrasound fusion biopsy combined with systematic prostate biopsy. All the patients underwent a 3.0 Tesla pelvic mpMRI for the first time before prostate biopsy. In detail, the detection rate for clinically significant prostate cancer (PCa) and the follow-up of the patients without proven diagnosis of PCa has been reported.ResultsIn 91 (86.7%) of 105 patients, a stage T1c PCa was diagnosed, and 89 (84.5%) of 105 of them were classified as clinically significant PCa. Among the 16 (15.5%) of 105 patients with absence of cancer, 5 (31.5%) of 16 had an aspecific granulomatous prostatitis, 1 (6.2%) of 16 had a specific granulomatous prostatitis secondary to prostatic Mycobacterium Tubercolosis, and 10 (62.3%) of 16 had a diagnosis of normal parenchyma. The 6 patients with granulomatous prostatitis underwent specific antibiotic therapy followed by laboratory (ie, semen and urine cultures) and clinical evaluation. Six months from prostate biopsy, none of the 16 patients underwent repeat prostate biopsy because prostate-specific antigen (PSA) (15/16 cases) plus PSA density significantly decreased; in addition, in all the cases the initial PI-RADS score 5 was downgraded at mpMRI revaluation to PI-RADS score ≤ 3.ConclusionThe reduction of PSA plus PSA density values and the downgrading of PI-RADS score to ≤ 3 allow avoiding a repeated prostate biopsy in men with initial mpMRI PI-RADS score 5 lesion and negative biopsy histology.     

Rotterdam mobile phone app including MRI data for the prediction of prostate cancer: A multicenter external validation

ObjectivesThe Rotterdam Prostate Cancer Risk calculator (RPCRC) has been validated in the past years. Recently a new version including multiparametric magnetic resonance imaging (mpMRI) data has been released. The aim of our study was to analyze the performance of the mpMRI RPCRC app.MethodsA series of men undergoing prostate biopsies were enrolled in eleven Italian centers. Indications for prostate biopsy included: abnormal Prostate specific antigen levels (PSA>4 ng/ml), abnormal DRE and abnormal mpMRI. Patients’ characteristics were recorded. Prostate cancer (PCa) risk and high-grade PCa risk were assessed using the RPCRC app. The performance of the mpMRI RPCRC in the prediction of cancer and high-grade PCa was evaluated using receiver operator characteristics, calibration plots and decision curve analysis.ResultsOverall, 580 patients were enrolled: 404/580 (70%) presented PCa and out of them 224/404 (55%) presented high-grade PCa. In the prediction of cancer, the RC presented good discrimination (AUC = 0.74), poor calibration (p = 0.01) and a clinical net benefit in the range of probabilities between 50 and 90% for the prediction of PCa (Fig. 1). In the prediction of high-grade PCa, the RC presented good discrimination (AUC = 0.79), good calibration (p = 0.48) and a clinical net benefit in the range of probabilities between 20 and 80% (Fig. 1).ConclusionsThe Rotterdam prostate cancer risk App accurately predicts the risk of PCa and particularly high-grade cancer. The clinical net benefit is wide for high-grade cancer and therefore its implementation in clinical practice should be encouraged. Further studies should assess its definitive role in clinical practice.     

Cutoff Values of Prostate Imaging Reporting and Data System Version 2.1 Score in Men With Prostate-specific Antigen Level 4 to 10 ng/mL: Importance of Lesion Location

IntroductionMultiparametric magnetic resonance imaging (mpMRI) has been shown to have a good performance in predicting cancer among patients with a prostate-specific antigen (PSA) level of 4 to 10 ng/mL. However, lesion location on mpMRI has never been separately considered.Patients and MethodsPatients with PSA level of 4 to 10 ng/mL were prospectively enrolled and underwent transrectal ultrasound-guided prostate biopsy. Patient information was collected, and logistic regression analysis was performed to determine the predictive factors of clinically significant prostate cancer (csPCa). Patients were grouped by lesion location to determine the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 cutoff value in predicting csPCa.ResultsAmong 222 patients, 121 were diagnosed with PCa and 92 had csPCa. Age, prostate volume, PSA density, location (peripheral zone, csPCa only), and PI-RADS v2.1 score were correlated with PCa and csPCa, and PI-RADS v2.1 score was the best predictor. A PI-RADS v2.1 score of 4 was the best cutoff value for predicting csPCa in patients with lesions only in the transitional zone with respect to the Youden index (0.5896) and negative predictive value (93.10%) with acceptable sensitivity (81.82%) and specificity (77.14%). An adjustment of the cutoff value to 3 for lesions in the peripheral zone would increase the negative predictive value (92.00%) and decrease the false negative rate (2.90%) with an acceptable sensitivity (97.10%) and specificity (30.67%).ConclusionPI-RADS v2.1 score is an effective predictor of csPCa in patients with PSA levels of 4 to 10 ng/mL. Patients with transitional zone or peripheral zone lesions should undergo biopsy if the PI-RADS v2.1 score is ≥ 4 or ≥ 3, respectively.     

The Use of Multiparametric Magnetic Resonance Imaging for Follow-up of Patients Included in Active Surveillance Protocol. Can PSA Density Discriminate Patients at Different Risk of Reclassification?

IntroductionThe objective of this study was to test Prostate Imaging Reporting and Data System (PI-RADS) classification on multiparametric magnetic resonance imaging (mpMRI) and MRI-derived prostate-specific antigen density (PSAD) in predicting the risk of reclassification in men in active surveillance (AS), who underwent confirmatory or per-protocol follow-up biopsy.Materials and MethodsThree hundred eighty-nine patients in AS underwent mpMRI before confirmatory or follow-up biopsy. Patients with negative (−) mpMRI underwent systematic random biopsy. Patients with positive (+) mpMRI underwent targeted fusion prostate biopsies + systematic random biopsies. Different PSAD cutoff values were tested (< 0.10, 0.10-0.20, ≥ 0.20). Multivariable analyses assessed the risk of reclassification, defined as clinically significant prostate cancer of grade group 2 or more, during follow-up according to PSAD, after adjusting for covariates.ResultsOne hundred twenty-seven (32.6%) patients had mpMRI(−); 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. The rate of reclassification to grade group 2 PCa was 16%, 22%, 31%, and 39% for mpMRI(−) and PI-RADS 3, 4, and 5, respectively, in case of PSAD < 0.10 ng/mL²; 16%, 25%, 36%, and 44%, in case of PSAD 0.10 to 0.19 ng/mL²; and 25%, 42%, 55%, and 67% in case of PSAD ≥ 0.20 ng/mL². PSAD ≥ 0.20 ng/mL² (odds ratio [OR], 2.45; P = .007), PI-RADS 3 (OR, 2.47; P = .013), PI-RADS 4 (OR, 2.94; P < .001), and PI-RADS 5 (OR, 3.41; P = .004) were associated with a higher risk of reclassification.ConclusionPSAD ≥ 0.20 ng/mL² may improve predictive accuracy of mpMRI results for reclassification of patients in AS, whereas PSAD < 0.10 ng/mL² may help selection of patients at lower risk of harboring clinically significant prostate cancer. However, the risk of reclassification is not negligible at any PSAD cutoff value, also in the case of mpMRI(−).     

Which Prostate Biopsy in Men Enrolled in Active Surveillance? Experience in 110 Men Submitted to Scheduled Three-Years Transperineal Saturation Biopsy Combined With Fusion Targeted Cores

IntroductionThe reclassification rate for clinically significant prostate cancer (csPCa) has been evaluated in men enrolled in active surveillance (AS) protocol who previously underwent confirmatory biopsy.Materials and MethodsFrom May 2013 to September 2017, 110 patients (median age 63 years) with very low risk PCa underwent 3-years scheduled prostate biopsy performing repeated transperineal saturation biopsy (SPBx); in addition, the mpMRI lesions characterized by Prostate Imaging Reporting and Data System (PI-RADS) version 2 scores ≥ 3 were submitted to additional mpMRI/TRUS fusion biopsies (4 cores). The reclassification rate for csPCa (over 3 or more than 10% of positive cores, ISUP Grade Group/GG ≥ 2, greatest percentage of cancer > 50%) has been evaluated.ResultsSix (5.4%) patients with PI-RADS score 3 (4 men) vs. 4 (2 men) were reclassified based on upgraded (GG2); SPBx and MRI/TRUS fusion biopsy diagnosed 100% and 0% of csPCa, respectively. Of the remaining 104 (94.5%) patients, 75 (72.2%) were found to have very low-risk PCa and in 29 (27.8%) cancer was absent (normal parenchyma).ConclusionSPBx combined with mpMRI at confirmatory and repeated evaluation allow to reduce the reclassification rate during AS follow up (5.4% of the cases at 3 years from diagnosis).     

Cognitive versus Software-Assisted Registration: Development of a New Nomogram Predicting Prostate Cancer at MRI-Targeted Biopsies

Introduction

Multiparametric magnetic resonance imaging (mpMRI) is gaining acceptance to guide targeted biopsy (TB) in prostate cancer (PC) diagnosis. We aimed to compare the detection rate of software-assisted fusion TB (SA-TB) versus cognitive fusion TB (COG-TB) for PC and to evaluate potential clinical features in detecting PC and clinically significant PC (csPC) at TB.

Editorial comments

Ninety-nine of 105 consecutive men who underwent transrectal prostatic ultrasound (TRUS) at Highland Park Hospital had the results correlated with digital rectal examination (DRE), serum prostate specific antigen (PSA), and biopsy results. Ninety-six cases had evaluable ultrasound studies. Thirty-two of the 99 who underwent biopsy had primary carcinoma of the prostate. Prostate volume, predicted PSA, a ratio of observed/predicted PSA, and Gleason score were examined. There was no correlation between age and prostate volume, volume and the presence of carcinoma, or PSA and Gleason score. Thirty-one point six percent of the abnormal DREs, 36.6% of the abnormal TRUSs, and 40.6% of the elevated PSAs occurred in men with prostatic carcinoma (PCa). If PSA was normal (less than or equal to 4.0 ng/ml) and either DRE or TRUS was abnormal, then the risk of carcinoma was 2.9%. If PSA was elevated, regardless of the other two tests, the risk of finding PCa was at least 38%. If all three tests were abnormal, the risk of carcinoma was 38% in our series and 68% in a meta-analysis. Many men with PSA values between 4 and 10 ng/ml have benign biopsies. However, close future follow-up with consideration of repeat biopsy should be strongly considered. © 1994 Wiley-Liss, Inc.     

Fourteen-Core Systematic Biopsy That Includes Two Anterior Cores in Men With PI-RADS Lesion ≥ 3 is Comparable With Magnetic Resonance Imaging-ultrasound Fusion Biopsy in Detecting Clinically Significant Prostate Cancer: A Single-institution Experience

IntroductionMagnetic resonance imaging (MRI)-ultrasound fusion targeted prostate biopsy (FB) has been advocated by many experts as a replacement for the standard template biopsy. Herein, we compared pathology results and cancer detection rates of FB with our standard 14-core systematic prostate biopsy (SB) that includes 2 anterior cores.Materials and MethodsOne hundred two men with elevated prostate-specific antigen and suspicious lesions on multiparametric MRI, Prostate Imaging Reporting And Data System (PI-RADS) v2 score ≥ 3, underwent FB. Each target lesion was biopsied 3 times; our SB was performed concurrently. Biopsy results were compared for overall and clinically significant (cs), defined as Gleason score ≥ 7, cancer detection.ResultsFifty-two percent of patients had positive biopsy results, and of those, 44 had cs prostate cancer (PCa). The overall detection rates for FB and SB were 39% and 50%, respectively, and there was no statistical difference in the detection rate of csPCa detection rate (P = .42). Of 17 patients diagnosed with a high-risk PCa, defined as Gleason score ≥ 8, SB identified 15, whereas FB identified 10. Within the SB group, 21 had positive anterior core biopsies, of which 11 were cs.ConclusionExpanding the standard template prostate biopsies to include 2 anterior horn sampling may be just as effective as FB in men with PI-RADS lesion ≥ 3, thereby mitigating the increased cost associated with FB.     

PCA3 and TMPRSS2-ERG gene fusions as diagnostic biomarkers for prostate cancer

The incidence of prostate cancer (PCa) is rising steadily among males in many countries. Serum prostate-specific antigen (PSA) is widely applied to clinical diagnosis and screening of PCa. However, the so-called grey area of PSA levels 4.0–10.0 ng/mL has a low specificity of 25–40% resulting in a high rate of negative biopsy and overtreatment. So in order to treat PCa patients in early stage, there is an urgent need for new biomarkers in PCa diagnosis. The PCA3 gene, a non-coding RNA (ncRNA) that is highly expressed in prostate cancer (PCa) cells, has been identified as a molecular biomarkers to detect PCa, of which PCA3 has already under clinical application. PCA3 is strongly overexpressed in malignant prostate tissue compared to benign or normal adjacent one. Newly, PCA3 is considered to be a promising biomarker in clinical diagnosis and targeted therapy. The diagnostic significance of PCA3, however, is awaiting further researches. Moreover, it has been demonstrated recently that TMPRSS2-ERG gene fusion is identified as the predominant genetic change in patients diagnosed with PCa. Recent study revealed that combination of the PCA3 and TMPRSS2-ERG gene fusion test optimizes PCa detection compared with that of single biomarker, which would lead to a considerable reduction of the number of prostate biopsies. In this review, we focused on the potential use of PCA3 and TMPRSS2-ERG gene fusion detection in the diagnosis of PCa.     

Comparison of Cancer Detection Rates Between TRUS-Guided Biopsy and MRI-Targeted Biopsy According to PSA Level in Biopsy-Naive Patients: A Propensity Score Matching Analysis

Background

The purpose of the study was to compare cancer detection rates between 12-core transrectal ultrasound-guided prostate biopsy (TRUS-Bx) and multiparametric magnetic resonance imaging (mpMRI)-guided target prostate biopsy (MRI-TBx) according to prostate-specific antigen (PSA) level in biopsy-naive patients.

Natural History of Patients with Prostate MRI Likert 1-3 and Development of RosCaP: a Multivariate Risk Score for Clinically Significant Cancer

IntroductionClinically significant prostate cancer (csCaP) with Gleason ≥3 + 4 is found in 10% negative prebiopsy multiparametric (mp) MRI cases and varies widely for equivocal mpMRI cases. The objective of this study was to investigate long-term outcomes of patients with negative and equivocal mpMRIs and to develop a predictive score for csCaP risk stratification in this group.Patients and MethodsPatients who underwent an upfront mpMRI between May 2015 and March 2018 with an MRI score Likert 1 to 3 were included in the study. Patients had either a CaP diagnosis at MRI-targeted biopsy or were not diagnosed and attended follow-up in the community. Outcomes were analysed through the Kaplan-Meier estimator and Cox Model. Regression coefficients of significant variables were used to develop a Risk of significant Cancer of the Prostate score (RosCaP).ResultsAt first assessment 281/469 patients had mpMRI only and 188/469 mpMRI and biopsy, 26 csCaP were found at biopsy, including 10/26 in Likert 3 patients. 12/371 patients discharged without CaP after first assessment were diagnosed with csCaP during a median of 34.2 months’ follow-up, 11/12 diagnosis occurred in patients omitting initial biopsy. csCaP diagnosis-free survival was 95.7% in the MRI group and 99.1% in the biopsy group. From these outcomes, a continuous RosCaP score was developed: RosCaP = 0.083 x Age - 0.202 x (1/PSA Density) + 0.786 (if Likert 3), and 4 risk classes were proposed. Limitations include retrospective design and absence of external validation.ConclusionAge, PSA Density and MRI Likert score were significantly associated to the risk of csCaP and utilised to devise the novel RosCap predictive score focused to support risk assessment in patients with negative or equivocal mpMRI results.     

智能融合成像技术对中低风险前列腺特异性抗原人群的临床显著性前列腺癌诊断研究

目的:探讨核磁联合经直肠超声计算机软件融合成像引导前列腺靶向穿刺活检(software guided magnetic resonance imag?ing-ultrasound fusion targeted biopsies,MRUS-TB)在中低风险前列腺特异性抗原(prostate-specific antig...     

A Combinatorial Neural Network Analysis Reveals a Synergistic Behaviour of Multiparametric Magnetic Resonance and Prostate Health Index in the Identification of Clinically Significant Prostate Cancer

BackgroundThe widespread use of prostate specific antigen (PSA) caused high rate of overdiagnosis. Overdiagnosis leads to unnecessary definitive treatments of prostate cancer (PCa) with detrimental side effects, such as erectile dysfunction and incontinence. The aim of this study was to evaluate the feasibility of an artificial neural network-based approach to develop a combinatorial model including prostate health index (PHI) and multiparametric magnetic resonance (mpMRI) to recognize clinically significant PCa at initial diagnosis.MethodsTo this aim we prospectively enrolled 177 PCa patients who underwent radical prostatectomy and had received PHI tests and mpMRI before surgery. We used artificial neural network to develop models that can identify aggressive PCa efficiently. The model receives as an input PHI plus PI-RADS score.ResultsThe output of the model is an estimate of the presence of a low or high Gleason score. After training on a dataset of 135 samples and optimization of the variables, the model achieved values of sensitivity as high as 80% and 68% specificity.ConclusionsOur preliminary study suggests that combining mpMRI and PHI may help to better estimate the risk category of PCa at initial diagnosis, allowing a personalized treatment approach. The efficiency of the method can be improved even further by training the model on larger datasets.     

Multiparametric Magnetic Resonance Imaging Second Opinion May Reduce the Number of Unnecessary Prostate Biopsies: Time to Improve Radiologists’ Training Program?

Purpose

To understand the multiparametric magnetic resonance imaging (mpMRI) interreader agreement between radiologists of peripheral and academic centers and the possibility to avoid prostate biopsies according to magnetic resonance imaging second opinion.

Clinical value of minimum apparent diffusion coefficient for prediction of clinically significant prostate cancer in the transition zone

Background

This study investigated the association between apparent diffusion coefficients in Prostate Imaging Reporting and Data System 4/5 lesions and clinically significant prostate cancer in the transition zone.

Methods

We included 102 patients who underwent transperineal cognitive fusion targeted biopsy for Prostate Imaging Reporting and Data System 4/5 lesions in the transition zone between 2016 and 2020. The association between apparent diffusion coefficients and prostate cancers in the transition zone was analyzed.

Results

The detection rate of prostate cancer was 49% (50/102), including clinically significant prostate cancer in 37.3% (38/102) of patients. The minimum apparent diffusion coefficients in patients with clinically significant prostate cancer were 494.5 ± 133.6 µm²/s, which was significantly lower than 653.8 ± 172.5 µm²/s in patients with benign histology or clinically insignificant prostate cancer. Age, prostate volume, transition zone volume, and mean and minimum apparent diffusion coefficients were associated with clinically significant prostate cancer. Multivariate analysis demonstrated that only the minimum apparent diffusion coefficient value (odds ratio: 0.994; p < 0.001) was an independent predictor of clinically significant prostate cancer. When the cutoff value of the minimum apparent diffusion coefficient was less than 595 µm²/s, indicating the presence of prostate cancer in the transition zone, the detection rate increased to 59.2% (29/49) in this cohort.

Conclusion

The minimum apparent diffusion coefficient provided additional value to indicate the presence of clinically significant prostate cancer in the transition zone. It may help consider the need for subsequent biopsies in patients with Prostate Imaging Reporting and Data System 4/5 lesions and an initial negative targeted biopsy.

     

Utility of Multiparametric Magnetic Resonance Imaging With PI-RADS,Version 2, in Patients With Prostate Cancer Eligible for Active Surveillance: Which Radiologic Characteristics Can Predict Unfavorable Disease?

BackgroundWe investigated the utility of multiparametric magnetic resonance imaging (mpMRI) using Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), scoring in patients with prostate cancer eligible for active surveillance (AS).Materials and MethodsThe medical records of the patients who had undergone mpMRI before radical prostatectomy from 2014 to 2018 were reviewed. All the patients had met the Prostate Cancer Research International AS criteria. PI-RADSv2 scores were assigned to 12 prostate regions. Unfavorable disease was stratified using the American Joint Committee on Cancer (AJCC) prognostic scale as stage IIB (Gleason score [GS], 3+4 and pathologic stage T2) and IIC-III (GS, ≥ 4+3 or pathologic stage T3).ResultsOf 376 eligible patients, 184 (48.9%), 129 (34.3%), and 63 (16.8%) had AJCC stage I, IIB, and IIC-III disease, respectively. The patients with IIC-III disease were older and had a higher prostate-specific antigen density than those with stage I or IIB disease. PI-RADS 5 lesions were more frequent in patients with stage IIC-III than in patients with stage I or IIB disease. Multivariable analysis revealed that ≥ 2 lesions with a PI-RADS 5 score was an independent predictor for unfavorable disease (hazard ratio [HR], 3.612; P < .001 for IIB; HR, 6.562; P < .001 for IIC-III), and PI-RADS score of ≥ 4 was limited for predicting AJCC stage IIB disease (HR, 2.387; P = .01).ConclusionmpMRI with PI-RADSv2 showed high negative predictive value for patients with prostate cancer eligible for AS. Multiple PI-RADS 4-5 lesions were associated with unfavorable disease compared with solitary lesions. Multiple PI-RADS 5 lesions were strongly associated with GS ≥ 4+3 or pathologic T3 disease. Targeted biopsy or radical treatment should be considered for these patients.     

The risk of prostate cancer for men on aspirin,statin or antidiabetic medications

BackgroundA decreased risk of prostate cancer (PCa) has been suggested in men taking aspirin, statins and metformin, although the evidence has been conflicting. We estimated the association between prescribed medications, prostate specific antigen (PSA) levels and the risk of either any PCa or high-grade PCa.MethodsThis population-based cohort study included 185,667 men having a first recorded PSA test and 18,574 men having a first prostate biopsy in Stockholm County, Sweden for the period 2007–2012. Detailed clinical information including PSA levels, biopsy results, comorbidities and educational level were obtained from population-based registers. High-grade prostate cancer was defined as a Gleason score of seven or higher. Differences in PSA levels by medication status were estimated using linear regression on log PSA values. PCa risk was estimated using multivariate logistic regression.ResultsCompared with men who were not on medication, the PSA level at the first PSA test was lower among men using 75 mg/dose aspirin (−3.9% change in PSA concentration; 95% confidence interval (CI): −5.8 to −2.1), statin (−4.6%; 95% CI: −6.2 to −2.9), metformin (−14%; 95% CI: −17 to −12) and insulin (−16%; 95% CI: −18 to −14). Men using any statins had an increased risk of both high-grade PCa (odds ratio (OR) 1.25; 95% CI: 1.10–1.42) and PCa of any grade (OR 1.16; 95% CI 1.04–1.29). There were no significant associations between aspirin or any antidiabetic medication and the risk of PCa.ConclusionWe found no protective effect of aspirin, statins or antidiabetics in terms of risk for any PCa or high-grade PCa. Use of any statins was associated with an elevated risk of being diagnosed with high-grade prostate cancer.     

Can We Improve the Preoperative Prediction of Prostate Cancer Recurrence With Multiparametric MRI?

IntroductionThe use of multiparametric magnetic resonance imaging (mpMRI) to assess prostate cancer (PCa) has increased over the past decade. We aimed to assess if preoperative mpMRI lesion score, a variable routinely available for men undergoing pre-biopsy MRI, improves the performance of commonly used preoperative predictive models for PCa recurrence.Patients and MethodsWe analyzed data from 372 patients with PCa treated with radical prostatectomy in 2012 to 2017 and assessed with pre-biopsy mpMRI within 6 months prior to surgery. Suspicious areas for cancer were scored on a standardized 5-point scale. Cox regression was used to assess the association between mpMRI score and the risk of postoperative biochemical recurrence. Two different models were tested accounting for factors included in the Kattan nomogram and in the D’Amico risk-classification.ResultsOverall, 53% and 30% of patients were found with a lesion scored 4 or 5 at pre-biopsy mpMRI, respectively. Risk varied widely by mpMRI (29% 2-year risk of biochemical recurrence for a score of 5 vs. 5% for a score of 1-2), and mpMRI score was associated with large hazard ratios after adjusting for stage, grade, and prostate-specific antigen: 1.66, 1.96, and 2.71 for scores 3, 4, and 5, respectively. However, 95% confidence intervals were very wide (0.19-14.20, 0.26-14.65, and 0.36-20.55, respectively) and included 1.ConclusionsOur data did not show that preoperative models, commonly used to assess PCa risk, were improved after including the pre-biopsy mpMRI score. However, the value of pre-biopsy mpMRI to improve preoperative risk models should be investigated in larger data sets.     

Application of Urinary Volatile Organic Compounds (VOCs) for the Diagnosis of Prostate Cancer

BackgroundProstate cancer (PCa) screening using serum prostate-specific antigen (PSA) testing has caused unnecessary biopsies and overdiagnosis owing to its low accuracy and reliability. Therefore, there is an increased interest in identifying better PCa biomarkers. Studies showed that trained dogs can discriminate patients with PCa from unaffected men by sniffing urine. We hypothesized that urinary volatile organic compounds (VOCs) may be the source of that odor and could be used to develop urinary VOC PCa diagnosis models.Patients and MethodsUrine samples from 55 and 53 biopsy proven PCa-positive and -negative patients respectively were initially obtained for diagnostic model development. Urinary metabolites were analyzed by gas chromatography-mass spectrometry. A PCa diagnosis model was developed and validated using innovative statistical machine-learning techniques. A second set of samples (53 PCa-positive and 22 PCa-negative patients) were used to evaluate the previously developed PCa diagnosis model.ResultsThe analysis resulted in 254 and 282 VOCs for their significant association (P < .05) with either PCa-positive or -negative samples respectively. Regularized logistic regression analysis and the Firth method were then applied to predict PCa prevalence, resulting in a final model that contains 11 VOCs. Under cross-validation, the area under the receiver operating characteristic curve (AUC) for the final model was 0.92 (sensitivity, 0.96; specificity, 0.80). Further evaluation of the developed model using a testing cohort yielded an AUC of 0.86. As a comparison, the PSA-based diagnosis model only rendered an AUC of 0.54.ConclusionThe study describes the development of a urinary VOC-based model for PCa detection.