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.

Downgrading of Grade Group After Radical Prostatectomy: Comparison of Multiparametric Magnetic Resonance Imaging Guided Fusion Biopsy and Standard 12-Core Biopsy.

OBJECTIVE: To analyze the factors associated with Grade group (GG) downgrading post-radical prostatectomy. PATIENTS AND METHODS: We performed a retrospective analysis of 536 patients who underwent robot-assisted laparoscopic radical prostatectomy from February 2014 to October 2015. We have analyzed the clinical, radiological, and pathologic factors associated with GG downgrading in final pathology. Downgrading was defined as those patients who downgraded from GG 3, 4, or 5 on biopsy to GG 1 or 2 on final pathology as well as patients who downgraded from GG 2 on biopsy to GG 1 on final pathology. Categorical values were compared with chi-square and Fischer's exact tests. Mann-Whitney U and Kruskal-Wallis were used for analysis of independent variables associated with GG downgrading. RESULTS: Ninety-three patients underwent fusion biopsy (FB) and 443 underwent the standard 12 core biopsy. Baseline clinical characteristics were similar between the 2 groups except for race (P = .009). Downgrading was observed in 76 patients (14.1%). Rate of downgrading was higher in the FB group (n = 22, 23.7% vs n = 54, 12.2%, P = .008). In multivariable logistic regression analysis, FB (OR:2.39, P = .004) and maximum percentage of core involvement (OR:1.01, P = .013) were associated with downgrading after robot-assisted laparoscopic radical prostatectomy. After 1:2 propensity score matching, FB was still associated with an increased rate of downgrading (P = .034). Downgrading had no significant effect on pathologic outcome. CONCLUSION: FB and maximum percentage of core involvement are the only factors associated with GG downgrading in final pathology. However, downgrading did not influence surgical outcome.

Defining Prostate Cancer at Favorable Intermediate Risk: The Potential Utility of Magnetic Resonance Imaging and Genomic Tests.

PURPOSE: We determined whether prostate multiparametric magnetic resonance imaging and genomic biomarkers might help further define patients with favorable intermediate risk prostate cancer which could safely be considered suitable for active surveillance. MATERIALS AND METHODS: From our institutional database we identified 509 patients who underwent radical prostatectomy with preoperative magnetic resonance imaging and a postoperative Decipher® prostate cancer test. According to the NCCN® (National Comprehensive Cancer Network®) risk stratification 125 men had favorable intermediate and 171 had unfavorable intermediate risk disease. Univariable and multivariable binary logistic regression analyses were done to test the utility of different variables in predicting adverse pathology, defined as Gleason Grade Group greater than 2, pT3b or pN1. RESULTS: On univariable analysis favorable intermediate risk, multiparametric magnetic resonance imaging and the prostate cancer test significantly predicted adverse pathology. On multivariable analysis favorable intermediate risk and the prostate cancer test maintained independent predictive value while multiparametric magnetic resonance imaging did not meet statistical significance (p = 0.059). The 19 patients at favorable intermediate risk with high genomic risk had an adverse pathology rate slightly higher than patients at unfavorable intermediate risk (42.1% vs 39.8%, p = 0.56). Those at low genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (7.5% vs 10.2%, p = 0.84). The 31 patients at favorable intermediate risk but at high multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at unfavorable intermediate risk (25.8% vs 39.8%, p = 0.14). Those at low multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (8.5% vs 10.2%, p = 0.89). CONCLUSIONS: Multiparametric magnetic resonance imaging and the Decipher test allowed us to better define the risk of adverse pathology in patients at favorable intermediate risk who were diagnosed with prostate cancer.

Multiparametric Magnetic Resonance Imaging Features Identify Aggressive Prostate Cancer at the Phenotypic and Transcriptomic Level.

PURPOSE: Multiparametric magnetic resonance imaging is a diagnostic tool for prostate cancer with limited data on prognostic use. We sought to determine whether multiparametric magnetic resonance could predict aggressive prostate cancer features. MATERIALS AND METHODS: We retrospectively analyzed the records of 206 patients who underwent radical prostatectomy between 2013 and 2017. All patients had available RNA expression data on the final pathology specimen obtained from a location corresponding to a lesion location on multiparametric magnetic resonance imaging. The association between the PIRADS™ (Prostate Imaging Reporting and Data System) score and adverse pathology features were analyzed. We also performed differential transcriptomic analysis between the PIRADS groups. Factors associated with adverse pathology were analyzed using a multivariable logistic regression model. RESULTS: Lesion size (p = 0.03), PIRADS score (p = 0.02) and extraprostatic extension (p = 0.01) associated significantly with the Decipher® score. Multivariable analysis showed that the PIRADS score (referent PIRADS 3, OR 8.1, 95% CI 1.2-57.5, p = 0.04), the Gleason Grade Group (referent 3, OR 5.6, 95% CI 1.5-21.1, p = 0.01) and prostate specific antigen (OR 1.103, 95% CI 1.011-1.203) were risk factors for adverse pathology findings. The difference between PIRADS 4 and 5 did not reach significance (OR 1.9, 95% CI 0.8-4.5, p = 0.12). However, the PI3K-AKT-mTOR, WNT-ß and E2F signaling pathways were more active in PIRADS 5 than in PIRADS 4 cases. CONCLUSIONS: The PIRADS score is associated with adverse pathology results, increased metastatic risk and differential genomic pathway activation.