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.

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.

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.

Unified model involving genomics, magnetic resonance imaging and prostate-specific antigen density outperforms individual co-variables at predicting biopsy upgrading in patients on active surveillance for low risk prostate cancer.

BACKGROUND: Active surveillance (AS) is the reference standard treatment for the management of low risk prostate cancer (PCa). Accurate assessment of tumor aggressiveness guides recruitment to AS programs to avoid conservative treatment of intermediate and higher risk patients. Nevertheless, underestimating the disease risk may occur in some patients recruited, with biopsy upgrading and the concomitant potential for delayed treatment. AIM: To evaluate the accuracy of mpMRI and GPS for the prediction of biopsy upgrading during active surveillance (AS) management of prostate cancer (PCa). METHOD: A retrospective analysis was performed on 144 patients recruited to AS from October 2013 to December 2020. Median follow was 4.8 (IQR 3.6, 6.3) years. Upgrading was defined as upgrading to biopsy grade group ≥2 on follow up biopsies. Cox proportional hazard regression was used to investigate the effect of PSA density (PSAD), baseline Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 score and GPS on upgrading. Time-to-event outcome, defined as upgrading, was estimated using the Kaplan-Meier method with log-rank test. RESULTS: Overall rate of upgrading was 31.9% (n = 46). PSAD was higher in the patients who were upgraded (0.12 vs. 0.08 ng/ml2 , p = .005), while no significant difference was present for median GPS in the overall cohort (overall median GPS 21; 22 upgrading vs. 20 no upgrading, p = .2044). On univariable cox proportional hazard regression analysis, the factors associated with increased risk of biopsy upgrading were PSA (HR = 1.30, CI 1.16-1.47, p = <.0001), PSAD (HR = 1.08, CI 1.05-1.12, p = <.0001) and higher PI-RADS score (HR = 3.51, CI 1.56-7.91, p = .0024). On multivariable cox proportional hazard regression analysis, only PSAD (HR = 1.10, CI 1.06-1.14, p = <.001) and high PI-RADS score (HR = 4.11, CI 1.79-9.44, p = .0009) were associated with upgrading. A cox regression model combining these three clinical features (PSAD ≥0.15 ng/ml2 at baseline, PI-RADS Score and GPS) yielded a concordance index of 0.71 for the prediction of upgrading. CONCLUSION: In this study PSAD has higher accuracy over baseline PI-RADS score and GPS score for the prediction of PCa upgrading during AS. However, combined use of PSAD, GPS and PI-RADS Score yielded the highest predictive ability with a concordance index of 0.71.

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.

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.

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.

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.

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.

Performance of prostate multiparametric MRI for prediction of prostate cancer extra-prostatic extension according to NCCN risk categories: implication for surgical planning.

BACKGROUND: Prediction of extra-prostatic extension (EPE) in men undergoing radical prostatectomy (RP) is of utmost importance. Great variability in the performance of multiparametric magnetic resonance imaging (mpMRI) has been reported for prediction of EPE. The present study aimed to determine the diagnostic performance of mpMRI for predicting EPE in different National Comprehensive Cancer Network (NCCN) risk categories. METHODS: Overall 664 patients who underwent radical prostatectomy with a staging mpMRI were enrolled in this single-center, retrospective study. Patients with mpMRI report non-compliant with PI-RADSv2.0, were excluded. Patients were stratified according to NCCN criteria: very low/low (VLR-LR) to High Risk (HR) in order to assess final pathology EPE rates (focal and established). Sensitivity, specificity, positive and negative predictive values of staging mpMRI were computed in each group. Univariable and multivariable analysis were used to evaluate predictors of positive surgical margins. RESULTS: Pathological evaluation demonstrated established and focal EPE in 60 (9%) and 106 (16%) patients, respectively, while mpMRI suspicion for EPE was present in 180 (27%) patients. Age, preoperative PSA, PSA density, number of positive cores, NCCN groups, prostate volume, mpMRI suspicion for EPE, PIRADSv2.0 and lesion size differed significantly between the patients with any EPE and without EPE (all P≤0.05). The sensitivity of mpMRI in detecting any EPE varied from 12% (95% CI: 0.6-53%) in VLR-LR to 83% (66-93%) in HR while the corresponding values for the specificity were 92% (85-96%) and 63% (45-78%), respectively. Patients with false-negative mpMRI EPE prediction were more likely to have positive surgical margins in univariable (OR: 2.14; CI: 1.18, 3.87) as well as multivariable analysis adjusting for NCCN risk categories (OR: 1.97; CI: 1.08, 3.60). CONCLUSIONS: The performance of mpMRI for prediction of EPE varies greatly between different NCCN risk categories with a low positive predicting value in patients at low to favorable intermediate risk and a low negative predictive value in patients at Unfavorable intermediate to high risk PCa. Given that mpMRI EPE misdiagnosis could have a negative impact on oncological and functional outcomes, NCCN risk categories should be considered when interpreting mpMRI findings in PCa patients.

Avoiding Unnecessary Magnetic Resonance Imaging (MRI) and Biopsies: Negative and Positive Predictive Value of MRI According to Prostate-specific Antigen Density, 4Kscore and Risk Calculators.

The 2019 European Association of Urology guidelines recommend multiparametric magnetic resonance imaging (mpMRI) for biopsy-naïve patients with clinical suspicion of prostate cancer (PC) and avoiding biopsy in patients with negative mpMRI and low clinical suspicion. However, consensus on the optimal definition of low clinical suspicion is lacking. We evaluated 266 biopsy-naïve patients who underwent mpMRI, the 4Kscore test, and prostate biopsy to define the best strategy to avoid unnecessary testing and biopsies. The European Randomized Study of Screening for Prostate Cancer risk calculator (ERSPC-RC) and prostate-specific antigen density (PSAd) were also considered. For men with Prostate Imaging-Reporting and Data System v2.0 (PI-RADS) 1â¿¿2 lesions, the highest negative predictive value was observed for those with low or intermediate 4Kscore risk (96.9% and 97.1%), PSAd <0.10ng/ml/cm3 (98.7%), and ERSPC-RC <2% (98.7%). For men with PI-RADS 3â¿¿5 lesions the lowest positive predictive value was observed for those with low 4Kscore risk (0%), PSAd <0.10ng/ml/cm3 (13.2%), and ERSPC-RC <2% (12.3%). The best biopsy strategy was an initial 4Kscore followed by mpMRI if the 4Kscore was>7.5% and a subsequent biopsy if the mpMRI was positive (PI-RADS 3â¿¿5) or the 4Kscore was â¿¥18%. This would result in missing 2.7% (2/74) of clinically significant PCs (csPCs) and avoiding 34.2% of biopsies. Initial mpMRI followed by biopsy for negative mpMRI (PI-RADS 1â¿¿2) if the 4Kscore was â¿¥18% or PSAd was â¿¥0.10ng/ml/cm3 resulted in a similar percentage of csPC missed (2.7% [2/74] and 1.3% [1/74]) but slightly fewer biopsies avoided (25.2% and 28.1%). Physicians should consider clinical risk screening tools when ordering and interpreting mpMRI results to avoid unnecessary testing and diagnostic errors. PATIENT SUMMARY: Performing the 4Kscore test in conjunction with multiparametric magnetic resonance imaging for men with a clinical suspicion of prostate cancer may help to reduce unnecessary biopsies.

Weighted Gleason Grade Group (WGGG): A new prostate cancer biopsy reporting system with prognostic potential.

INTRODUCTION: Presently, prostate biopsy (PBx) results report the highest Gleason Grade Group (GGG) as a single metric that gauges the overall clinical aggressiveness of cancer and dictates treatment. We hypothesized a PBx showing multiple cores of cancer with more volume cancer per core would represent more aggressive disease. We propose the Weighted Gleason Grade Group (WGGG), a novel scoring system that synthesizes all histopathologic data and cancer volume into a single numeric value representing the entire PBx, allowing for improved prediction of adverse pathology and risk of biochemical recurrence (BCR) following radical prostatectomy (RP). METHODS: We studied 171 men who underwent RP after standard PBx. The WGGG was calculated by summing each positive core using the formula: GGG + (GGG x %Ca/core). RP pathology was evaluated for extraprostatic extension (EPE), positive surgical margins (PSM), seminal vesicle invasion (SVI), and lymph node involvement (LNI), and patients were followed for BCR. We compared GGG vs. WGGG receiver operating characteristic curves for each outcome, and determined the predictive capability of GGG and WGGG to identify patients with BCR. Categorized WGGG groups were created based on risk of BCR using classification and regression tree analysis. We then sought to externally validate WGGG in a cohort of 389 patients in a separate institutional dataset. RESULTS: In the development cohort, area under the curves (AUCs) for the WGGG vs. GGG were significantly higher for predicting EPE (0.784 vs. 0.690, P = 0.002), SVI (AUC 0.823 vs. 0.721, P = .014), LNI (AUC 0.862 vs. 0.823, P = 0.039), and PSM (AUC 0.638 vs. 0.575, P = 0.031. Analysis of the validation cohort showed similar findings for EPE (AUC 0.764 vs. 0.729, P = 0.13), SVI (AUC 0.819 vs. 0.749, P = 0.01), LNI (AUC 0.939 vs. 0.867, P = 0.02), and PSM (AUC 0.624 vs. 0.547, P = 0.04). Patients with WGGG >30 (high-risk group) demonstrated ∼50% failure at 2 years in both cohorts. CONCLUSIONS: The WGGG, by providing a metric reflecting the entirety of the PBx, is more informative than conventional single GGG alone in identifying adverse pathologic outcomes and risk of BCR following RP. This superior discriminatory capability has been achieved without any consideration of other commonly available clinical disease characteristics.

Clinical implications of prostatic capsular abutment or bulging on multiparametric magnetic resonance imaging.

BACKGROUND: The presence of capsular abutment or bulging can raise concern when planning surgery. In this study we aimed to test the clinical implications of capsular abutment or bulging on preoperative multiparametric magnetic resonance imaging (mpMRI). METHODS: We analyzed the data of 291 patients who underwent radical prostatectomy (RP) for a cT1-2N0 prostate cancer in a single surgeon series. All patients underwent preoperative staging with mpMRI. PIRADS v2 was used for characterizing lesions. The role of capsular abutment or bulging was tested in a multivariable logistic regression adjusting for prostate-specific antigen and highest ipsilateral biopsy Gleason grade. The presence of focal versus extensive extracapsular extension (ECE) was investigated. RESULTS: Overall, ECE on final pathology was documented in 35 (12%) cases and ECE was focal in 32 (91%) patients. Overall, mpMRI demonstrated capsule bulging or abutment in 12 (24%) cases. After adjusting for confounders, capsule bulging or abutment on mpMRI emerged as predictor for ECE (OR=6.70; 95% CI: 2.97-15.12, P<0.001). The sensitivity and specificity of capsule abutment or bulging in predicting ECE were 43% and 95%, respectively. Sensitivity and specificity were 36% and 48% respectively to predict focal ECE. CONCLUSIONS: The PIRADS v2 scoring system has a grey zone concerning ECE as defined by capsule abutment or bulging. We found an increased risk of ECE and specifically focal ECE when capsule bulging or abutment on mpMRI are documented.

Predicting Survival of Small Intestine Neuroendocrine Tumors: Experience From a Major Referral Center.

OBJECTIVE: Neuroendocrine tumors (NETs) comprise 41.8% of small intestine malignancies. The NET nomogram is a 15-item prognostic tool that includes relevant factors for guiding management decisions. This is the first external validation of this tool among American patients at a tertiary treatment center. METHODS: Patients who underwent surgical intervention from 2005 to 2017 were screened by retrospective chart review. Nomogram scores were calculated following the methods outlined by Modlin et al (Neuroendocrinology. 2010;92:143-157). Validation assessed the association between nomogram scores and survival using Wilcoxon test and Cox regression. RESULTS: Among the 121 patients selected, the NET nomogram significantly predicted survival as a continuous variable (P < 0.01) and when dichotomized using 83 points to distinguish low-risk versus high-risk groups (P < 0.01). However, the nomogram was not universally applicable as even at our specialty center, variables such as chromogranin A and urinary 5-hydroxyindoleacetic acid are not routinely collected, whereas others, like tumor grade, do not reflect the most recently updated classifications. CONCLUSION: The NET nomogram accurately identified patients at low and high risk of death. However, revision to update prognosticators could improve its usefulness for predicting survival of small intestine NETs.

A transcriptomic signature of tertiary Gleason 5 predicts worse clinicopathological outcome.

OBJECTIVE: To investigate the genomic features of tertiary pattern 5 (TP5) on radical prostatectomy specimens in an effort to explain the poor clinical outcomes associated with this disease subtype. PATIENTS AND METHODS: Data from 159 men with Gleason Grade Group (GGG) 3 or 4 were considered. All patients had Decipher diagnostic testing with transcript profiles and single-channel array normalisation (SCAN)-normalised expression of coding genes. The relationship between Decipher and TP5 was investigated by linear and binary logistic regressions. A differential transcriptomic analysis between patients with and without TP5 was performed. The prognostic role of these genes on progression-free survival (PFS) and overall survival (OS) was evaluated using The Cancer Genome Atlas. RESULTS: In all, 52/159 (33%) patients had GGG 3-4 with TP5 disease. TP5 was associated with a higher Decipher score (ß 0.07, 95% confidence interval [CI] 0.02-0.13; P = 0.04) and higher likelihood of falling within the intermediate- or high-risk categories (odds ratio 3.34, 95% CI 1.34-8.35; P = 0.01). Analysis of microarray data revealed an 18-gene signature that was differentially expressed in patients with TP5; 13 genes were over- and five under-expressed in the TP5 cohort. The overexpression of cyclin dependent kinase inhibitor 2B (CDKN2B), polo-like kinase 1 (PLK1), or cell division cycle 20 (CDC20) was associated with worse PFS. The group harbouring overexpression of at least one gene had a 5-year PFS rate of 50% vs 74% in the group without overexpression (P < 0.001). CONCLUSIONS: Our studies have elucidated unique genomic features of TP5, whilst confirming previous clinical findings that patients harbouring TP5 tend to have worse prognosis. This is the first RNA-based study to investigate the molecular diversity of TP5 and the first correlating CDKN2B to poorer prognosis in patients with prostate cancer.

Novel nomogram for the prediction of seminal vesicle invasion including multiparametric magnetic resonance imaging.

OBJECTIVES: To create a model that predicts side-specific seminal vesicle invasion using clinical, biopsy and multiparametric magnetic resonance imaging data. METHODS: We analyzed data from 544 patients who underwent robot-assisted radical prostatectomy at a single institution. To develop a side-specific predictive model, we ultimately considered four variables: prostate-specific antigen, highest ipsilateral biopsy Gleason grade, highest ipsilateral percentage core involvement and seminal vesicle invasion on multiparametric magnetic resonance imaging. A binary multivariable logistic regression model was fitted to predict seminal vesicle invasion. A nomogram was then built based on the coefficients of the resulting logit function. The leave-one-out cross validation method was used for internal validation, and the decision curve analysis for the evaluation of the net clinical benefit. RESULTS: We relied on 804 side-specific cases after excluding negative biopsy observations (n = 284). Seminal vesicle invasion was reported on multiparametric magnetic resonance imaging in 41 (5%) cases, and on final pathology in 64 (8%) cases. All variables in the model emerged as predictors of seminal vesicle invasion (all P ≤ 0.001) and were subsequently considered to build a nomogram. The area under the curve of multiparametric magnetic resonance imaging alone in predicting seminal vesicle invasion was 59.1%; whereas one of the clinical variables only was 85.1%. The area under the curve of the nomogram resulting from their combination was 86.5%. After internal validation, this resulted in 84.7%. The model achieved good calibration and the decision curve analysis showed its clinical benefit, especially when compared with relying only on multiparametric magnetic resonance imaging prediction of seminal vesicle invasion. CONCLUSIONS: A nomogram based on clinical and multiparametric magnetic resonance imaging data can predict seminal vesicle invasion and serve as a tool to urologists for surgical planning.

An updated approach to incremental nerve sparing for robot-assisted radical prostatectomy.

OBJECTIVES: To update the algorithm for performing incremental nerve sparing (NS) using our multiparametric magnetic resonance imaging (mpMRI)-based nomogram. PATIENTS AND METHODS: We applied the coefficients of the nomogram to the observations extracted from our population of patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015 and who received preoperative mpMRI. The information considered were PSA level, highest side-specific biopsy Gleason grade group, highest ipsilateral percentage core involvement with the highest Gleason grade group, and extracapsular extension (ECE) on mpMRI. The nomogram-derived probability [P (%)], after internal validation, was used as the independent variable on a classification tree to identify the most significant thresholds for ECE prediction. Incremental NS was performed as follows: Grade 1 NS: intrafascial dissection between the peri-prostatic veins and the pseudocapsule of the prostate; Grade 2 NS: inter-fascial dissection along the peri-venous plane; Grade 3 NS: inter-fascial dissection through the outer compartment of the lateral prostatic fascia; Grade 4 NS: extrafascial dissection. RESULTS: Data from 561 patients were considered, and 829 prostatic lobes with biopsy-documented tumour were analysed. Overall, 142 lobes presented ECE that was focal in 27 (19%) cases. The classification tree identified four risk categories. In the low- [P (%) ≤10], intermediate- [P (%) 10-21], high [P (%) 21-73] and very-high-risk [P(%) >73] groups, the ECE rates were 3.3%, 16%, 61.6% and 90%, respectively. Amongst those, ECE was focal in 41.7%, 31.7%, 7.9% and 0%, respectively. CONCLUSION: We suggest that Grade 1 NS (intrafascial) should be performed in the low-risk group. The inter-fascial approach, namely grades 2 and 3 NS, should be performed in the intermediate- and high-risk categories, respectively. Grade 4 NS (extrafascial) should be performed in the very-high-risk group. The current algorithm yields a better accuracy than the previous one; however, prospective validation is warranted.