Prostate Cancer Incidence and Mortality in Men Exposed to α1-Adrenoceptor Antagonists.

BACKGROUND: α1-antagonists are commonly used to treat benign prostatic hyperplasia. Preclinical studies suggest they induce cell death and inhibit tumor growth. This study evaluates the risk of prostate cancer death in men using α1-antagonists. METHODS: A population-based cohort study in Stockholm, Sweden (January 1, 2007 to December 31, 2019) including 451,779 men with a prostate-specific antigen (PSA) test. Study entry was one year after the first PSA test. Men were considered exposed at their second filled prescription. Primary outcome: prostate cancer mortality. Secondary outcomes: all-cause mortality and prostate cancer incidence. Cox proportional hazard regression models were used to calculate adjusted hazard ratios (HRs) and 95% CIs for all outcomes. Inverse probability weighting with marginal structural models accounted for time-dependent confounders. RESULTS: Of 351,297 men in the cohort, 39,856 (11.3%) were exposed to α1-antagonists. Median follow-up for prostate cancer mortality was 8.9 years and median exposure time to α1-antagonists was 4.4 years. There was no evidence of an association between α1-antagonist use and prostate cancer mortality, all-cause mortality, or high-grade prostate cancer. α1-antagonist-use was associated with an increased risk of prostate cancer (HR: 1.11, 95% CI: 1.06-1.17) and low-grade prostate cancer (HR: 1.22, 95% CI: 1.11-1.33). Men treated with α1-antagonists had more frequent PSA testing. CONCLUSIONS: Our findings show no significant association between α1-adrenoceptor antagonist exposure and prostate cancer mortality or high-grade prostate cancer. Although the preclinical evidence indicates a potential chemopreventive effect, this study's findings do not support it.

Clinical Significance of Extracellular Vesicles in Prostate and Renal Cancer.

Extracellular vesicles (EVs)-including apoptotic bodies, microvesicles, and exosomes-are released by almost all cell types and contain molecular footprints from their cell of origin, including lipids, proteins, metabolites, RNA, and DNA. They have been successfully isolated from blood, urine, semen, and other body fluids. In this review, we discuss the current understanding of the predictive value of EVs in prostate and renal cancer. We also describe the findings supporting the use of EVs from liquid biopsies in stratifying high-risk prostate/kidney cancer and advanced disease, such as castration-resistant (CRPC) and neuroendocrine prostate cancer (NEPC) as well as metastatic renal cell carcinoma (RCC). Assays based on EVs isolated from urine and blood have the potential to serve as highly sensitive diagnostic studies as well as predictive measures of tumor recurrence in patients with prostate and renal cancers. Overall, we discuss the biogenesis, isolation, liquid-biopsy, and therapeutic applications of EVs in CRPC, NEPC, and RCC.

Decipher Score predicts prostate specific antigen persistence after prostatectomy.

BACKGROUND: The aim of this study was to evaluate genomic risk of patients with persistent prostate specific antigen (PSA) using mRNA expression analysis and a validated prognostic genomic-risk classifier. METHODS: Monocentric retrospective study including all patients who underwent radical prostatectomy (RP) by one surgeon and Decipher Test from October 2013 to December 2018. PSA persistent population was defined as all patients with two consecutive PSA>0.1 ng/mL at follow-up after the surgery. Neurovascular Structure-adjacent Frozen-section Examination (NeuroSAFE) was performed intraoperatively for research of positive surgical margins. Multivariate analysis was performed for persistent PSA (pPSA) predictors. A specific localized, organ-confined, and negative margins sub-population with PSA persistence was compared to a similar sub-population without PSA persistence for genomic differential expression analyses. RESULTS: A total of 564 patients were included and 61 of them had pPSA. Preoperative PSA was higher in the PSA persistent group (11.6 [6.4, 21.2] vs. 6.2 [4.7, 9.2] P=0.00010), as well as PSA density (PSAd) (0.3 [0.2, 0.5] vs. 0.2 [0.1, 0.3] P=0.0001). Postoperative characteristics, Gleason Score, and positive surgical margins were significantly higher in the PSA persistent population. 31 patients had pPSA in our specific subpopulation and were compared to 217 patients with no pPSA. On multivariate analysis, only Decipher Score (OR=5.64 [1.28; 24.89], P=0.022) and preoperative PSA (OR=1.06, [1.02; 1.09], P=0.001) were significant predictors for PSA persistence. We found two genes to be significantly upregulated with a 2.5-fold change in our specific subpopulation (SERPINB11 and PDE11A). CONCLUSIONS: We found unique genomic features of patients with pPSA, whilst confirming previous clinical findings that this condition behaves to a worse prognosis. Given this high genomic risk, further imaging studies should be performed to select patients for early treatment intensification.

'Stealth' Prostate Tumors.

BACKGROUND: The aim of this study was to determine the false negative rates of prebiopsy magnetic resonance imaging (MRI) and MRI-ultrasound (US) 12-core systematic prostate biopsy (PBx) by analyzing radical prostatectomy specimens. METHODS: This retrospective study included 3600 prostate cancer (PCa) patients who underwent robot-assisted laparoscopic radical prostatectomy. Based on comparison of lobe-specific data on final pathology with preoperative biopsy and imaging data, the study population was subdivided into group I-contralateral (CL) benign PBx (n = 983), group II-CL and/or bilateral (BL) non-suspicious mpMRI (n = 2223) and group III-CL benign PBx + non-suspicious mpMRI (n = 688). This population was studied for the presence of PCa, clinically significant PCa (csPCa), extracapsular extension (ECE) (pathological stage pT3), positive frozen section and final positive surgical margin (PSM) in the CL lobe. Descriptive statistics were performed. RESULTS: In subgroups I, II and III, PCa was respectively detected in 21.5%, 37.7% and 19.5% of cases, and csPCa in 11.3%, 16.3% and 10.3% of cases. CL pT3 disease was seen in 4.5%, 4% and 5.5%, and CL surgical margins and/or frozen section analysis were positive in 6%, 7% and 5% of cases in subgroups I, II and III, respectively. CONCLUSIONS: There are still significant rates of false negatives in the standard care diagnostics of PCa. Further strategies are required to improve the accuracy of diagnosis and determination of tumor location.

Robot-assisted simple prostatectomy for prostates greater than 100 g.

PURPOSE: Efforts are ongoing to treat severe benign prostatic hyperplasia as traditional endoscopic treatment options are often difficult to perform and associated with significant complications. This manuscript highlights our initial experience of robot-assisted simple prostatectomy [RASP] with minimum a year follow-up. We also compared our outcomes with published literature. METHODS: After an Institution Review Board approval, we gathered data of 50 cases of RASP between Jan 2014 and May 2021. Patients with prostate volume > 100 cc [calculated from magnetic resonance imaging (MRI)] and prostate biopsy confirmed benign prostate were candidates for RASP. Patients underwent RASP via transperitoneal route either by suprapubic or trans-vesical approach. Preoperative demographics, peri-operative parameters and post-operative parameters such as hospital stay, catheter removal, urinary continence and uroflow were recorded in standard database and presented as descriptive statistics. RESULTS: Patients presented with a baseline median International Prostate Symptom Score (IPSS) of 23 (inter-quartile range (IQR) 21,25) and a median PSA of 7.7 ng/ml (IQR 6.4,8.7). Median preoperative prostate volume was 167 ml (IQR, 136,198 ml). Median console time was 118 min, and median estimated blood loss was 148 ml (IQR 130, 167 ml). None of our cohort needed intraoperative transfusion, conversion to open surgery or developed any complications. Median time to Foley removal was 10 days (IQR 8,12). Significant drop in the IPSS score and improvement in Qmax was noted over the period of follow-up. CONCLUSION: RASP is associated with considerable improvements in urinary symptoms. However, comparative studies with endoscopic treatment options of large prostatic adenomas are warranted and ideally include cost analysis of different procedures.

When to order genomic tests: development and external validation of a model to predict high-risk prostate cancer at the genotypic level.

PURPOSE: The aim of this study was to develop a model to predict high-genomic-risk prostate cancer (PCa) according to Decipher score, a validated 22 gene prognostic panel. By doing so, one might select the individuals who are likely to benefit from genomic testing and improve pre-op counseling about the need for adjuvant treatments. METHODS: We retrospectively reviewed IRB-approved databases at two institutions. All patients had preoperative magnetic resonance imaging (MRI) and Decipher prostate radical prostatectomy (RP), a validated 22 gene prognostic panel. We used binary logistic regression to estimate high-risk Decipher (Decipher score > 0.60) probability on RP specimen. Area under the curve (AUC) and calibration were used to assess the accuracy of the model in the development and validation cohort. Decision curve analysis (DCA) was performed to assess the clinical benefit of the model. RESULTS: The development and validation cohort included 622 and 185 patients with 283 (35%) and 80 (43%) of those with high-risk Decipher. The multivariable model included PSA density, biopsy Gleason Grade Group, percentage of positive cores and MRI extracapsular extension. AUC was 0.73 after leave-one-out cross-validation. DCA showed a clinical benefit in a range of probabilities between 15 and 60%. In the external validation cohort, AUC was 0.70 and calibration showed that the model underestimates the actual probability of the outcome. CONCLUSIONS: The proposed model to predict high-risk Decipher score at RP is helpful to improve risk stratification of patients with PCa and to assess the need for additional testing and treatments.

A SelectMDx/magnetic resonance imaging-based nomogram to diagnose prostate cancer.

BACKGROUND: 70%-80% of prostate cancer (PCa) biopsies performed in the US annually may be unnecessary. Specific antigen testing (PSA) and tans rectal ultrasound (TRUS) are imprecise predictive methods for risk of PCa. Novel strategies are critical to guide biopsy decision-making. AIM: We assessed the utility and accuracy of combining Select MDx and multiparametric magnetic resonance imaging (mpMRI) scores for predicting risk of PCa. METHODS AND RESULTS: Our study was conducted at Mount Sinai hospital at Urology department in New York City from January 2020 to April 2021. Total 129 men performed select MDx test. Indications for prostate biopsy were high-risk Select MDx score, suspicious DRE, PI-RADS scores 3/4/5 on mpMRI, or any combination of these. Fifty-one percentage of 129 patients underwent systemic or combined systemic and MRI/US (ultrasound) fusion biopsy; All men underwent 3 T MRI of Prostate w/wo contrast using standard protocols prior to biopsy. A single surgeon performed prostate biopsies. Gleason score ≥3 + 3 on biopsy is defined as outcome. Descriptive statistics were calculated as cross tables. Binary logistic regression model is used to determine the outcome. The nomogram was based on the coefficients of the logit function. ROCs were plotted and decision curve analysis was performed. Using both high-risk Select MDx and PI-RADS scores of 4/5, 87% of biopsies could have been avoided, while detecting 64% of PCa and missing 36%. If biopsies were performed on men with positive Select MDx or PI-RADS 4/5 results, 16% of biopsies could have been avoided while detecting all PCa. Combining these scores improved specificity and accuracy for the detection of PCa over either used alone. Study limitations include limited sample size, sole institution study, and risk or overfitting for the proposed model which may limit generalizability. CONCLUSION: Combining SelectMDx and mpMRI PI-PADS scores of 4/5 may be useful for PCa biopsy decision-making.

Technical Tips in Managing Large Median Lobes During Robot-assisted Radical Prostatectomy.

Prostate cancer surgeons are commonly faced by a technically challenging situation dealing with prostate cancer having large median lobes. Patients with large median lobes often have larger prostates, which makes it difficult to visualize anatomical planes during robot-assisted radical prostatectomy (RARP). Herein, we described our experience in dealing with large median lobes during RARP. We have focused on technical tips to avoid complications and facilitate a smooth procedure in patients with large median lobes during RARP. A total of 2671 patients who underwent RARP were divided into two groups based on the presence or absence of a protruded median lobe (PML): group A (2411 patients without a PML) and group B (260 patients with a PML). All patients underwent preoperative magnetic resonance imaging and final intraoperative confirmation for the presence of a PML. Pre-, intra-, and postoperative parameters were compared in two groups using the Student t test and two-proportion t test as appropriate. Patients in group B have statistically significantly higher median prostate-specific antigen (PSA; 7.7 vs 5.8 ng/dl), PSA density (0.17 vs 0.09), and International Prostate Symptom Score (19.5 vs 7.2); longer median console time (114 vs 134 min) and surgery time (145 vs 170 min); and higher blood loss (150 vs 175 ml) than those in group A. There were no statistically significant differences in pathological stages (T2, T3; 87%, 13% vs 88%, 12%) and rates of positive surgical margins (7% vs 8.5%) between groups A and B. Single-center and retrospective design was the major limitation of our study. We conclude that understanding the key steps to facilitate bladder neck dissection is vital to avoid serious intraoperative events and to maximize outcomes. Patient summary: In this report, we looked at our robotic radical prostatectomy cohort with large median lobes. We found that surgery in these patients requires more time and blood loss, but similar cancer control. We conclude that following the key steps are important to avoid complications.

The Mount Sinai Prebiopsy Risk Calculator for Predicting any Prostate Cancer and Clinically Significant Prostate Cancer: Development of a Risk Predictive Tool and Validation with Advanced Neural Networking, Prostate Magnetic Resonance Imaging Outcome Database, and European Randomized Study of Screening for Prostate Cancer Risk Calculator.

Background: The European Association of Urology guidelines recommend the use of imaging, biomarkers, and risk calculators in men at risk of prostate cancer. Risk predictive calculators that combine multiparametric magnetic resonance imaging with prebiopsy variables aid as an individualized decision-making tool for patients at risk of prostate cancer, and advanced neural networking increases reliability of these tools. Objective: To develop a comprehensive risk predictive online web-based tool using magnetic resonance imaging (MRI) and clinical data, to predict the risk of any prostate cancer (PCa) and clinically significant PCa (csPCa) applicable to biopsy-naïve men, men with a prior negative biopsy, men with prior positive low-grade cancer, and men with negative MRI. Design setting and participants: Institutional review board-approved prospective data of 1902 men undergoing biopsy from October 2013 to September 2021 at Mount Sinai were collected. Outcome measurements and statistical analysis: Univariable and multivariable analyses were used to evaluate clinical variables such as age, race, digital rectal examination, family history, prostate-specific antigen (PSA), biopsy status, Prostate Imaging Reporting and Data System score, and prostate volume, which emerged as predictors for any PCa and csPCa. Binary logistic regression was performed to study the probability. Validation was performed with advanced neural networking (ANN), multi-institutional European cohort (Prostate MRI Outcome Database [PROMOD]), and European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSPC RC) 3/4. Results and limitations: Overall, 2363 biopsies had complete clinical information, with 57.98% any cancer and 31.40% csPCa. The prediction model was significantly associated with both any PCa and csPCa having an area under the curve (AUC) of 81.9% including clinical data. The AUC for external validation was calculated in PROMOD, ERSPC RC, and ANN for any PCa (0.82 vs 0.70 vs 0.90) and csPCa (0.82 vs 0.78 vs 0.92), respectively. This study is limited by its retrospective design and overestimation of csPCa in the PROMOD cohort. Conclusions: The Mount Sinai Prebiopsy Risk Calculator combines PSA, imaging and clinical data to predict the risk of any PCa and csPCa for all patient settings. With accurate validation results in a large European cohort, ERSPC RC, and ANN, it exhibits its efficiency and applicability in a more generalized population. This calculator is available online in the form of a free web-based tool that can aid clinicians in better patients counseling and treatment decision-making. Patient summary: We developed the Mount Sinai Prebiopsy Risk Calculator (MSP-RC) to assess the likelihood of any prostate cancer and clinically significant disease based on a combination of clinical and imaging characteristics. MSP-RC is applicable to all patient settings and accessible online.

Prostate MRI percentage tumor involvement or "PI-RADS percent" as a predictor of adverse surgical pathology.

BACKGROUND: This study assesses magnetic resonance imaging (MRI) prostate % tumor involvement or "PI-RADs percent" as a predictor of adverse pathology (AP) after surgery for localized prostate cancer (PCa). Two separate variables, "All PI-RADS percent" (APP) and "Highest PI-RADS percent" (HPP), are defined as the volume of All PI-RADS 3-5 score lesions on MRI and the volume of the Highest PI-RADS 3-5 score lesion each divided by TPV, respectively. METHOD: An analysis was done of an IRB approved prospective cohort of 557 patients with localized PCa who had targeted biopsy of MRI PIRADs 3-5 lesions followed by RARP from April 2015 to May 2020 performed by a single surgeon at a single center. AP was defined as ISUP GGG ≥3, pT stage ≥T3 and/or LNI. Univariate and multivariable analyses were used to evaluate APP and HPP at predicting AP with other clinical variables such as Age, PSA at surgery, Race, Biopsy GGG, mpMRI ECE and mpMRI SVI. Internal and External Validation demonstrated predicted probabilities versus observed probabilities. RESULTS: AP was reported in 44.5% (n = 248) of patients. Multivariable regression showed both APP (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.14, p = 0.0007) and HPP (OR: 1.10; 95% CI: 1.04-1.16; p = 0.0007) were significantly associated with AP with individual area under the operating curves (AUCs) of 0.6142 and 0.6229, respectively, and AUCs of 0.8129 and 0.8124 when incorporated in models including preoperative PSA and highest biopsy GGG. CONCLUSIONS: Increasing PI-RADS Percent was associated with a higher risk of AP, and both APP and HPP may have clinical utility as predictors of AP in GGG 1 and 2 patients being considered for AS. PATIENT SUMMARY: Using PIRADs percent to predict AP for presurgical patients may help risk stratification, and for low and low volume intermediate risk patients, may influence treatment decisions.

Nomogram Predicting Adverse Pathology Outcome on Radical Prostatectomy in Low-Risk Prostate Cancer Men.

OBJECTIVE: To develop and validate a prediction model to predict the risk of adverse pathology outcome on final pathology in low-risk prostate cancer (PCa) men. MATERIALS AND METHODS: This study was a monocentric retrospective analysis of 426 men who underwent radical prostatectomy (RP) for low-risk PCa. The validation cohort included 103 men from another hospital. Adverse pathology outcome was defined either by upgrading on RP Gleason Score (GS) (from GS 3+3 to GS ≥ 3+4 with Gleason pattern 4 ≥ 10%) or a non-organ confined disease (pathologic stage ≥ pT3a). Multivariable logistic regression analysis was performed to build nomogram for predicting adverse pathology outcome. Nomogram validation was performed by calculating the area under receiver operating characteristic curves (AUC) and comparing nomogram-predicted probabilities with actual rates of adverse pathology outcome in the external cohort. The Kaplan-Meier method was used to estimate and compare the biochemical recurrence-free survival rates between the two groups. RESULTS: Of 426 men in the development cohort, 45.7% showed adverse pathology outcome on RP. Age, body mass index, prostate specific antigen density, history of prior negative biopsy, magnetic resonance imaging prostate imaging reporting and data system score 4-5 and percentage of positive biopsies were significant predictors in multivariate analysis. A nomogram was constructed with an area under curve of 87%. There was agreement between predicted and actual rates of adverse pathology outcome in the validation cohort. The 5-year biochemical recurrence-free survival rates in patients with and without adverse pathology outcome was 70% and 98%, respectively. CONCLUSION: This novel nomogram would help identify low-risk PCa men at risk of adverse pathology outcome and can be relevant for treatment decision-making.

Development and External Validation of a Prediction Model to Identify Candidates for Prostate Biopsy.

PURPOSE: Prostate biopsies are associated with infectious complications and approximately 80% are either benign or clinically insignificant prostate cancer. Our aim is to develop and independently validate prediction model to avoid unnecessary prostate biopsies by predicting clinically significant prostate cancer (csPCa) Materials and Methods: Retrospective analysis of single-center cohort (Mount Sinai Hospital, NY) of 1632 men who underwent systematic or combined systematic and Magnetic Resonance Imaging (MRI)/ultrasound fusion targeted prostate biopsy between 2014-2020. External cohort (University of Miami) included 622 men that underwent biopsy. Outcome for predicting csPCa was defined as International Society of Urologic Pathology (ISUP) Gleason grade ≥ 2 on biopsy. Multivariable logistic regression analysis was performed to build nomogram using coefficients of logit function. Nomogram validation was performed in external cohort by plotting receiver operating characteristics (ROC). We also plotted decision curve analysis (DCA) and compared nomogram-predicted probabilities with actual rates of csPCa probabilities in external cohort. RESULTS: Of 1632 men, 43% showed csPCa on biopsy. PSA density, prior negative biopsy, and Prostate Imaging and Reporting Data System (PI-RADS) scores 3, 4, and 5 were significant predictors for csPCa. ROC for prediction of csPCa was 0.88 in external cohort. There was agreement between predicted and actual rate of csPCa in external cohort. DCA demonstrated net benefit using the model. Using the prediction model at threshold of 30, 35% of biopsies and 46% of diagnosed indolent PCa could be avoided, while missing 5% of csPCa. CONCLUSION: Using our prediction model can help reduce unnecessary prostate biopsies with minimal impact on csPCa detection rates.

Expanding Active Surveillance Inclusion Criteria: A Novel Nomogram Including Preoperative Clinical Parameters and Magnetic Resonance Imaging Findings.

BACKGROUND: Current European Association of Urology, American Urological Association, and National Comprehensive Cancer Network guidelines recommend active surveillance (AS) for selected intermediate-risk prostate cancer (PCa) patients. However, limited evidence exists regarding which men can be selected safely. OBJECTIVE: To externally validate the Gandaglia risk calculator (Gandaglia-RC), designed to predict adverse pathology (AP) at radical prostatectomy (RP) and thus able to improve selection of intermediate-risk PCa patients suitable for AS, and to assess whether addition of magnetic resonance imaging (MRI) findings (MAP model) improves the predictive ability of Gandaglia-RC. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective analysis of a single-center cohort of 1284 consecutive men with low- and intermediate-risk PCa treated with RP between 2013 and 2019. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: AP was defined as non-organ-confined disease and/or lymph node invasion and/or pathological grade group≥3 at RP. Logistic regression was used to calculate the predictors of AP; calculated coefficients were used to develop a risk score. Receiver operating characteristic curve analysis and decision curve analysis were performed to evaluate the net benefit within models. RESULTS AND LIMITATIONS: At multivariable analysis, age at surgery, prostate-specific antigen, systematic and targeted biopsy Gleason grade group, MRI prostate volume, Prostate Imaging Reporting and Data System score, and MRI extraprostatic extension were significantly associated with AP. The model significantly improved the ability of Gandaglia-RC to predict AP (area under the curve 0.71 vs 0.63 [p<0.0001]). Using a 30% threshold, the proportions of men eligible for AS were 45% and 77% and the risks of AP were 16% and 17%, for Gandaglia-RC and MAP model, respectively. CONCLUSIONS: Compared with Gandaglia-RC, the MAP model significantly increased the number of patients eligible for AS without significantly increasing the risk of AP at RP. PATIENT SUMMARY: In this report, we have developed a risk prediction tool to select men for conservative treatment of prostate cancer. Using the novel tool, more men could safely be allocated to conservative treatment rather than surgery or radiation.

Clinical Utility of Negative Multiparametric Magnetic Resonance Imaging in the Diagnosis of Prostate Cancer and Clinically Significant Prostate Cancer.

BACKGROUND: Multiparametric magnetic resonance imaging (MRI) is increasingly used to diagnose prostate cancer (PCa). It is not yet established whether all men with negative MRI (Prostate Imaging-Reporting and Data System version 2 score <3) should undergo prostate biopsy or not. OBJECTIVE: To develop and validate a prediction model that uses clinical parameters to reduce unnecessary prostate biopsies by predicting PCa and clinically significant PCa (csPCa) for men with negative MRI findings who are at risk of harboring PCa. DESIGN SETTING AND PARTICIPANTS: This was a retrospective analysis of 200 men with negative MRI at risk of PCa who underwent prostate biopsy (2014-2020) with prostate-specific antigen (PSA) >4 ng/ml, 4Kscore of >7%, PSA density ≥0.15 ng/ml/cm3, and/or suspicious digital rectal examination. The validation cohort included 182 men from another centre (University of Miami) with negative MRI who underwent systematic prostate biopsy with the same criteria. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: csPCa was defined as Gleason grade group ≥2 on biopsy. Multivariable logistic regression analysis was performed using coefficients of logit function for predicting PCa and csPCa. Nomogram validation was performed by calculating the area under receiver operating characteristic curves (AUC) and comparing nomogram-predicted probabilities with actual rates of PCa and csPCa. RESULTS AND LIMITATIONS: Of 200 men in the development cohort, 18% showed PCa and 8% showed csPCa on biopsy. Of 182 men in the validation cohort, 21% showed PCa and 6% showed csPCa on biopsy. PSA density, 4Kscore, and family history of PCa were significant predictors for PCa and csPCa. The AUC was 0.80 and 0.87 for prediction of PCa and csPCa, respectively. There was agreement between predicted and actual rates of PCa in the validation cohort. Using the prediction model at threshold of 40, 47% of benign biopsies and 15% of indolent PCa cases diagnosed could be avoided, while missing 10% of csPCa cases. The small sample size and number of events are limitations of the study. CONCLUSIONS: Our prediction model can reduce the number of prostate biopsies among men with negative MRI without compromising the detection of csPCa. PATIENT SUMMARY: We developed a tool for selection of men with negative MRI (magnetic resonance imaging) findings for prostate cancer who should undergo prostate biopsy. This risk prediction tool safely reduces the number of men who need to undergo the procedure.

Unannotated small RNA clusters associated with circulating extracellular vesicles detect early stage liver cancer.

OBJECTIVE: Surveillance tools for early cancer detection are suboptimal, including hepatocellular carcinoma (HCC), and biomarkers are urgently needed. Extracellular vesicles (EVs) have gained increasing scientific interest due to their involvement in tumour initiation and metastasis; however, most extracellular RNA (exRNA) blood-based biomarker studies are limited to annotated genomic regions. DESIGN: EVs were isolated with differential ultracentrifugation and integrated nanoscale deterministic lateral displacement arrays (nanoDLD) and quality assessed by electron microscopy, immunoblotting, nanoparticle tracking and deconvolution analysis. Genome-wide sequencing of the largely unexplored small exRNA landscape, including unannotated transcripts, identified and reproducibly quantified small RNA clusters (smRCs). Their key genomic features were delineated across biospecimens and EV isolation techniques in prostate cancer and HCC. Three independent exRNA cancer datasets with a total of 479 samples from 375 patients, including longitudinal samples, were used for this study. RESULTS: ExRNA smRCs were dominated by uncharacterised, unannotated small RNA with a consensus sequence of 20 nt. An unannotated 3-smRC signature was significantly overexpressed in plasma exRNA of patients with HCC (p<0.01, n=157). An independent validation in a phase 2 biomarker case-control study revealed 86% sensitivity and 91% specificity for the detection of early HCC from controls at risk (n=209) (area under the receiver operating curve (AUC): 0.87). The 3-smRC signature was independent of alpha-fetoprotein (p<0.0001) and a composite model yielded an increased AUC of 0.93. CONCLUSION: These findings directly lead to the prospect of a minimally invasive, blood-only, operator-independent clinical tool for HCC surveillance, thus highlighting the potential of unannotated smRCs for biomarker research in cancer.

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate biopsies without missing clinically significant prostate cancers (csPCa). The utility of multiparametric magnetic resonance imaging (mpMRI) in detecting prostate cancer (PCa) shows promise to be used as triage test for systematic prostate biopsy. Our aim is to Study clinical parameters and oncological outcomes in men with negative mpMRI (nMRI; PI-RADS v2 scores of ≤ 2) who underwent robot-assisted radical prostatectomy (RARP) to evaluate nMRI's practicality as a biopsy triage test. METHODS: Retrospective analysis of 331 men with nMRI who underwent RARP between 2014 and 2020 compared with men with positive mpMRI (pMRI; PI-RADS v2 scores ≥ 3, N = 1770). csPCa was defined as Gleason score ≥ 3 + 4 and biochemical recurrence (BCR) was defined as PSA > 0.2 ng/ml on two occasions. Biopsies were graded with the International Society of Urologic Pathology [ISUP] grade. Descriptive statistics for nMRI and pMRI were performed. Mann-Whitney U test was used for continuous variables and χ 2 for categorical variables. Univariable and multivariable regression analyses were performed. RESULTS: Univariable analysis shows statistically significant difference (p < .05) between median age (nMRI-61 years vs. pMRI 63 years), race (higher incidence of nMRI in African American men), use of 5-alpha reductase inhibitors (higher rate in nMRI). While incidence rates of family history of PCa, suspicious digital rectal examination (DRE) findings, median PSA levels and 4Kscore, were lower in nMRI versus pMRI. Rates of positive surgical margins and BCR were comparable in nMRI versus pMRI. Biopsy ISUP Grades I and II upgraded by 51% and 12%, respectively in final pathology. African American race and no history of the prior negative biopsy were significant predictors for upgrading. CONCLUSION: Men with nMRI pose diagnostic challenges as they tend to be younger patients with lower rates of suspicious DRE findings and lower 4K scores, yet comparable oncological outcomes in csPCa rates, positive surgical margins, and BCR rates.

A 4K score/MRI-based nomogram for predicting prostate cancer, clinically significant prostate cancer, and unfavorable prostate cancer.

BACKGROUND: The detection of prostate cancer requires histological confirmation in biopsy core. Currently, number of unnecessary prostate biopsies are being performed in the United States. This is due to the absence of appropriate biopsy decision-making protocol. AIM: To develop and validate a 4K score/multiparametric magnetic resonance imaging (mpMRI)-based nomogram to predict prostate cancer (PCa), clinically significant prostate cancer (csPCa), and unfavorable prostate cancer (uPCa). METHODS AND RESULTS: Retrospective, single-center study evaluating a cohort of 574 men with 4K score test >7% or suspicious digital rectal examination (DRE) or Prostate Imaging Reporting and Data System (PI-RADS) scores 3, 4, or 5 on mpMRI that underwent systematic and/or mpMRI/ultrasound fusion-targeted prostate biopsy between 2016 and 2020. External cohort included 622 men. csPCa and uPCa were defined as Gleason score ≥3 + 4 and ≥4 + 3 on biopsy, respectively. Multivariable logistic regression analysis was performed to build nomogram for predicting PCa, csPCa, and uPCa. Validation was performed by plotting the area under the curve (AUC) and comparing nomogram-predicted probabilities with actual rates of PCa, csPCa, and uPCa probabilities in the external cohort. 4K score, a PI-RADS ≥4, prostate volume and prior negative biopsy were significant predictors of PCa, csPCa, and uPCa. AUCs were 0.84, 0.88, and 0.86 for the prediction of PCa, csPCa, and uPCa, respectively. The predicted and actual rates of PCa, csPCa, and uPCa showed agreement across all percentage probability ranges in the validation cohort. Using the prediction model at threshold of 30, 30% of overall biopsies, 41% of benign biopsies, and 19% of diagnosed indolent PCa could be avoided, while missing 9% of csPCa. CONCLUSION: This novel nomogram would reduce unnecessary prostate biopsies and decrease detection of clinically insignificant PCa.

Using biomarkers in patients with positive multiparametric magnetic resonance imaging: 4Kscore predicts the presence of cancer outside the index lesion.

OBJECTIVES: To evaluate if the blood biomarker, 4Kscore, in addition to multiparametric magnetic resonance imaging information could identify patients who would benefit from undergoing only a targeted biopsy. METHODS: We retrospectively analyzed a population of 256 men with positive multiparametric magnetic resonance imaging who underwent standard + targeted biopsy at Mount Sinai Hospital, New York, NY, USA. 4Kscore (OPKO Health, Miami, FL, USA) was sampled from all patients before biopsy. Uni- and multivariable binary logistic regression analyses were carried out to predict clinically significant prostate cancer, defined as International Society of Urological Pathology grade group ≥2, in standard biopsy cores. The model with the best area under the curve was selected and internal validation was carried out using the leave-one-out cross-validation. RESULTS: The developed model showed an area under the curve of 0.86. Carrying out only targeted biopsy in patients with a model-derived probability <12.5% resulted in 39.5% (n = 101) fewer standard biopsies and a 33.9% (n = 20) reduction of detecting grade group 1 disease, while missing grade group ≥2 in 5.2% (n = 4) using standard biopsy only and 1.1% (n = 1) using standard biopsy + targeted biopsy. CONCLUSIONS: 4Kscore in combination with multiparametric magnetic resonance imaging can help to reduce unnecessary standard biopsy and decrease detection of clinically insignificant prostate cancer.

Hood Technique for Robotic Radical Prostatectomy-Preserving Periurethral Anatomical Structures in the Space of Retzius and Sparing the Pouch of Douglas, Enabling Early Return of Continence Without Compromising Surgical Margin Rates.

BACKGROUND: A common side effect following radical prostatectomy is urinary incontinence. Here, we describe a novel surgical technique to reduce postoperative urinary incontinence and facilitate early return of continence. OBJECTIVE: To describe the novel "hood technique" for robotic-assisted radical prostatectomy (RARP). DESIGN, SETTING, AND PARTICIPANTS: This is an institutional review board-approved prospective study of 300 patients (median age 64 yr) with localized prostate cancer treated with the RARP hood technique at a major urban hospital between April 2018 and March 2019. The exclusion criteria were as follows: patients with anterior tumor location based on biopsy or multiparametric magnetic resonance imaging. All but one patient participated in follow-up over 12 mo after the procedure. SURGICAL PROCEDURE: The RARP "hood technique" was performed to preserve the detrusor apron, puboprostatic ligament complex, arcus tendineus, endopelvic fascia, and pouch of Douglas. MEASUREMENTS: Clinical data collected included pre- and intraoperative variables, and postoperative functional and oncological outcomes and complications. Descriptive statistical analysis was performed. RESULTS AND LIMITATIONS: Continence rates at 1, 2, 4, 6 12, 24, and 48 wk after catheter removal were 21%, 36%, 83%, 88%, 91%, 94%, and 95%, respectively. Positive surgical margin rate was 6%. Thirty patients (9.7%) experienced complications after RARP: 17 (5.7%), 11 (3.6%), and one (0.4%) had Clavien-Dindo grade I, II, and III complications, respectively. This study was conducted within a single health system and may not be generalizable. The study lacked randomization and a comparative arm. CONCLUSIONS: Results indicate that the hood technique spares musculofascial structures anterior to the urethral sphincter complex with early return of continence after surgery, without compromising positive surgical margin rates. Exclusion of anterior tumor location contributed to a reduction in positive surgical margins. PATIENT SUMMARY: By better preservation of anatomical structures around the urethra, we were able to achieve early return of urinary continence without a negative impact on complications and cancer outcomes.

Combined Use of Prostate-specific Antigen Density and Magnetic Resonance Imaging for Prostate Biopsy Decision Planning: A Retrospective Multi-institutional Study Using the Prostate Magnetic Resonance Imaging Outcome Database (PROMOD).

BACKGROUND: Previous studies suggested that prostate-specific antigen (PSA) density (PSAd) combined with magnetic resonance imaging (MRI) may help avoid unnecessary prostate biopsy (PB) with a limited risk of missing clinically significant prostate cancer (csPCa; Gleason grade group [GGG] >1). OBJECTIVE: To define optimal diagnostic strategies based on the combined use of PSAd and MRI in patients at risk of prostate cancer (PCa). DESIGN, SETTING, AND PARTICIPANTS: A retrospective analysis of the international multicenter Prostate MRI Outcome Database (PROMOD), including 2512 men having undergone PSAd and prostate MRI before PB between 2013 and 2019, was performed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Rates of avoided PB, missed GGG 1, and csPCa according to 10 strategies based on PSAd values and MRI reporting scores (Prostate Imaging Reporting and Data System [PI-RADS]/Likert/IMPROD biparametric prostate MRI Likert). Decision curve analysis (DCA) was used to statistically compare the net benefit of each strategy. Combined systematic and targeted biopsies were used for reference. RESULTS AND LIMITATIONS: According to DCA, the best strategy in biopsy-naive patients was #7 (PI-RADS/Likert 4-5 or PI-RADS/Likert 3 if PSAd >0.2), which avoided 41.2% PBs while missed 44% of GGG 1 and 10.9% of csPCa cases. From a clinical standpoint, however, strategies with a lower risk of missing csPCa included #10 (PI-RADS/Likert 4-5 or PI-RADS 3 if PSAd >0.10 or PSAd >0.2), which avoided 27% PBs while missing 24.4% GGG 1 and 4% csPCa cases, or #5 (PI-RADS/Likert 3-5 or PSAd>0.15), which avoided 14.7% PBs while missing 9.3% GGG 1 and 1.7% csPCa cases. Similar results were found in patients with a previous negative biopsy. This study is limited by its retrospective nature, and no central review of MRI and histopathological findings. CONCLUSIONS: Combined PSAd and MRI findings allows individualization of the decision to perform PB on the basis of the risk of missing PCa that both patients and clinicians are ready to accept to avoid this procedure. PATIENT SUMMARY: We compared several biopsy strategies based on a combination of prostate magnetic resonance imaging findings and prostate-specific antigen density, providing a readily available tool for each center and practicing urologist to counsel patients about their individual risk of significant prostate cancer.