Risk factors for Gleason score upgrade from prostate biopsy to radical prostatectomy.

Accurate identification of prostate cancer Gleason grade group remains an important component of the initial management of clinically localized disease. However, Gleason score upgrading (GSU) from biopsy to radical prostatectomy can occur in up to a third of patients treated with surgery. Concern for disease undergrading remains a source of diagnostic uncertainty, contributing to both over-treatment of low-risk disease as well as under-treatment of higher-risk prostate cancer. This review examines the published literature concerning risk factors for GSU from time of biopsy to prostatectomy final pathology. Risk factors identified for Gleason upgrading include patient demographic and clinical factors including age, body mass index, race, prostate volume, and biomarker based assays, including prostate-specific antigen (PSA) density, and testosterone values. In addition, prostate magnetic resonance imaging (MRI) findings have also been associated with GSU. Biopsy-specific characteristics associated with GSU include lower number of biopsy cores and lack of targeted methodology, and possibly increasing percent biopsy core positivity. Recognition of risk factors for disease undergrading may prompt confirmatory testing including repeat sampling or imaging. Continued refinements in imaging guided biopsy techniques may also reduce sampling error contributing to undergrading.

Association Between the Decipher Genomic Classifier and Prostate Cancer Outcome in the Real-world Setting.

BACKGROUND AND OBJECTIVE: Although the prognostic significance of the Decipher prostate cancer genomic classifier (GC) has been established largely from analyses of archival tissue, less is known about the associations between the results of Decipher testing and oncologic outcomes among patients receiving contemporaneous testing and treatment in the real-world practice setting. Our objective was to assess the associations between the Decipher GC and risks of metastasis and biochemical recurrence (BCR) following prostate biopsy and radical prostatectomy (RP) among patients tested and treated in the real-world setting. METHODS: A retrospective cohort study was conducted using a novel longitudinal linkage of transcriptomic data from the Decipher GC and real-world clinical data (RWD) aggregated from insurance claims, pharmacy records, and electronic health record data across payors and sites of care. Kaplan-Meier and Cox proportional hazards regressions were used to examine the associations between the GC and study outcomes, adjusting for clinical and pathologic factors. KEY FINDINGS AND LIMITATIONS: Metastasis from prostate cancer and BCR after radical prostatectomy, Decipher GC continuous score, and risk categories were evaluated. We identified 58 935 participants who underwent Decipher testing, including 33 379 on a biopsy specimen and 25 556 on an RP specimen. The median age was 67 yr (interquartile range [IQR] 62-72) at biopsy testing and 65 yr (IQR 59-69) at RP. The median GC score was 0.43 (IQR 0.27-0.66) among biopsy-tested patients and 0.54 (0.32-0.79) among RP-tested patients. The GC was independently associated with the risk of metastasis among biopsy-tested (hazard ratio [HR] per 0.1 unit increase in GC 1.21 [95% confidence interval {CI} 1.16-1.27], p < 0.001) and RP-tested (HR 1.20 [95% CI 1.17-1.24], p < 0.001) patients after adjusting for baseline clinical and pathologic risk factors. In addition, the GC was associated with the risk of BCR among RP-tested patients (HR 1.12 [95% CI 1.10-1.14], p < 0.001) in models adjusted for age and Cancer of the Prostate Risk Assessment postsurgical score. CONCLUSIONS AND CLINICAL IMPLICATIONS: This real-world study of a novel transcriptomic linkage conducted at a national scale supports the external prognostic validity of the Decipher GC among patients managed in contemporary practice. PATIENT SUMMARY: This study looked at the use of the Decipher genomic classifier, a test used to help understand the aggressiveness of a patient's prostate cancer. Looking at the results of 58 935 participants who underwent testing, we found that the Decipher test helped estimate the risk of cancer recurrence and metastasis.

Associations Between Prostate Magnetic Resonance Imaging, Genomic Testing, and Treatment for Localized Prostate Cancer.

INTRODUCTION: Although prostate MRI and tissue-based gene expression (genomic) tests improve staging and estimates of prostate cancer prognosis, their association with the intensity of treatment patients receive is not well understood. METHODS: We performed a retrospective cohort study of Medicare beneficiaries diagnosed with clinically localized prostate cancer in 2013 through 2017 in the Surveillance, Epidemiology, and End Results database. The primary study outcome was the receipt of treatment intensification in the first 12 months after diagnosis (defined as the addition of androgen deprivation therapy among patients receiving radiation or pelvic lymphadenectomy among those undergoing radical prostatectomy). We assessed associations between the receipt of prostate MRI and genomic testing and treatment intensification, adjusting for clinical and sociodemographic factors and further stratifying the analyses by risk status. RESULTS: We identified 37,064 patients with clinically localized prostate cancer, including 6,398, 22,011, and 5976 with low, intermediate, and high D'Amico-risk disease, respectively. Among all treated patients, receipt of prostate MRI was associated with increased odds of treatment intensification (odds ratio 1.76, 95% CI 1.65-1.88, P < .001). In contrast, genomic testing was not significantly associated. Among treated patients with high-risk disease, genomic testing was associated with decreased odds of intensified treatment (odds ratio 0.59, 95% CI 0.35-1.00, P = .05). CONCLUSIONS: Prostate MRI was associated with intensified treatment across risk strata, while genomic testing was associated with lower intensity of treatment among high-risk disease. Additional study is needed to determine whether use of imaging and risk stratification tools leads to improved long-term patient outcomes.

Prostate-specific antigen screening for prostate cancer: Diagnostic performance, clinical thresholds, and strategies for refinement.

Prostate specific antigen (PSA) has transformed the diagnosis and treatment of prostate cancer by enabling early detection at global scale. Due to expression in both benign and malignant cells, PSA-based prostate cancer screening using single cut-points yields imperfect diagnostic performance and has led to the detection and over-treatment of low-grade prostate cancer. Additional challenges in the interpretation of PSA include substantial inter and intrapersonal variation, differences with age and prostate volume, and selection of standardized PSA value cutoffs for clinical application. In response, refinements to PSA including risk and age-based thresholds, age and genetic adjustments, PSA density, percentage free PSA, and PSA velocity have been proposed and extensively studied. In this review, we focus on the clinical role of PSA as a screening biomarker with a particular emphasis on its test characteristics, clinically actionable thresholds, and strategies to refine its clinical interpretation.

Association of Crowd-Sourced Assessment of Technical Skills and Outcomes of Robotic-assisted Radical Prostatectomy.

OBJECTIVE: To investigate if use of the Crowd-Sourced Assessment of Technical Skills (CSATS) platform and video peer review with constructive feedback is associated with improvement in technical skill and patient outcomes for robotic-assisted laparoscopic prostatectomy (RALP). METHODS: Five fellowship-trained urologists voluntarily submitted RALP cases for CSATS Global Evaluative Assessment of Robotic Skills (GEARS) scoring and expert narrative review between April 15, 2022-April 30, 2023. Surgeon-selected and randomly selected cases were reviewed. Surgeons underwent local peer review of videos with constructive feedback. Change in GEARS scores and frequency of postoperative outcomes over the 12-month periods before and during the study were analyzed in logistic regression models. Bias was assessed with sensitivity analysis comparing surgeon-selected to randomly selected cases. RESULTS: GEARS scores for randomly selected vs surgeon-selected cases did not differ significantly. Overall GEARS score correlated positively with annual surgical RALP volume (r = 0.39, P = .003) and negatively with years in practice (r = -0.34, P = .01). After adjusting for confounders, there was no significant improvement in overall GEARS Score (0.01 ± 0.02/month, P = .48); but likelihood of sepsis (Odds Ratio 0.07, 95% CI 0.01-1.00, P = .05) and pelvic fluid collection (Odds Ratio 0.09, 95% CI 0.01-0.99, P = .049) were significantly decreased during the intervention period (n = 165) compared to the prior 12months (n = 144). No outcome increased in likelihood (P > .05). CONCLUSION: Integration of CSATS and local video peer review is associated with significant improvement in patient outcomes after RALP, despite no significant change in surgeons' GEARS scores. This is the first study demonstrating improvement in patient RALP outcomes after implementation of such a paradigm in practicing surgeons.

Association between pelvic lymph node dissection and survival among patients with prostate cancer treated with radical prostatectomy.

Introduction: Although the clinical benefits of pelvic lymph node dissection (PLND) at the time of radical prostatectomy for prostate cancer remain uncertain, major guidelines recommend PLND based on risk profile. Thus, the objective of this study was to examine the association between PLND and survival among patients undergoing RP stratified by Gleason grade group (GG) with the aim of allowing patients and physicians to make more informed care decisions about the potential risks and benefits of PLND. Materials and methods: From the SEER-17 database, we examined overall (OS) and prostate cancer-specific (PCSS) survival of prostate cancer patients who underwent RP from 2010 to 2015 stratified by GG. We applied propensity score matching to balance pre-operative characteristics including race, age, PSA, household income, and housing status (urban/rural) between patients who did and did not undergo PLND for each GG. Statistical analyses included log-rank test and Kaplan-Meier curves. Results: We extracted a matched cohort from 80,287 patients with GG1-5 who underwent RP. The median PSA value was 6.0 ng/mL, and the median age was 62-years-old. 49,453 patients underwent PLND (61.60%), while 30,834 (38.40%) did not. There was no difference in OS and PCSS between patients who received PLND and those who did not for all Gleason GG (OS-GG1: P = 0.20, GG2: P = 0.34, GG3: P > 0.05, GG4: P = 0.55, GG5: P = 0.47; PCSS-GG1: P = 0.11, GG2: P = 0.96, GG3: P = 0.81, GG4: P = 0.22, GG5: P = 0.14). Conclusions: In this observational study, PLND at the time of RP was not associated with improved OS or PCSS among patients with cGS of 3 + 3, 3 + 4, 4 + 3, 4 + 4, 4 + 5, and 5 + 4. These findings suggest that until definitive clinical trials are completed, prostate cancer patients who have elected RP should be appropriately counseled on the potential risks and lack of proven survival benefit of PLND.

Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage.

Importance: Although tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood. Objective: To develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US. Design, Setting, and Participants: In this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024. Exposure: Diagnosis of prostate cancer. Main Outcomes and Measures: The primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard. Results: A total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy. Conclusions and Relevance: This study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Risk Factors and Contemporary Management Options for Pain and Discomfort Experienced During a Prostate Biopsy.

PURPOSE OF REVIEW: Prostate fusion biopsy, an innovative imaging modality for diagnosing prostate cancer, presents certain challenges for patients including discomfort and emotional distress, leading to nonadherence to treatment and follow-ups. To inform clinicians and offer pain relief alternatives to patients, this review delves into the risk factors for increased pain and modern management options to alleviate pain during prostate biopsy. RECENT FINDINGS: Individual responses to pain vary, and the overall experience of pain during a prostate biopsy has been contributed to numerous factors such as patient age, prostate volume, previous biopsy experience, and more. As a result, several strategies aim to mitigate pain during in-office procedures. Notably, techniques including pharmacological analgesics, hand holding, heating pads, entertainment/virtual reality, and distraction have shown significant efficacy. Existing studies explore risk factors influencing pain intensity during prostate biopsy and effective pain management strategies. This review consolidates available information to guide clinicians in enhancing patient comfort and thus, encourage surveillance adherence.

Reliable Prostate Cancer Risk Mapping From MRI Using Targeted and Systematic Core Needle Biopsy Histopathology.

OBJECTIVE: To compute a dense prostate cancer risk map for the individual patient post-biopsy from magnetic resonance imaging (MRI) and to provide a more reliable evaluation of its fitness in prostate regions that were not identified as suspicious for cancer by a human-reader in pre- and intra-biopsy imaging analysis. METHODS: Low-level pre-biopsy MRI biomarkers from targeted and non-targeted biopsy locations were extracted and statistically tested for representativeness against biomarkers from non-biopsied prostate regions. A probabilistic machine learning classifier was optimized to map biomarkers to their core-level pathology, followed by extrapolation of pathology scores to non-biopsied prostate regions. Goodness-of-fit was assessed at targeted and non-targeted biopsy locations for the post-biopsy individual patient. RESULTS: Our experiments showed high predictability of imaging biomarkers in differentiating histopathology scores in thousands of non-targeted core-biopsy locations (ROC-AUCs: 0.85-0.88), but also high variability between patients (Median ROC-AUC [IQR]: 0.81-0.89 [0.29-0.40]). CONCLUSION: The sparseness of prostate biopsy data makes the validation of a whole gland risk mapping a non-trivial task. Previous studies i) focused on targeted-biopsy locations although biopsy-specimens drawn from systematically scattered locations across the prostate constitute a more representative sample to non-biopsied regions, and ii) estimated prediction-power across predicted instances (e.g., biopsy specimens) with no patient distinction, which may lead to unreliable estimation of model fitness to the individual patient due to variation between patients in instance count, imaging characteristics, and pathologies. SIGNIFICANCE: This study proposes a personalized whole-gland prostate cancer risk mapping post-biopsy to allow clinicians to better stage and personalize focal therapy treatment plans.

Cytologic evaluation of upper urinary tract specimens: An institutional retrospective study using The Paris System for Reporting Urine Cytology second edition with histopathologic follow-up.

OBJECTIVE: Cytologic evaluation of the upper urinary tract (UUT) can be challenging due to instrumentation artefacts. This study retrospectively reviewed UUT specimens using The Paris System for Reporting Urinary Cytopathology, second edition (TPS 2.0), compared it with the original reporting system (ORS) and correlated it with histopathologic follow-up. METHODS: An institutional database was reviewed for the UUT biopsy/resection histopathologic specimens, and we included 52 UUT cytology specimens pertinent to these cases in the study. These specimens were blindly reviewed and reclassified using TPS 2.0. The correlation between TPS 2.0, ORS and histopathologic follow-up was assessed. RESULTS: The UUT cytology specimens corresponded to 21 (40.4%) high-grade urothelial carcinoma (HGUC), 27 (51.9%) low-grade urothelial carcinoma (LGUC) and 4 (7.7%) benign cases on follow-up. For HGGC cases, the associated TPS categories included unsatisfactory (n = 1, 4.8%), negative for HGUC (NHGUC; n = 3, 14.3%), atypical urothelial cells (AUC; n = 6, 28.6%), suspicious for HGUC (SHGUC; n = 3, 14.3%) and HGUC (n = 8, 38.1%), while ORS categorised the specimens as unsatisfactory (n = 1, 4.8%), negative for malignant cells (NFMC; n = 3, 14.3%), AUC (n = 5, 23.8%), low-grade urothelial carcinoma (LGUC; n = 0, 0%), SHGUC (n = 5, 23.8%) and HGUC (n = 7, 33.3%). The risks of high-grade malignancy among cytologic categories were similar between ORS and TPS (p > 0.05). The majority of LGUC were classified as AUC similarly by ORS and TPS (55.6% vs. 59.3%). CONCLUSIONS: Our study demonstrated comparable performance between TPS 2.0 and ORS for UUT cytology specimens. Cytological diagnosis of UUT specimens remains challenging, especially for LGUC.

Association between sociodemographic factors and diagnosis of lethal prostate cancer in early life.

OBJECTIVE: A subset of patients are diagnosed with lethal prostate cancer (CaP) early in life before prostate-specific antigen (PSA) screening is typically initiated. To identify opportunities for improved detection, we evaluated patient sociodemographic factors associated with advanced vs. localized (CaP) diagnosis across the age spectrum. METHODS: We conducted a retrospective cohort study using the National Cancer Database, identifying patients diagnosed with CaP from 2004 to 2020. We compared characteristics of patients diagnosed at the advanced (cN1 or M1) versus localized (cT1-4N0M0) stage. Using multivariable logistic regression, we evaluated the associations among patient clinical and sociodemographic factors and advanced diagnosis, stratifying patients by age as ≤55 (before screening is recommended for most patients), 56 to 65, 66 to 75, and ≥76 years. RESULTS: We identified 977,722 patients who met the inclusion criteria. The mean age at diagnosis was 65.3 years and 50,663 (5.1%) had advanced disease. Overall, uninsured (OR = 3.20, 95% CI 3.03-3.78) and Medicaid-insured (OR 2.58, 95% CI 2.48-2.69) vs. privately insured status was associated with higher odds of diagnosis with advanced disease and this effect was more pronounced for younger patients. Among patients ≤55 years, uninsured (OR 4.14, 95% CI 3.69-4.65) and Medicaid-insured (OR 3.39, 95% CI 3.10-3.72) vs. privately insured patients were associated with higher odds of advanced cancer at diagnosis. Similarly, residence in the lowest vs. highest income quartile was associated with increased odds of advanced CaP in patients ≤55 years (OR 1.15, 95% CI 1.02-1.30). Black vs. White race was associated with increased odds of advanced CaP at diagnosis later in life (OR 1.17, 95% CI 1.09-1.25); however, race was not significantly associated with advanced stage CaP in those ≤55 years (P = 0.635). CONCLUSIONS: Sociodemographic disparities in diagnosis at advanced stages of CaP were more pronounced in younger patients, particularly with respect to insurance status. These findings may support greater attention to differential use of early CaP screening based on patient health insurance.

Prostate cancer risk stratification using magnetic resonance imaging-ultrasound fusion vs systematic prostate biopsy.

BACKGROUND: Image-guided approaches improve the diagnostic yield of prostate biopsy and frequently modify estimates of clinical risk. To better understand the impact of magnetic resonance imaging-ultrasound fusion targeted biopsy (MRF-TB) on risk assessment, we compared the distribution of National Comprehensive Cancer Network (NCCN) risk groupings, as calculated from MRF-TB vs systematic biopsy alone. METHODS: We performed a retrospective analysis of 713 patients who underwent MRF-TB from January 2017 to July 2021. The primary study objective was to compare the distribution of National Comprehensive Cancer Network risk groupings obtained using MRF-TB (systematic + targeted) vs systematic biopsy. RESULTS: Systematic biopsy alone classified 10% of samples as very low risk and 18.7% of samples as low risk, while MRF-TB classified 10.5% of samples as very low risk and 16.1% of samples as low risk. Among patients with benign findings, low-risk disease, and favorable/intermediate-risk disease on systematic biopsy alone, 4.6% of biopsies were reclassified as high risk or very high risk on MRF-TB. Of 207 patients choosing active surveillance, 64 (31%), 91 (44%), 42 (20.2%), and 10 (4.8%) patients were classified as having very low-risk, low-risk, and favorable/intermediate-risk and unfavorable/intermediate-risk criteria, respectively. When using systematic biopsy alone, 204 patients (28.7%) were classified as having either very low-risk and low-risk disease per NCCN guidelines, while 190 men (26.6%) received this classification when using MRF-TB. CONCLUSION: The addition of MRF-TB to systematic biopsy may change eligibility for active surveillance in only a small proportion of patients with prostate cancer. Our findings support the need for routine use of quantitative risk assessment over risk groupings to promote more nuanced decision making for localized cancer.

NCCN Guidelines® Insights: Prostate Cancer Early Detection, Version 1.2023.

The NCCN Guidelines for Prostate Cancer Early Detection provide recommendations for individuals with a prostate who opt to participate in an early detection program after receiving the appropriate counseling on the pros and cons. These NCCN Guidelines Insights provide a summary of recent updates to the NCCN Guidelines with regard to the testing protocol, use of multiparametric MRI, and management of negative biopsy results to optimize the detection of clinically significant prostate cancer and minimize the detection of indolent disease.

Prediction of Adverse Pathology at Radical Prostatectomy in Grade Group 2 and 3 Prostate Biopsies Using Machine Learning.

PURPOSE: There is ongoing clinical need to improve estimates of disease outcome in prostate cancer. Machine learning (ML) approaches to pathologic diagnosis and prognosis are a promising and increasingly used strategy. In this study, we use an ML algorithm for prediction of adverse outcomes at radical prostatectomy (RP) using whole-slide images (WSIs) of prostate biopsies with Grade Group (GG) 2 or 3 disease. METHODS: We performed a retrospective review of prostate biopsies collected at our institution which had corresponding RP, GG 2 or 3 disease one or more cores, and no biopsies with higher than GG 3 disease. A hematoxylin and eosin-stained core needle biopsy from each site with GG 2 or 3 disease was scanned and used as the sole input for the algorithm. The ML pipeline had three phases: image preprocessing, feature extraction, and adverse outcome prediction. First, patches were extracted from each biopsy scan. Subsequently, the pre-trained Visual Geometry Group-16 convolutional neural network was used for feature extraction. A representative feature vector was then used as input to an Extreme Gradient Boosting classifier for predicting the binary adverse outcome. We subsequently assessed patient clinical risk using CAPRA score for comparison with the ML pipeline results. RESULTS: The data set included 361 WSIs from 107 patients (56 with adverse pathology at RP). The area under the receiver operating characteristic curves for the ML classification were 0.72 (95% CI, 0.62 to 0.81), 0.65 (95% CI, 0.53 to 0.79) and 0.89 (95% CI, 0.79 to 1.00) for the entire cohort, and GG 2 and GG 3 patients, respectively, similar to the performance of the CAPRA clinical risk assessment. CONCLUSION: We provide evidence for the potential of ML algorithms to use WSIs of needle core prostate biopsies to estimate clinically relevant prostate cancer outcomes.

Clinical utility of MR/ultrasound fusion-guided biopsy in patients with lower suspicion lesions on active surveillance for low-risk prostate cancer.

BACKGROUND: The utility of Multiparametric magnetic resonance imaging (mpMRI) guided prostate biopsy among patients with prostate cancer (CaP) managed with active surveillance (AS) with low-suspicion lesions remains unsettled. METHODS: We performed a retrospective analysis of 415 men with low-risk CaP managed with active surveillance. We selected men with mpMRI visible index lesions scored as 2 or 3 according to Prostate Imaging Reporting and Data System (PI-RADS) version 2. The primary outcome was detection of clinically significant prostate cancer (csCaP) was defined as Gleason grade group ≥ 2. We assessed the diagnostic accuracy of biopsy approaches using area under the receiver operator characteristic (ROC) curve and evaluated factors associated with csCaP in these patients using multivariate logistic regression. RESULTS: CsCaP was identified in 22 of 125 patients (17.6%) with PI-RADS 2 or 3 index lesions during surveillance prostate biopsies. These included 10 (45.5%) diagnosed by systematic biopsy alone, 9 (40.9%) by targeted alone, and 3 (13.6%) by both approaches. On multivariable analysis, the only significant variable predicting the detection of csCaP in men with low-risk imaging mpMRI characteristics was higher PSAD (OR per 0.1 unit=2.26, 95% CI 1.25-4.06, P = 0.007. A PSAD cutoff of 0.1, 0.12 and 0.15 resulted in a negative predictive value (NPV) of 90.9%, 87.1% and 86.2%, respectively. When stratified by PI-RADS score, a PSAD cutoff of 0.1, 0.12 and 0.15 resulted in NPV of 96.2%, 90.6% and 89.7% and 86.2%, 84.2% and 83.3% for detection of csCaP in PI-RADS 2 and 3 lesions, respectively. In patients with PIRDAS 2 lesions, using a PSAD of 0.1 would potentially allow 51% of patients to avoid biopsy with only a 3.8% chance of missing csCaP. CONCLUSION: In men with clinical low-risk prostate cancer on active surveillance with PI-RADS 2 and 3 lesions, there is an almost 18% risk of upgrade to csCaP. Integration of PSAD may be a useful adjunctive tool in identifying patients at highest risk for upgrade despite favorable imaging findings. In men with PIRADS 2 lesions with PSAD ≤0.12 biopsy can be avoided. For men with PIRADS 2 lesions with PSAD ≤0.15 informed decision making regarding the AS intensity should include that these patients have a low risk (>10%) of developing csCaP. In men with PIRADS 3 lesions with PSAD >0.1, shared decision making should include discussion of a >10% miss rate of csCaP.

Multi-institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI-RADS 3 lesions.

BACKGROUND: Most Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions do not contain clinically significant prostate cancer (CSPCa; grade group ≥2). This study was aimed at identifying clinical and magnetic resonance imaging (MRI)-derived risk fac- tors that predict CSPCa in men with PI-RADS 3 lesions. METHODS: This study analyzed the detection of CSPCa in men who underwent MRI-targeted biopsy for PI-RADS 3 lesions. Multivariable logistic regression models with goodness-of-fit testing were used to identify variables associated with CSPCa. Receiver operating curves and decision curve analyses were used to estimate the clinical utility of a predictive model. RESULTS: Of the 1784 men reviewed, 1537 were included in the training cohort, and 247 were included in the validation cohort. The 309 men with CSPCa (17.3%) were older, had a higher prostate-specific antigen (PSA) density, and had a greater likelihood of an anteriorly located lesion than men without CSPCa (p < .01). Multivariable analysis revealed that PSA density (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.05-1.85; p < .01), age (OR, 1.05; 95% CI, 1.02-1.07; p < .01), and a biopsy-naive status (OR, 1.83; 95% CI, 1.38-2.44) were independently associated with CSPCa. A prior negative biopsy was negatively associated (OR, 0.35; 95% CI, 0.24-0.50; p < .01). The application of the model to the validation cohort resulted in an area under the curve of 0.78. A predicted risk threshold of 12% could have prevented 25% of biopsies while detecting almost 95% of CSPCas with a sensitivity of 94% and a specificity of 34%. CONCLUSIONS: For PI-RADS 3 lesions, an elevated PSA density, older age, and a biopsy-naive status were associated with CSPCa, whereas a prior negative biopsy was negatively associated. A predictive model could prevent PI-RADS 3 biopsies while missing few CSPCas. LAY SUMMARY: Among men with an equivocal lesion (Prostate Imaging-Reporting and Data System 3) on multiparametric magnetic resonance imaging (mpMRI), those who are older, those who have a higher prostate-specific antigen density, and those who have never had a biopsy before are at higher risk for having clinically significant prostate cancer (CSPCa) on subsequent biopsy. However, men with at least one negative biopsy have a lower risk of CSPCa. A new predictive model can greatly reduce the need to biopsy equivocal lesions noted on mpMRI while missing only a few cases of CSPCa.

Real-Time MRI-Guided Prostate Interventions.

Prostate cancer (PCa) is the second most common cause of cancer death in males. Targeting MRI-visible lesions has led to an overall increase in the detection of clinically significant PCa compared to the prior practice of random ultrasound-guided biopsy of the prostate. Additionally, advances in MRI-guided minimally invasive focal treatments are providing new options for patients with PCa. This review summarizes the currently utilized real-time MRI-guided interventions for PCa diagnosis and treatment.

Association Between a 22-feature Genomic Classifier and Biopsy Gleason Upgrade During Active Surveillance for Prostate Cancer.

BACKGROUND: Although the Decipher genomic classifier has been validated as a prognostic tool for several prostate cancer endpoints, little is known about its role in assessing the risk of biopsy reclassification for patients on active surveillance, a key event that often triggers treatment. OBJECTIVE: To evaluate the association between Decipher genomic classifier scores and biopsy Gleason upgrading among patients on active surveillance. DESIGN SETTING AND PARTICIPANTS: This was a retrospective cohort study among patients with low- and favorable intermediate-risk prostate cancer on active surveillance who underwent biopsy-based Decipher testing as part of their clinical care. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We evaluated the association between the Decipher score and any increase in biopsy Gleason grade group (GG) using univariable and multivariable logistic regression. We compared the area under the receiver operating characteristic curve (AUC) for models comprising baseline clinical variables with or without the Decipher score. RESULTS AND LIMITATIONS: We identified 133 patients for inclusion with a median age of 67.7 yr and median prostate-specific of 5.6 ng/ml. At enrollment, 75.9% had GG1 and 24.1% had GG2 disease. Forty-three patients experienced biopsy upgrading. On multivariable logistic regression, the Decipher score was significantly associated with biopsy upgrading (odds ratio 1.37 per 0.10 unit increase, 95% confidence interval [CI] 1.05-1.79; p = 0.02). The Decipher score was associated with upgrading among patients with biopsy GG 1 disease, but not GG2 disease. The discriminative ability of a clinical model (AUC 0.63, 95% CI 0.51-0.74) was improved by integration of the Decipher score (AUC 0.69, 95% CI 0.58-0.80). CONCLUSIONS: The Decipher genomic classifier score was associated with short-term biopsy Gleason upgrading among patients on active surveillance. PATIENT SUMMARY: The results from this study indicate that among patients with prostate cancer undergoing active surveillance, those with higher Decipher scores were more likely to have higher-grade disease found over time. These findings indicate that the Decipher test might be useful for guiding the intensity of monitoring during active surveillance, such as more frequent biopsy for patients with higher scores.

Optimal Use of Tumor-Based Molecular Assays for Localized Prostate Cancer.

PURPOSEOF REVIEW: The use of genomic testing for prostate cancer continues to grow; however, utilization remains institutionally dependent. Herein, we review current tissue-based markers and comment on current use with active surveillance and prostate MRI. RECENT FINDINGS: While data continues to emerge, several studies have shown a role for genomic testing for treatment selection. Novel testing options include ConfirmMDx, ProMark, Prolaris, and Decipher, which have shown utility in select patients. The current body of literature on this specific topic remains very limited; prospective trials with long-term follow-up are needed to improve our understanding on how these genomic tests fit when combined with our current clinical tools. As the literature matures, it is likely that newer risk calculators that combine our classic clinical variables with genomic and imaging data will be developed to bring about standard protocols for prostate cancer decision-making.

Extent of High-Grade Prostatic Adenocarcinoma in Multiparametric Magnetic Resonance Imaging-Targeted Biopsy Enhances Prediction of Pathologic Stage.

CONTEXT.­: Multiparametric magnetic resonance imaging (mpMRI) of prostate with targeted biopsy has enhanced detection of high-grade prostatic adenocarcinoma (HG PCa). However, utility of amount of HG PCa (Gleason pattern 4/5) in mpMRI-targeted biopsies versus standard 12-core biopsies in predicting adverse outcomes on radical prostatectomy (RP) is unknown. OBJECTIVE.­: To examine the utility of amount of HG PCa in mpMRI-targeted biopsies versus standard 12-core biopsies in predicting adverse RP outcomes. DESIGN.­: We performed a retrospective review of prostate biopsies that had corresponding RP, 1 or more mpMRI-targeted biopsy, and Grade Group 2 disease or higher. For the 169 cases identified, total millimeters of carcinoma and HG PCa and longest length HG PCa in a single core were recorded for 12-core biopsies and each set of mpMRI-targeted biopsies. For RP specimens, Gleason grade, extraprostatic extension, seminal vesicle involvement, and lymph node metastasis were recorded. The main outcome studied was prostate-confined disease at RP. A logistic regression model was used to test which pre-RP variables related to this outcome. RESULTS.­: Univariate analysis showed significant associations with adverse RP outcomes in 5 of 8 quantifiable variables; longest millimeter HG PCa in a single 12-core biopsy, highest Grade Group in any core, and total millimeter HG in mpMRI-targeted biopsies showed no statistical association (P = .54, P = .13, and P = .55, respectively). In multivariate analysis, total millimeter carcinoma in all cores, highest Grade Group in any core, and longest millimeter HG PCa in a single mpMRI-targeted core provided additional predictive value (P < .001, P = .004, and P = .03, respectively). CONCLUSIONS.­: Quantitation of HG PCa in mpMRI-targeted biopsies provides additional value over 12-core biopsies alone in predicting nonorgan confined prostate cancer at RP. Linear millimeters of HG PCa in mpMRI-targeted biopsies is a significant parameter associated with higher pathologic stage and could be of value in risk models.