Prostate Cancer Risk Stratification Research Articles

Performance of a validated urine exosome gene expression test (EPI) in men within the USPSTF suggested age-group of 55 to 69 years at initial biopsy with a PSA 2-10 ng/mL.

53 Background: Prostate-specific antigen (PSA) plays a key-role in prostate cancer (PCa) risk stratification but leads to over-diagnosis of low grade PCa. Recently, the USPSTF recommended that the decision to undergo PSA-based screening for men aged 55 to 69 years should be an individual one. We have developed and validated a non-invasive diagnostic test (ExoDx Prostate(IntelliScore), EPI) as a decision aid to guide the initial prostate biopsy decision process for men in the PSA gray zone of 2-10 ng/mL. The EPI test is a urine exosome gene expression assay to discriminate high-grade (GG 2) from low-grade (GG 1) and benign disease, thereby reducing the number of unnecessary biopsies. Methods: Patient data from two clinical trials were merged and constrained by age (55-69) according to the USPSTF suggested age-group resulting in a cohort of 701 patients with PSA 2-10 ng/mL, scheduled for initial prostate needle biopsy. EPI test results as well as PCPT2.0 risk calculator, ERSPC risk calculator and PSA results are compared with biopsy outcomes. Performances are reported using the area under the receiver operating characteristic curve (AUC), Negative predictive value (NPV), Positive predictive value (PPV), Sensitivity, and Specificity for discriminating ≥GG2 from GG1 and benign disease. Results: EPI showed a superior AUC of 0.70 compared to PSA (AUC: 0.57), PCPT2.0 (AUC: 0.60) and ERSPC (AUC: 0.58) (all p-values < 0.001) for discriminating ≥GG2 PCa from benign and GG1. The previously validated EPI cut-point of 15.6 would avoid 22% of all prostate biopsies and 29% of unnecessary biopsies, with an NPV of 93% and miss only 5.4% of ≥GG2, respectively. Conclusions: EPI is a non-invasive, easy to use urine exosome RNA expression assay to discriminate high-grade (GG2) from low-grade (GG1) PCa and benign disease. EPI significantly outperformed the other standard of care parameters tested and applying the EPI test for risk stratification of patients in the USPSTF suggested age group, should reduce the number of unnecessary biopsies.

Predictive value of 68Ga-PSMA PET/CT for high-risk prostate cancer

Objective To investigate the value of 68Ga-prostate specific membrane antigen (PSMA)-617 PET/CT in predicting high-risk prostate cancer. Methods From May 2016 to January 2017, 30 patients (median age 67 years) with biopsy-proven prostate cancer were included. The 68Ga-PSMA-617 PET/CT images and clinical data of all patients were analyzed retrospectively. According to prostate cancer risk stratification criteria of National Comprehensive Cancer Network (NCCN) Guidelines (including Gleason scores, prostate specific antigen (PSA)), all patients were classified into low-moderate-risk group and high-risk group. PET images were analyzed semi-quantitatively and maximum standardized uptake value (SUVmax) of primary prostate cancer was measured. SUVmax of 68Ga-PSMA-617 PET/CT was used to establish logistic regression model for predicting high-risk prostate cancer, and the diagnostic efficiency of the model was evaluated by receiver operating characteristic (ROC) curve analysis. Results The median Gleason score of 30 patients was 7.5 (7, 9), and the median PSA was 34.0 (19.4, 119.1) μg/L, including 9 patients with PSA≤20 μg/L and 21 patients with PSA>20 μg/L. According to the NCCN Guidelines, there were 24 patients with high-risk prostate cancer and 6 patients with low-moderate-risk prostate cancer. SUVmax was higher in high-risk group than that in low-moderate-risk group (14.2(11.4, 23.1) vs 7.9(3.8, 13.1); u=118, P<0.05). Logistic regression model established with SUVmax could effectively predict high-risk prostate cancer with the area under ROC curve of 0.819. When the cut-off value was set as 0.73, the sensitivity and specificity of the model were 87.5%(21/24) and 4/6 respectively. Conclusion SUVmax of 68Ga-PSMA-617 PET/CT can be used as an imaging biomarker for predicting high-risk prostate cancer. Key words: Prostatic neoplasms; Prostate-specific membrane antigen; Isotope labeling; Gallium radioisotopes; Positron-emission tomography; Tomography, X-ray computed

Objective risk stratification of prostate cancer using machine learning and radiomics applied to multiparametric magnetic resonance images

Multiparametric magnetic resonance imaging (mpMRI) has become increasingly important for the clinical assessment of prostate cancer (PCa), but its interpretation is generally variable due to its relatively subjective nature. Radiomics and classification methods have shown potential for improving the accuracy and objectivity of mpMRI-based PCa assessment. However, these studies are limited to a small number of classification methods, evaluation using the AUC score only, and a non-rigorous assessment of all possible combinations of radiomics and classification methods. This paper presents a systematic and rigorous framework comprised of classification, cross-validation and statistical analyses that was developed to identify the best performing classifier for PCa risk stratification based on mpMRI-derived radiomic features derived from a sizeable cohort. This classifier performed well in an independent validation set, including performing better than PI-RADS v2 in some aspects, indicating the value of objectively interpreting mpMRI images using radiomics and classification methods for PCa risk assessment.

Creating a potential diagnostic for prostate cancer risk stratification (InformMDx™) by translating novel scientific discoveries concerning cAMP degrading phosphodiesterase-4D7 (PDE4D7).

Increased PSA-based screening for prostate cancer has resulted in a growing number of diagnosed cases. However, around half of these are 'indolent', neither metastasizing nor leading to disease specific death. Treating non-progressing tumours with invasive therapies is currently regarded as unnecessary over-treatment with patients being considered for conservative regimens, such as active surveillance (AS). However, this raises both compliance and protocol issues. Great clinical benefit could accrue from a biomarker able to predict long-term patient outcome accurately at the time of biopsy and initial diagnosis. Here we delineate the translation of a laboratory discovery through to the precision development of a clinically validated, novel prognostic biomarker assay (InformMDx™). This centres on determining transcript levels for phosphodiesterase-4D7 (PDE4D7), an enzyme that breaks down cyclic AMP, a signalling molecule intimately connected with proliferation and androgen receptor function. Quantifiable detection of PDE4D7 mRNA transcripts informs on the longitudinal outcome of post-surgical disease progression. The risk of post-surgical progression increases steeply for patients with very low 'PDE4D7 scores', while risk decreases markedly for those patients with very high 'PDE4D7 scores'. Combining clinical risk variables, such as the Gleason or CAPRA (Cancer of the Prostate Risk Assessment) score, with the 'PDE4D7 score' further enhances the prognostic power of this personalized, precision assessment. Thus the 'PDE4D7 score' has the potential to define, more effectively, appropriate medical intervention/AS strategies for individual prostate cancer patients.

Preparation and Evaluation of ZD2 Peptide 64Cu-DOTA Conjugate as a Positron Emission Tomography Probe for Detection and Characterization of Prostate Cancer.

Positron emission tomography (PET) is a sensitive modality for cancer molecular imaging. We aim to develop a PET probe for sensitive detection and risk stratification of prostate cancer by targeting an abundant microenvironment oncoprotein, extradomain-B fibronectin (EDB-FN). The probe consists of a small ZD2 peptide specific to EDB-FN and a 64Cu-DOTA chelate. The probe was synthesized using standard solid-phase peptide chemistry and chelated to 64Cu prior to imaging. PET images were acquired at 4 and 22 h after intravenously injecting a 200 μCi probe into mice bearing human PC3 and LNCaP tumors, which represent highly aggressive and slow-growing prostate tumors, respectively. At 4 and 22 h postinjection, tumors could be clearly identified in the PET images. A significant higher signal was observed in PC3 tumors than in LNCaP tumors at 22 h (p = 0.01). Probe accumulation was also higher in PC3 tumors at 24 h. These data demonstrated that PET molecular imaging of EDB-FN in the tumor microenvironment of prostate cancer allows efficient differentiation of PC3 and LNCaP tumors in vivo. The ZD2 peptide-targeted PET probe shows potential in the detection and characterization of high-risk prostate cancer to improve the clinical management of prostate cancer.

The SmartTarget Biopsy Trial: A Prospective, Within-person Randomised, Blinded Trial Comparing the Accuracy of Visual-registration and Magnetic Resonance Imaging/Ultrasound Image-fusion Targeted Biopsies for Prostate Cancer Risk Stratification

BackgroundMultiparametric magnetic resonance imaging (mpMRI)-targeted prostate biopsies can improve detection of clinically significant prostate cancer and decrease the overdetection of insignificant cancers. It is unknown whether visual-registration targeting is sufficient or augmentation with image-fusion software is needed. ObjectiveTo assess concordance between the two methods. Design, setting, and participantsWe conducted a blinded, within-person randomised, paired validating clinical trial. From 2014 to 2016, 141 men who had undergone a prior (positive or negative) transrectal ultrasound biopsy and had a discrete lesion on mpMRI (score 3–5) requiring targeted transperineal biopsy were enrolled at a UK academic hospital; 129 underwent both biopsy strategies and completed the study. InterventionThe order of performing biopsies using visual registration and a computer-assisted MRI/ultrasound image-fusion system (SmartTarget) on each patient was randomised. The equipment was reset between biopsy strategies to mitigate incorporation bias. Outcome measurements and statistical analysisThe proportion of clinically significant prostate cancer (primary outcome: Gleason pattern ≥3+4=7, maximum cancer core length ≥4mm; secondary outcome: Gleason pattern ≥4+3=7, maximum cancer core length ≥6mm) detected by each method was compared using McNemar's test of paired proportions. Results and limitationsThe two strategies combined detected 93 clinically significant prostate cancers (72% of the cohort). Each strategy detected 80/93 (86%) of these cancers; each strategy identified 13 cases missed by the other. Three patients experienced adverse events related to biopsy (urinary retention, urinary tract infection, nausea, and vomiting). No difference in urinary symptoms, erectile function, or quality of life between baseline and follow-up (median 10.5 wk) was observed. The key limitations were lack of parallel-group randomisation and a limit on the number of targeted cores. ConclusionsVisual-registration and image-fusion targeting strategies combined had the highest detection rate for clinically significant cancers. Targeted prostate biopsy should be performed using both strategies together. Patient summaryWe compared two prostate cancer biopsy strategies: visual registration and image fusion. A combination of the two strategies found the most clinically important cancers and should be used together whenever targeted biopsy is being performed.

Development and Validation of a Multiparameterized Artificial Neural Network for Prostate Cancer Risk Prediction and Stratification.

To develop and validate a multiparameterized artificial neural network (ANN) on the basis of personal health information for prostate cancer risk prediction and stratification. The 1997 to 2015 National Health Interview Survey adult survey data were used to train and validate a multiparameterized ANN, with parameters including age, body mass index, diabetes status, smoking status, emphysema, asthma, race, ethnicity, hypertension, heart disease, exercise habits, and history of stroke. We developed a training set of patients ≥ 45 years of age with a first primary prostate cancer diagnosed within 4 years of the survey. After training, the sensitivity and specificity were obtained as functions of the cutoff values of the continuous output of the ANN. We also evaluated the ANN with the 2016 data set for cancer risk stratification. We identified 1,672 patients with prostate cancer and 100,033 respondents without cancer in the 1997 to 2015 data sets. The training set had a sensitivity of 21.5% (95% CI, 19.2% to 23.9%), specificity of 91% (95% CI, 90.8% to 91.2%), area under the curve of 0.73 (95% CI, 0.71 to 0.75), and positive predictive value of 28.5% (95% CI, 25.5% to 31.5%). The validation set had a sensitivity of 23.2% (95% CI, 19.5% to 26.9%), specificity of 89.4% (95% CI, 89% to 89.7%), area under the curve of 0.72 (95% CI, 0.70 to 0.75), and positive predictive value of 26.5% (95% CI, 22.4% to 30.6%). For the 2016 data set, the ANN classified all 13,031 patients into low-, medium-, and high-risk subgroups and identified 5% of the cancer population as high risk. A multiparameterized ANN that is based on personal health information could be used for prostate cancer risk prediction with high specificity and low sensitivity. The ANN can further stratify the population into three subgroups that may be helpful in refining prescreening estimates of cancer risk.

Imaging as a Personalized Biomarker for Prostate Cancer Risk Stratification.

Biomarkers provide objective data to guide clinicians in disease management. Prostate-specific antigen serves as a biomarker for screening of prostate cancer but has come under scrutiny for detection of clinically indolent disease. Multiple imaging techniques demonstrate promising results for diagnosing, staging, and determining definitive management of prostate cancer. One such modality, multiparametric magnetic resonance imaging (mpMRI), detects more clinically significant disease while missing lower volume and clinically insignificant disease. It also provides valuable information regarding tumor characteristics such as location and extraprostatic extension to guide surgical planning. Information from mpMRI may also help patients avoid unnecessary biopsies in the future. It can also be incorporated into targeted biopsies as well as following patients on active surveillance. Other novel techniques have also been developed to detect metastatic disease with advantages over traditional computer tomography and magnetic resonance imaging, which primarily rely on defined size criteria. These new techniques take advantage of underlying biological changes in prostate cancer tissue to identify metastatic disease. The purpose of this review is to present literature on imaging as a personalized biomarker for prostate cancer risk stratification.

Prospective Inclusion of Apparent Diffusion Coefficients in Multiparametric Prostate MRI Structured Reports: Discrimination of Clinically Insignificant and Significant Cancers.

The purpose of this study was to assess the diagnostic performance of prospectively assigned mean apparent diffusion coefficient (ADC) values in multiparametric MRI (mpMRI) structured reports for discriminating clinically insignificant (International Society of Urological Pathology [ISUP] group 1) from clinically significant (ISUP groups 2-5) prostate cancer. This single-center study included men with abnormal 3-T mpMRI findings (Prostate Imaging Reporting and Data System version 2 score, ≥ 3) who subsequently underwent radical prostatectomy or targeted biopsy with positive results. One of nine radiologists prospectively reported the mean ADC for each lesion during clinical interpretation. Lesions with ADC ≤ 0.700 mm2/s × 10-3 were flagged as concerning for clinically significant prostate cancer. The index lesion at MRI correlated with the site-concordant lesion at targeted biopsy or whole-mount histopathologic analysis. Logistic regression was used to evaluate the utility of mean ADC values for discriminating ISUP grade group 1 from groups 2-5. Diagnostic performance was assessed by ROC AUC. Among the 218 eligible men, those with ISUP group 2-5 lesions had lower mean ADC values than those with ISUP 1 lesions; overall, 0.598 vs 0.803 mm/s2 × 10-3 (p < 0.0001); peripheral zone (PZ), 0.597 vs 0.855 mm/s2 × 10-3 (p < 0.0001); transition zone (TZ), 0.600 vs 0.660 mm/s2 × 10-3 (p = 0.035). The AUC for the PZ was 0.91 and for the TZ was 0.70. The optimal ADC cutoff values were 0.682 mm/s2 × 10-3 for PZ lesions and 0.638 mm2/s × 10-3 for TZ lesions, resulting in sensitivity and specificity of 78% and 94% for the PZ and 72% and 67% for the TZ. ADC values estimated prospectively in a clinical setting can help differentiate clinically insignificant from clinically significant prostate cancer, facilitating prebiopsy and pretreatment risk stratification.

Comparison of the Prognostic Utility of the Cell Cycle Progression Score for Predicting Clinical Outcomes in African American and Non-African American Men with Localized Prostate Cancer

BackgroundBetter prostate cancer risk stratification is necessary to inform medical management, especially for African American (AA) men, for whom outcomes are particularly uncertain. ObjectiveTo evaluate the utility of both a cell cycle progression (CCP) score and a clinical cell-cycle risk (CCR) score to predict clinical outcomes in a large cohort of men with prostate cancer highly enriched in an AA patient population. Design, setting, and participantsPatients were diagnosed with clinically localized adenocarcinoma of the prostate and treated at The Ochsner Clinic (New Orleans, LA, USA) from January 2006 to December 2011. CCP scores were derived from archival formalin-fixed, paraffin-embedded biopsy tissue. CCR scores were calculated as the combination of molecular (CCP score) and clinical (Cancer of the Prostate Risk Assessment [CAPRA] score) components. InterventionActive treatment (radical prostatectomy, radiation therapy alone, or radiation and hormone therapy) or watchful waiting. Outcome measurements and statistical analysisThe primary outcome was progression to metastatic disease. Association with outcomes was evaluated via Cox proportional hazards survival analysis and likelihood ratio tests. Results and limitationsThe final cohort included 767 men, of whom 281 (36.6%) were AA. After accounting for ancestry, treatment, and CAPRA in multivariable analysis, the CCP score remained a significant predictor of metastatic disease (hazard ratio [HR] 2.04; p<0.001), and there was no interaction with ancestry (p=0.20) or treatment (p=0.09). The CCR score was highly prognostic (HR 3.86; p<0.001), and as with the CCP score, there was no interaction with ancestry (p=0.24) or treatment (p=0.32). Limitations include the retrospective study design and the use of self-reported ancestry information. ConclusionsA CCR score provided significant prognostic information regardless of ancestry. The findings demonstrate that AA men in this study cohort appear to have similar prostate cancer outcomes to non-AA patients after accounting for all available molecular and clinicopathologic variables. Patient summaryIn this study we evaluated the ability of a combined molecular and clinical score to predict the progression of localized prostate cancer. We found that the combined molecular and clinical score predicted progression to metastasis regardless of patient ancestry or treatment. This suggests that the combined molecular and clinical score may be a valuable tool for determining the risk of metastasis in men with newly diagnosed prostate cancer in order to make appropriate treatment decisions.

Prospective Evaluation of a Digital RNA Circulating Tumor Cell Signature in Localized Prostate Cancer

Prostate biopsies are an essential part of risk stratification for localized prostate cancer, but are associated with undergrading and understaging. A digital RNA expression signature of circulating tumor cells (CTCs) in the blood has been shown to predict for subclinical dissemination of prostate cancer identified at the time of radical prostatectomy. Thus, analysis of molecular CTC signatures may improve the accuracy of risk stratification prior to radiation therapy and may predict response to therapy. Here, we evaluated a CTC molecular signature in prostate cancer patients receiving external beam radiation therapy (EBRT) in the context of a prospective clinical trial and assessed for correlations with baseline clinicopathologic features. Patients enrolled in a prospective randomized clinical trial comparing proton beam therapy (PBT) and intensity modulated radiation therapy (IMRT) were consented to an optional companion CTC biomarker study. Eligible patients had a diagnosis of low or intermediate risk prostate cancer and were planned for treatment with EBRT (either PBT or IMRT) without concurrent hormonal therapy. 65 patients donated 20 mL blood prior to initiation of EBRT, and a subset of patients donated blood during the last week of EBRT and 3 months after completion of EBRT. CTCs were isolated using a negative selection microfluidic device, and quantitation of CTC RNA expression was performed for a panel of 8 prostate-lineage genes using a highly sensitive multiplex droplet digital PCR assay. Using previously trained algorithms for digital RNA CTC signatures in localized prostate cancer, a CTC-L score was calculated for each time point. Pre-treatment CTC-L scores were compared to baseline clinicopathologic characteristics. Longitudinal trends in CTC-L scores were assessed in a subset of patients. Molecular CTC analyses were performed prospectively in 65 prostate cancer patients enrolled in a randomized clinical trial comparing PBT and IMRT. 28 patients (43%) had low risk and 37 (57%) had intermediate risk disease. Baseline CTC-L scores were not significantly correlated with clinical T-stage or Gleason score, but patients with a pre-treatment PSA ≥10 ng/mL had a significantly higher CTC-L score compared to those with a PSA <10 ng/mL (P=0.01). Among intermediate risk patients, 3/37 (8%) had a CTC-L score above a threshold previously associated with increased risk for microscopic dissemination beyond the prostate; 0/28 low risk patients scored above this threshold. Out of 31 patients with longitudinal data available, 61% exhibited a decreased or stable CTC-L score upon completion of EBRT, while 39% exhibited an increase in CTC-L score at the end of therapy. Analysis of a digital RNA CTC signature in the blood may improve the accuracy of risk stratification in localized prostate cancer. Long-term follow up is necessary to determine whether molecular CTC signatures correlate with clinical outcomes after radiation therapy.

Elevated Serum Cytokines and Trichomonas vaginalis Serology at Diagnosis Are Not Associated With Higher Gleason Grade or Lethal Prostate Cancer.

Inflammation and infections have been associated with prostate cancer progression. We assessed whether elevated serum cytokines or T. vaginalis seropositivity at the time of diagnosis was associated with higher grade or lethal prostate cancer. Men with localized or metastatic prostate cancer were included in this study. Cytokine serum levels including interleukin (IL)-1α, IL-1β, IL-2, IL-6, IL-8, monocyte chemotactic protein 1 (CCL-2), tumor necrosis factor α, and growth-regulated oncogene α (CXCL-1) using a multiplex enzyme-linked immunosorbent assay and T.vaginalis serology were measured in blood samples at diagnosis. Atotal of 324 patients were identified at time of localized disease and 118 at time of metastatic disease. Of the 189 patients with localized disease and clinical follow-up data (median, 73 months), 28 developed lethal disease. There was no association between circulating cytokine levels above median concentrations nor T.vaginalis seropositivity and risk of intermediate- to high-risk or lethal prostate cancer. Higher levels of serum cytokine levels and T.vaginalis seropositivity at diagnosis are not associated with high-grade or lethal prostate cancer and do not aid risk stratification of localized prostate cancer.

Initial risk stratification and staging in prostate cancer with prostatic-specific membrane antigen positron emission tomography/computed tomography: A first-stop-shop

Current imaging for prostate cancer (PCa) had limitations for risk stratification and staging. Magnetic resonance imaging frequently underestimated lymph node metastasis while bone scintigraphy often had diagnostic dilemmas. Prostatic-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET/CT) has been remarkable in PCa recurrence. Ninety-seven PSMA PET-CT scans were reanalyzed for tumor node metastases staging and risk stratification of lymph node and distant metastasis proportion. Histopathology of 23/97 patients was available as gold standard. Chi-square test was used for proportion comparison. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), overestimation, underestimation, and correct estimation of T and N stages were calculated. Kappa coefficient (κ) was derived for inter-rater agreement. Lymph node or distant metastasis detection on PSMA PET/CT increased significantly with increase in risk category. PSMA PET/CT sensitivity, specificity, PPV, and NPV for extraprostatic extension, seminal vesicle invasion, and lymph node metastases were 63.16%, 100%, 100%, 36.36%; 55%, 100%, 100%, 25%; and 65.62%, 99.31%, 87.50%, and 97.53%, respectively. Kappa coefficient showed substantial agreement between PSMA PET/CT and histopathological lymph node metastases (κ = 0.734); however, it was just in fair agreement (κ = 0.277) with T stage. PSMA PET/CT overestimated, underestimated, and correct estimated T and N stages in 8.71%, 39.13%, 52.17% and 8.71%, 4.35%, and 86.96% cases, respectively. PSMA PET/CT has potential for initial risk stratification with reasonable correct N stage estimation, however underestimates T stage. Hence, we concluded that PSMA PET/CT should be used as “ first-stop-shop” for staging and initial risk stratification of PCa with regional magnetic resonance imaging in surgically resectable cases.

Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning.

The risk stratification of prostate cancer and breast cancer tumours from patients relies on histopathology, selective genomic testing, or on other methods employing fixed formalin tissue samples. However, static biomarker measurements from bulk fixed-tissue samples provide limited accuracy and actionability. Here, we report the development of a live-primary-cell phenotypic-biomarker assay with single-cell resolution, and its validation with prostate cancer and breast cancer tissue samples for the prediction of post-surgical adverse pathology. The assay includes a collagen-I/fibronectin extracellular-matrix formulation, dynamic live-cell biomarkers, a microfluidic device, machine-vision analysis and machine-learning algorithms, and generates predictive scores of adverse pathology at the time of surgery. Predictive scores for the risk stratification of 59 prostate cancer patients and 47 breast cancer patients, with values for area under the curve in receiver-operating-characteristic curves surpassing 80%, support the validation of the assay and its potential clinical applicability for the risk stratification of cancer patients.

Perceptions of Prostate MRI and Fusion Biopsy of Radiation Oncologists and Urologists for Patients Diagnosed with Prostate Cancer: Results from a National Survey

BackgroundMagnetic resonance imaging (MRI) of the prostate and fusion biopsy have been advanced to improve the detection of clinically significant prostate cancer (PCa). Yet, frequency of their use and contemporary attitudes among radiation oncologists (ROs) and urologists (UROs) remain largely unknown. ObjectiveWe performed a national survey of UROs and ROs to assess the perceived attitudes towards and frequency of prostate MRI and fusion biopsy. Design, setting, and participantsWe conducted a national survey of 915 ROs and 940 UROs about prostate MRI and fusion biopsy in 2017. Outcome measurements and statistical analysisThe survey queried respondents about perceptions of prostate MRI and fusion biopsy and inquired about self-reported utilization. Pearson chi-square test and multivariable logistic regression were used to identify physician characteristics associated with survey responses. Results and limitationsThe overall response rate was 37% (n=691). Both UROs and ROs demonstrated similar positive views that MRI with fusion biopsy improves PCa risk stratification (67% vs 71%; p=0.19) and fusion biopsy increases the confidence recommending active surveillance (55% vs 60%; p=0.18). Yet, only a quarter of both specialties reported frequent use of prostate MRI for treatment decisions for low- and intermediate-risk PCa. Compared with respondents practicing in community practices, those in academic practices were more likely to report using prostate MRI for low- (44% vs 19%; adjusted odds ratio [OR]: 3.96; p<0.001) and intermediate-risk PCa (42% vs 24%; adjusted OR: 2.49; p<0.001). Our study was limited by a modestly lower response rate. ConclusionsWhile both specialties have perceived value in favor of prostate MRI and fusion biopsy, only a quarter of respondents report their use in clinical practice. Physicians practicing in academic medical centers had greater self-reported use. Patient summaryMagnetic resonance imaging of the prostate and targeted biopsies have growing evidence of their use as a superior diagnostic methodology for prostate cancer diagnosis and treatment decisions. Our survey study found that a majority of radiation oncologists and urologists view both favorably in improving prostate cancer detection and treatment decisions. Yet, only a quarter report using it in routine clinical practice for men diagnosed with prostate cancer.

Risk Stratification of Prostate Cancer Using the Combination of Histogram Analysis of Apparent Diffusion Coefficient Across Tumor Diffusion Volume and Clinical Information: A Pilot Study.

The effectiveness of quantitative MRI and clinical information in the risk stratification of prostate cancer (PCa) patients was evaluated separately in previous research; however, the differentiation power of combining quantitative MRI and clinical information has yet to be investigated. To investigate the power of combining histogram analysis of apparent diffusion coefficient (ADC) of tumor diffusion volume (tDv) with clinical information for the differentiation of low-grade (Gleason score [GS] ≤6) and high-grade (GS ≥7) PCa. Retrospective. Fifty-nine PCa patients who underwent preoperative diffusion-weighted imaging (DWI) (acquired with b = 0, 1000 mm2 /s) and followed by radical prostatectomy within 6 months. T2 -weighted, DWI, and ADC images at 3.0T. tDv defined with different ADC thresholds were analyzed for each patient and combined with age and prostate-specific antigen (PSA) level. Binary logistic regression with backward feature selection was applied to determine the best discrimination and corresponding combination of parameters. Kolmogorov-Smirnov test; independent samples t-test; Mann-Whitney U-test; Spearman's rank correlation; receiver operating characteristic (ROC) analysis; binary logistical regression. PSA and the 10th percentile ADC value of tDv defined with different diffusion thresholds were significantly different between low-grade and high-grade PCa groups (P < 0.05 for all). Median ADC of tDv based on a threshold of 1.008 × 10-3 mm2 /s exhibited the best performance (AUC = 0.86, 95% confidence interval [CI]: 0.75-0.94), whereas binary logistic regression with backward feature selection achieved 97.20% accuracy with AUC = 0.978 (95% CI: 0.929-0.997). The discriminatory power of a single histogram variable of ADC in tDv was not significantly superior to that of a single clinical parameter. The combination of histogram analysis of ADC of tDv and clinical information using logistic regression might significantly improve the risk stratification of PCa and achieve reasonably high accuracy. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:556-564.

Urinary markers aiding in the detection and risk stratification of prostate cancer.

The purpose of this review is to highlight the role of existing and promising urinary biomarkers for the detection and prognostication of prostate cancer (PCa). A number of novel urinary biomarkers have been introduced into the clinical space, which in combination with clinical variables, have demonstrated an increased ability to select patients for biopsy and identify men at risk of harboring clinically significant PCa. Though a number of assays require further validation, initial data is promising and forthcoming results will ultimately determine their clinical utility and commercial availability. For the past 30 years, first-line screening for PCa has relied on measurement of serum prostate-specific antigen (PSA) levels and the results from a digital rectal exam (DRE). A large body of evidence from the last 3 decades indicates that these screening methods are problematic, and often inadequate for detecting clinically significant PCa. Extensive efforts have recently been made to identify and commercialize novel PCa biomarkers for more effective detection of PCa, either alone or in combination with current screening methods. This review article highlights problems with current screening standards, and discusses 6 urinary biomarker assays in terms of their ability to detect and risk-stratify PCa: prostate cancer antigen 3 (PCA3), TMPRSS2-ERG, second chromosome locus associated with prostate-1 (SChLAP1), ExoDx, SelectMDx, and Michigan Prostate Score (MiPS).

Entering an era of radiogenomics in prostate cancer risk stratification.

Radiogenomics is a field that amalgamates data from genomics and imaging techniques in order to derive clinically meaningful trends. In this article, we discuss the importance of prostate cancer risk classification and how data derived from genomic testing and multi-parametric magnetic resonance imaging (mpMRI) can be integrated into clinical decision-making processes with a focus on active surveillance (AS). Finally, we describe an ongoing prospective trial (Miami MAST trial) which incorporates imaging (mpMRI) and radiomics data in patients who are on AS for prostate cancer.

Training and validation of a novel 4-miRNA ratio model (MiCaP) for prediction of postoperative outcome in prostate cancer patients

BackgroundNew molecular biomarkers for prostate cancer (PC) prognosis are urgently needed. Ratio-based models are attractive, as they require no additional normalization. Here, we train and independently validate a novel 4-miRNA prognostic ratio model for PC. Patients and methodsBy genome-wide miRNA expression profiling of PC tissue samples from 123 men who underwent radical prostatectomy (RP) (PCA123, training cohort), we identified six top candidate prognostic miRNAs and systematically tested their ability to predict postoperative biochemical recurrence (BCR). The best miRNA-based prognostic ratio model (MiCaP) was validated in two independent cohorts (PCA352 and PCA476) including >800 RP patients in total. Clinical end points were BCR and prostate cancer-specific survival (CSS). The prognostic potential of MiCaP was assessed by univariate and multivariate Cox-regression analyses and Kaplan–Meier analyses. ResultsWe identified a 4-miRNA ratio model, MiCaP (miR-23a-3p×miR-10b-5p)/(miR-133a×miR-374b-5p), that predicted time to BCR independently of routine clinicopathologic variables in the training cohort (PCA123) and was successfully validated in two independent RP cohorts. In addition, MiCaP was a significant predictor of CSS in univariate analysis [HR 3.35 (95% CI 1.34−8.35), P=0.0096] and in multivariate analysis [HR 2.43 (95% CI 1.45–4.07), P=0.0210]. As proof-of-principle, we also analyzed MiCaP in plasma samples from 111 RP patients. A high MiCaP score in plasma was significantly associated with BCR (P=0.0036, Kaplan–Meier analysis). Limitations include low mortality rates (CSS: 5.4%). ConclusionsWe identified a novel 4-miRNA ratio model (MiCaP) with significant independent prognostic value in three RP cohorts, indicating promising potential to improve PC risk stratification.

Refining the risk-stratification of transrectal biopsy-detected prostate cancer by elastic fusion registration transperineal biopsies.

To evaluate image-guided Transperineal Elastic-Registration biopsy (TPER-B) in the risk-stratification of low-intermediate risk prostate cancer detected by Transrectal-ultrasound biopsy (TRUS-B) when estimates of cancer grade and volume discorded with multiparametric Magnetic Resonance Imaging (MRI). All patients referred for active surveillance or organ-conservative management were collegially reviewed for consistency between TRUS-B results and MRI. Image-guided TPER-B of the index target (IT) defined as the largest Prostate Imaging-Reporting Data System-v2 ≥ 3 abnormality was organized for discordant cases. Pathology reported Gleason grade, maximum cancer core length (MCCL) and total CCL (TCCL). Of 237 prostate cancer patients (1-4/2018), 30 were required TPER-B for risk-stratification. Eight cores were obtained [Median and IQR: 8 (6-9)] including six (IQR: 4-6) in the IT. TPER-B of the IT yielded longer MCCL [Mean and (95%CI): 6.9 (5.0-8.8) vs. 2.6mm (1.9-3.3), p < 0.0001] and TCCL [19.7 (11.6-27.8) vs. 3.6mm (2.6-4.5), p = 0.0002] than TRUS-B of the gland. On TPER-B cores, longer MCCL [Mean and (95%CI): 8.7mm (6.7-10.7) vs. 4.1mm (0.6-7.6), p = 0.002] were measured in Gleason score-7 cancers. TPER-B cores upgraded 13/30 (43.3%) patients. 14/30 (46.7%) met University College London-definition 1 and 18/30 (60.0%) definition 2, which correlate with clinically significant cancers > 0.5mL and > 0.2mL, respectively. 7/16 (43.8%) patients under active surveillance were re-allocated toward prostatectomy (n = 5) or radiation therapy (n = 2). In 14 patients not yet assigned, TPER-B risk-stratification spurred the selection (13/14, 92.9%) of treatments with curative intent. Image-guided TPER-B of the index target provided more cancer material for pathology. Subsequent re-evaluation of cancer volume and grade switched a majority of patients towards higher-risk groups and treatments with curative intent.