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Cribriform growth pattern is well-established as an adverse pathologic feature in prostate cancer. The literature suggests "large" cribriform glands associate with aggressive behavior; however, published studies use varying definitions for "large". We aimed to identify an outcome-based quantitative cut-off for "large" vs "small" cribriform glands. We conducted an initial training phase using the tissue microarray based Canary retrospective radical prostatectomy cohort. Of 1287 patients analyzed, cribriform growth was observed in 307 (24%). Using Kaplan-Meier estimates of recurrence-free survival curves (RFS) that were stratified by cribriform gland size, we identified 0.25 mm as the optimal cutoff to identify more aggressive disease. In univariable and multivariable Cox proportional hazard analyses, size >0.25 mm was a significant predictor of worse RFS compared to patients with cribriform glands ≤0.25 mm, independent of pre-operative PSA, grade, stage and margin status (p 0.25 mm had a significantly lower RFS relative to patients with cribriform glands ≤0.25 mm (each subset p = 0.004). Furthermore, there was no significant difference in outcomes between patients with cribriform glands ≤ 0.25 mm and patients without cribriform glands. The >0.25 mm cut-off was validated as statistically significant in a separate 419 patient, completely embedded whole-section radical prostatectomy cohort by biochemical recurrence, metastasis-free survival, and disease specific death, even when cases with admixed Gleason pattern 5 carcinoma were excluded. In summary, our findings support reporting cribriform gland size and identify 0.25 mm as an optimal outcome-based quantitative measure for defining "large" cribriform glands. Moreover, cribriform glands >0.25 mm are associated with potential for metastatic disease independent of Gleason pattern 5 adenocarcinoma.

PURPOSE: Many localized prostate cancers will follow an indolent course. Management has shifted toward active surveillance (AS), yet an optimal regimen remains controversial especially regarding expensive multiparametric magnetic resonance imaging (MRI). We aimed to assess cost-effectiveness of MRI in AS protocols. MATERIALS AND METHODS: A probabilistic microsimulation modeled individual patient trajectories for men diagnosed with low-risk cancer. We assessed no surveillance, up-front treatment (surgery or radiation), and scheduled AS protocols incorporating transrectal ultrasound-guided (TRUS) biopsy or MRI based regimens at serial intervals. Lifetime quality-adjusted life-years and costs adjusted to 2020 US$ were used to calculate expected net monetary benefit at $50,000/quality-adjusted life-year and incremental cost-effectiveness ratios. Uncertainty was assessed with probabilistic sensitivity analysis and linear regression metamodeling. RESULTS: Conservative management with AS outperformed up-front definitive treatment in a modeled cohort reflecting characteristics from a multi-institutional trial. Biopsy decision conditional on positive imaging (MRI triage) at 2-year intervals provided the highest expected net monetary benefit (incremental cost-effectiveness ratio $44,576). Biopsy after both positive and negative imaging (MRI pathway) and TRUS biopsy based regimens were not cost-effective. MRI triage resulted in fewer biopsies while reducing metastatic disease or cancer death. Results were sensitive to test performance and cost. MRI triage was the most likely cost-effective strategy on probabilistic sensitivity analysis. CONCLUSIONS: For men with low-risk prostate cancer, our modeling demonstrated that AS with sequential MRI triage is more cost-effective than biopsy regardless of imaging, TRUS biopsy alone or immediate treatment. AS guidelines should specify the role of imaging, and prospective studies should be encouraged.

BackgroundPathogenic germline mutations in several rare penetrant cancer predisposition genes are associated with an increased risk of aggressive prostate cancer (PC). Our objectives were to determine the prevalence of pathogenic germline mutations in men with low-risk PC on active surveillance, and assess whether pathogenic germline mutations associate with grade reclassification or adverse pathology, recurrence, or metastases, in men treated after initial surveillance.MethodsMen prospectively enrolled in the Canary Prostate Active Surveillance Study (PASS) were retrospectively sampled for the study. Germline DNA was sequenced utilizing a hereditary cancer gene panel. Mutations were classified according to the American College of Clinical Genetics and Genomics' guidelines. The association of pathogenic germline mutations with grade reclassification and adverse characteristics was evaluated by weighted Cox proportional hazards modeling and conditional logistic regression, respectively.ResultsOverall, 29 of 437 (6.6%) study participants harbored a pathogenic germline mutation of which 19 occurred in a gene involved in DNA repair (4.3%). Eight participants (1.8%) had pathogenic germline mutations in three genes associated with aggressive PC: ATM, BRCA1, and BRCA2. The presence of pathogenic germline mutations in DNA repair genes did not associate with adverse characteristics (univariate analysis HR=0.87, 95% CI: 0.36-2.06, p=0.7). The carrier rates of pathogenic germline mutations in ATM, BRCA1, and BRCA2did not differ in men with or without grade reclassification (1.9% vs. 1.8%).ConclusionThe frequency of pathogenic germline mutations in penetrant cancer predisposition genes is extremely low in men with PC undergoing active surveillance and pathogenic germline mutations had no apparent association with grade reclassification or adverse characteristics.

BACKGROUND: Distinguishing men with aggressive from indolent prostate cancer is critical to decisions in the management of clinically localized prostate cancer. Molecular signatures of aggressive disease could help men overcome this major clinical challenge by reducing unnecessary treatment and allowing more appropriate treatment of aggressive disease. METHODS: We performed a mass spectrometry-based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3 to 5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow-up. To better understand the biological pathways underlying prostate cancer aggressiveness, we performed a systems biology analysis and gene enrichment analysis. Proteins that distinguished recurrent from non-recurrent cancer were chosen for validation by immunohistochemical analysis on tissue microarrays containing samples from a larger cohort of patients with recurrent and non-recurrent prostate cancer. RESULTS: 24,037 unique peptides (false discovery rate < 1%) corresponding to 3,313 distinct proteins were identified with absolute abundance ranges spanning seven orders of magnitude. Of these proteins, 115 showed significantly (P < 0.01) different levels in tissues from recurrent versus non-recurrent cancers. Analysis of all differentially expressed proteins in recurrent and non-recurrent cases identified several protein networks, most prominently one in which approximately 24% of the proteins in the network were regulated by the YY1 transcription factor (adjusted P < 0.001). Strong immunohistochemical staining levels of three differentially expressed proteins, POSTN, CALR, and CTSD, on a tissue microarray validated their association with shorter patient survival. CONCLUSIONS: The protein signatures identified could improve understanding of the molecular drivers of aggressive prostate cancer and be used as candidate prognostic biomarkers.

PURPOSE Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data in the electronic health record (EHR). We aimed to predict risk of preventable ACU after starting chemotherapy using machine learning (ML) algorithms trained on comprehensive EHR data. METHODS Chemotherapy patients treated at an academic institution and affiliated community care sites between January 2013 and July 2019 who met inclusion criteria for OP-35 were identified. Preventable ACU was defined using OP-35 criteria. Structured EHR data generated before chemotherapy treatment were obtained. ML models were trained to predict risk for ACU after starting chemotherapy using 80% of the cohort. The remaining 20% were used to test model performance by the area under the receiver operator curve. RESULTS Eight thousand four hundred thirty-nine patients were included, of whom 35% had preventable ACU within 180 days of starting chemotherapy. Our primary model classified patients at risk for preventable ACU with an area under the receiver operator curve of 0.783 (95% CI, 0.761 to 0.806). Performance was better for identifying admissions than emergency department visits. Key variables included prior hospitalizations, cancer stage, race, laboratory values, and a diagnosis of depression. Analyses showed limited benefit from including patient-reported outcome data and indicated inequities in outcomes and risk modeling for Black and Medicaid patients. CONCLUSION Dense EHR data can identify patients at risk for ACU using ML with promising accuracy. These models have potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted, preventative interventions.

We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance.We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (RWe included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, RAmong active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

Prostate cancer is the second deadliest cancer for American men. While Magnetic Resonance Imaging (MRI) is increasingly used to guide targeted biopsies for prostate cancer diagnosis, its utility remains limited due to high rates of false positives and false negatives as well as low inter-reader agreements. Machine learning methods to detect and localize cancer on prostate MRI can help standardize radiologist interpretations. However, existing machine learning methods vary not only in model architecture, but also in the ground truth labeling strategies used for model training. In this study, we compare different labeling strategies, namely, pathology-confirmed radiologist labels, pathologist labels on whole-mount histopathology images, and lesion-level and pixel-level digital pathologist labels (previously validated deep learning algorithm on histopathology images to predict pixel-level Gleason patterns) on whole-mount histopathology images. We analyse the effects these labels have on the performance of the trained machine learning models. Our experiments show that (1) radiologist labels and models trained with them can miss cancers, or underestimate cancer extent, (2) digital pathologist labels and models trained with them have high concordance with pathologist labels, and (3) models trained with digital pathologist labels achieve the best performance in prostate cancer detection in two different cohorts with different disease distributions, irrespective of the model architecture used. Digital pathologist labels can reduce challenges associated with human annotations, including labor, time, inter- and intra-reader variability, and can help bridge the gap between prostate radiology and pathology by enabling the training of reliable machine learning models to detect and localize prostate cancer on MRI., Comment: Indrani Bhattacharya and David S. Lim contributed equally as first authors. Geoffrey A. Sonn and Mirabela Rusu contributed equally as senior authors

PurposeActive surveillance (AS) for grade group (GG) 2 patients is not yet well defined. We sought to compare clinical outcomes of men with GG1 and GG2 prostate cancer undergoing AS in a large prospective North American cohort.Materials and methodsParticipants were prospectively enrolled in an AS study with protocol-directed followup at 10 centers in the U.S. and Canada. We evaluated time from diagnosis to biopsy grade reclassification and time to treatment. In men treated after initial surveillance, adverse pathology and recurrence were also analyzed.ResultsAt diagnosis, 154 (9%) had GG2 and 1,574 (91%) had GG1. Five-year reclassification rates were similar between GG2 and GG1 (30% vs 37%, p=0.11). However, more patients with GG2 were treated at 5 years (58% vs 34%, p

Background Estimates of overall patient health are essential to inform treatment decisions for patients diagnosed with cancer. The authors applied XWAS methods, herein referred to as "laboratory-wide association study (LWAS)", to evaluate associations between routinely collected laboratory tests and survival in veterans with prostate cancer. Methods The authors identified 133,878 patients who were diagnosed with prostate cancer between 2000 and 2013 in the Veterans Health Administration using any laboratory tests collected within 6 months of diagnosis (3,345,083 results). Using the LWAS framework, the false-discovery rate was used to test the association between multiple laboratory tests and survival, and these results were validated using training, testing, and validation cohorts. Results A total of 31 laboratory tests associated with survival met stringent LWAS criteria. LWAS confirmed markers of prostate cancer biology (prostate-specific antigen: hazard ratio [HR], 1.07 [95% confidence interval (95% CI), 1.06-1.08]; and alkaline phosphatase: HR, 1.22 [95% CI, 1.20-1.24]) as well laboratory tests of general health (eg, serum albumin: HR, 0.78 [95% CI, 0.76-0.80]; and creatinine: HR, 1.05 [95% CI, 1.03-1.07]) and inflammation (leukocyte count: HR, 1.23 [95% CI, 1.98-1.26]; and erythrocyte sedimentation rate: HR, 1.33 [95% CI, 1.09-1.61]). In addition, the authors derived and validated separate models for patients with localized and advanced disease, identifying 28 laboratory markers and 15 laboratory markers, respectively, in each cohort. Conclusions The authors identified routinely collected laboratory data associated with survival for patients with prostate cancer using LWAS methodologies, including markers of prostate cancer biology, overall health, and inflammation. Broadening consideration of determinants of survival beyond those related to cancer itself could help to inform the design of clinical trials and aid in shared decision making. Lay summary This article examined routine laboratory tests associated with survival among veterans with prostate cancer. Using laboratory-wide association studies, the authors identified 31 laboratory tests associated with survival that can be used to inform the design of clinical trials and aid patients in shared decision making.

Purpose Prior studies suggest email communication between patients and providers may improve patient engagement and health outcomes. The purpose of this study was to determine whether patient‐initiated emails are associated with overall survival benefits among cancer patients undergoing chemotherapy. Patients and methods We identified patient‐initiated emails through the patient portal in electronic health records (EHR) among 9900 cancer patients receiving chemotherapy between 2013 and 2018. Email users were defined as patients who sent at least one email 12 months before to 2 months after chemotherapy started. A propensity score‐matched cohort analysis was carried out to reduce bias due to confounding (age, primary cancer type, gender, insurance payor, ethnicity, race, stage, income, Charlson score, county of residence). The cohort included 3223 email users and 3223 non‐email users. The primary outcome was overall 2‐year survival stratified by email use. Secondary outcomes included number of face‐to‐face visits, prescriptions, and telephone calls. The healthcare teams’ response to emails and other forms of communication was also investigated. Finally, a quality measure related to chemotherapy‐related inpatient and emergency department visits was evaluated. Results Overall 2‐year survival was higher in patients who were email users, with an adjusted hazard ratio of 0.80 (95 CI 0.72–0.90; p, Patient portals provide a tool for patients to communicate with their care team that provides overall clinical benefit for advanced cancer patients; the healthcare team's response to patients’ emails included drug prescriptions, medical appointment scheduling, telephone calls, and response emails. Patient emails are a novel source of patient‐generated data that may play a vital role in patient symptom monitoring.

To personalize treatment for renal cell carcinoma (RCC), it would be ideal to confirm the activity of druggable protein pathways within individual tumors. We have developed a high-resolution nanoimmunoassay (NIA) to measure protein activity with high precision in scant specimens (eg, fine needle aspirates [FNAs]). Here, we used NIA to determine whether protein activation varied in different regions of RCC tumors. Since most RCC therapies target angiogenesis by inhibiting the vascular endothelial growth factor (VEGF) receptor, we quantified phosphorylation of extracellular signal-regulated kinase (ERK), a downstream effector of the VEGF signaling pathway. In 90 ex vivo FNA biopsies sampled from multiple regions of 38 primary clear cell RCC tumors, ERK phosphorylation differed among patients. In contrast, within individual patients, we found limited intratumoral heterogeneity of ERK phosphorylation. Our results suggest that measuring ERK in a single FNA may be representative of ERK activity in different regions of the same tumor. As diagnostic and therapeutic protein biomarkers are being sought, NIA measurements of protein signaling may increase the clinical utility of renal mass biopsy and allow for the application of precision oncology for patients with localized and advanced RCC. Patient summary In this report, we applied a new approach to measure the activity of extracellular signal-regulated kinase (ERK), a key cancer signaling protein, in different areas within kidney cancers. We found that ERK activity varied between patients, but that different regions within individual kidney tumors showed similar ERK activity. This suggests that a single biopsy of renal cell carcinoma may be sufficient to measure protein signaling activity to aid in precision oncology approaches.

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy (PN). However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In this study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal-tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal-tumor pairs were analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids, and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94% and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.

Significance NEPC is a highly aggressive subtype of prostate cancer that is increasing in incidence, likely due to use of new secondary androgen deprivation therapies. Here, we demonstrate that Trop2 is significantly elevated in CRPC and NEPC and represents a driver of metastatic NEPC. Trop2 overexpression increases tumor growth, drives metastasis and neuroendocrine phenotype, and significantly increases PARP1 levels. Inhibition of PARP1 in Trop2-driven NEPC significantly decreases neuroendocrine features, tumor growth, and metastatic colonization in vivo, suggesting that PARP1 inhibitors may represent a promising therapeutic strategy for metastatic prostate cancer expressing high levels of Trop2., Resistance to androgen deprivation therapy, or castration-resistant prostate cancer (CRPC), is often accompanied by metastasis and is currently the ultimate cause of prostate cancer-associated deaths in men. Recently, secondary hormonal therapies have led to an increase of neuroendocrine prostate cancer (NEPC), a highly aggressive variant of CRPC. Here, we identify that high levels of cell surface receptor Trop2 are predictive of recurrence of localized prostate cancer. Moreover, Trop2 is significantly elevated in CRPC and NEPC, drives prostate cancer growth, and induces neuroendocrine phenotype. Overexpression of Trop2 induces tumor growth and metastasis while loss of Trop2 suppresses these abilities in vivo. Trop2-driven NEPC displays a significant up-regulation of PARP1, and PARP inhibitors significantly delay tumor growth and metastatic colonization and reverse neuroendocrine features in Trop2-driven NEPC. Our findings establish Trop2 as a driver and therapeutic target for metastatic prostate cancer with neuroendocrine phenotype and suggest that high Trop2 levels could identify cancers that are sensitive to Trop2-targeting therapies and PARP1 inhibition.

To develop and validate a new tissue-based biomarker that improves prediction of outcomes in localized prostate cancer by quantifying the host response to tumor. We use digital image analysis and machine learning to develop a biomarker of the prostate stroma called quantitative reactive stroma (qRS). qRS is a measure of percentage tumor area with a distinct, reactive stromal architecture. Kaplan Meier analysis was used to determine survival in a large retrospective cohort of radical prostatectomy samples. qRS was validated in two additional, distinct cohorts that include international cases and tissue from both radical prostatectomy and biopsy specimens. In the developmental cohort (Baylor College of Medicine, n=482), patients whose tumor had qRS > 34% had increased risk of prostate cancer-specific death (HR 2.94; p=0.039). This result was replicated in two validation cohorts, where patients with qRS > 34% had increased risk of prostate cancer-specific death (MEDVAMC; n=332; HR 2.64; p=0.02) and also biochemical recurrence (Canary; n=988; HR 1.51; p=0.001). By multivariate analysis, these associations were shown to hold independent predictive value when compared to currently used clinicopathologic factors including Gleason score and PSA. qRS is a new, validated biomarker that predicts prostate cancer death and biochemical recurrence across three distinct cohorts. It measures host-response rather than tumor-based characteristics, and provides information not represented by standard prognostic measurements.

Automated methods for detecting prostate cancer and distinguishing indolent from aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis and treatment planning. Existing automated methods of prostate cancer detection mostly rely on ground truth labels with limited accuracy, ignore disease pathology characteristics observed on resected tissue, and cannot selectively identify aggressive (Gleason Pattern≥4) and indolent (Gleason Pattern=3) cancers when they co-exist in mixed lesions. In this paper, we present a radiology-pathology fusion approach, CorrSigNIA, for the selective identification and localization of indolent and aggressive prostate cancer on MRI. CorrSigNIA uses registered MRI and whole-mount histopathology images from radical prostatectomy patients to derive accurate ground truth labels and learn correlated features between radiology and pathology images. These correlated features are then used in a convolutional neural network architecture to detect and localize normal tissue, indolent cancer, and aggressive cancer on prostate MRI. CorrSigNIA was trained and validated on a dataset of 98 men, including 74 men that underwent radical prostatectomy and 24 men with normal prostate MRI. CorrSigNIA was tested on three independent test sets including 55 men that underwent radical prostatectomy, 275 men that underwent targeted biopsies, and 15 men with normal prostate MRI. CorrSigNIA achieved an accuracy of 80% in distinguishing between men with and without cancer, a lesion-level ROC-AUC of 0.81±0.31 in detecting cancers in both radical prostatectomy and biopsy cohort patients, and lesion-levels ROC-AUCs of 0.82±0.31 and 0.86±0.26 in detecting clinically significant cancers in radical prostatectomy and biopsy cohort patients respectively. CorrSigNIA consistently outperformed other methods across different evaluation metrics and cohorts. In clinical settings, CorrSigNIA may be used in prostate cancer detection as well as in selective identification of indolent and aggressive components of prostate cancer, thereby improving prostate cancer care by helping guide targeted biopsies, reducing unnecessary biopsies, and selecting and planning treatment.

Sialic acids have been implicated in cancer initiation, progression, and immune evasion in diverse human malignancies. Sialylation of terminal glycans on cell surface and secreted glycoproteins is a long-recognized feature of cancer cells. Recently, immune checkpoint inhibitor immunotherapy has tremendously improved the outcomes of patients with various cancers. However, available immunotherapy approaches have had limited efficacy in metastatic castration-resistant prostate cancer. Sialic acid modified glycoproteins in prostate cancers and their interaction with Siglec receptors on tumor infiltrating immune cells might underlie immunosuppressive signaling in prostate cancer. Here, we summarize the function of sialic acids and relevant glycosynthetic enzymes in cancer initiation and progression. We also discuss the possible uses of sialic acids as biomarkers in prostate cancer and the potential methods for targeting Siglec-sialic acid interactions for prostate cancer treatment.

Background Maintaining men on active surveillance for prostate cancer can be challenging. Although most men who eventually undergo treatment have experienced clinical progression, a smaller subset elects treatment in the absence of disease reclassification. This study sought to understand factors associated with treatment in a large, contemporary, prospective cohort. Methods This study identified 1789 men in the Canary Prostate Cancer Active Surveillance Study cohort enrolled as of 2020 with a median follow-up of 5.6 years. Clinical and demographic data as well as information on patient-reported quality of life and urinary symptoms were used in multivariable Cox proportional hazards regression models to identify factors associated with the time to treatment RESULTS: Within 4 years of their diagnosis, 33% of men (95% confidence interval [CI], 30%-35%) underwent treatment, and 10% (95% CI, 9%-12%) were treated in the absence of reclassification. The most significant factor associated with any treatment was an increasing Gleason grade group (adjusted hazard ratio [aHR], 14.5; 95% CI, 11.7-17.9). Urinary quality-of-life scores were associated with treatment without reclassification (aHR comparing "mostly dissatisfied/terrible" with "pleased/mixed," 2.65; 95% CI, 1.54-4.59). In a subset analysis (n = 692), married men, compared with single men, were more likely to undergo treatment in the absence of reclassification (aHR, 2.63; 95% CI, 1.04-6.66). Conclusions A substantial number of men with prostate cancer undergo treatment in the absence of clinical changes in their cancers, and quality-of-life changes and marital status may be important factors in these decisions. Lay summary This analysis of men on active surveillance for prostate cancer shows that approximately 1 in 10 men will decide to be treated within 4 years of their diagnosis even if their cancer is stable. These choices may be related in part to quality-or-life or spousal concerns.

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer that rarely develops de novo in primary tumors and is commonly acquired during the development of treatment resistance. NEPC is characterized by gain of neuroendocrine markers and loss of androgen receptor (AR), making it resistant to current therapeutic strategies targeting the AR signaling axis. Here, we report that MCM2, MCM3, MCM4, and MCM6 (MCM2/3/4/6) are elevated in human NEPC and high levels of MCM2/3/4/6 are associated with liver metastasis and poor survival in prostate cancer patients. MCM2/3/4/6 are four out of six proteins that form a core DNA helicase (MCM2-7) responsible for unwinding DNA forks during DNA replication. Inhibition of MCM2-7 by treatment with ciprofloxacin inhibits NEPC cell proliferation and migration in vitro, significantly delays NEPC tumor xenograft growth, and partially reverses the neuroendocrine phenotype in vivo. Our study reveals the clinical relevance of MCM2/3/4/6 proteins in NEPC and suggests that inhibition of MCM2-7 may represent a new therapeutic strategy for NEPC.

Background High‐value cancer care balances effective treatment with preservation of quality of life. Chemotherapy is known to affect patients’ physical and psychological well‐being negatively. Patient‐reported outcomes (PROs) provide a means to monitor declines in a patients’ well‐being during treatment. Methods We identified 741 oncology patients undergoing chemotherapy in our electronic health record (EHR) system who completed Patient‐Reported Outcomes Measurement Information System (PROMIS) surveys during treatment at a comprehensive cancer center, 2013–2018. PROMIS surveys were collected before, during, and after chemotherapy treatment. Linear mixed‐effects models were performed to identify predictors of physical and mental health scores over time. A k‐mean cluster analysis was used to group patient PROMIS score trajectories. Results Mean global physical health (GPH) scores were 48.7 (SD 9.3), 47.7 (8.8), and 48.6 (8.9) and global mental health (GMH) scores were 50.4 (8.6), 49.5 (8.8), and 50.6 (9.1) before, during, and after chemotherapy, respectively. Asian race, Hispanic ethnicity, public insurance, anxiety/depression, stage III cancer, and palliative care were predictors of GPH and GMH decline. The treatment time period was also a predictor of both GPH and GMH decline relative to pre‐treatment. Trajectory clustering identified four distinct PRO clusters associated with chemotherapy treatment. Conclusions Patient‐reported outcomes are increasingly used to help monitor cancer treatment and are now a part of care reimbursement. This study leveraged routinely collected PROMIS surveys linked to EHRs to identify novel patient trajectories of physical and mental well‐being in oncology patients undergoing chemotherapy and potential predictors. Supportive care interventions in high‐risk populations identified by our study may optimize resource deployment. Novelty and impact This study leveraged routinely collected patient‐reported outcome (PROMIS) surveys linked to electronic health records to characterize oncology patients’ quality of life during chemotherapy. Important clinical and demographic predictors of declines in quality of life were identified and four novel trajectories to guide personalized interventions and support. This work highlights the utility of monitoring patient‐reported outcomes not only before and after, but during chemotherapy to help advert adverse patient outcomes and improve treatment adherence., This study leveraged routinely collected patient‐reported outcome (PROMIS) surveys linked to electronic health records to characterize oncology patients’ quality of life during chemotherapy. Important clinical and demographic predictors of declines in quality of life were identified and four novel trajectories to guide personalized interventions and support. This work highlights the utility of monitoring patient‐reported outcomes not only before and after, but during chemotherapy to help advert adverse patient outcomes and improve treatment adherence.

Purpose: While multi-parametric magnetic resonance imaging (MRI) shows great promise in assisting with prostate cancer diagnosis and localization, subtle differences in appearance between cancer and normal tissue lead to many false positive and false negative interpretations by radiologists. We sought to automatically detect aggressive cancer (Gleason pattern (Formula presented.) 4) and indolent cancer (Gleason pattern 3) on a per-pixel basis on MRI to facilitate the targeting of aggressive cancer during biopsy. Methods: We created the Stanford Prostate Cancer Network (SPCNet), a convolutional neural network model, trained to distinguish between aggressive cancer, indolent cancer, and normal tissue on MRI. Ground truth cancer labels were obtained by registering MRI with whole-mount digital histopathology images from patients who underwent radical prostatectomy. Before registration, these histopathology images were automatically annotated to show Gleason patterns on a per-pixel basis. The model was trained on data from 78 patients who underwent radical prostatectomy and 24 patients without prostate cancer. The model was evaluated on a pixel and lesion level in 322 patients, including six patients with normal MRI and no cancer, 23 patients who underwent radical prostatectomy, and 293 patients who underwent biopsy. Moreover, we assessed the ability of our model to detect clinically significant cancer (lesions with an aggressive component) and compared it to the performance of radiologists. Results: Our model detected clinically significant lesions with an area under the receiver operator characteristics curve of 0.75 for radical prostatectomy patients and 0.80 for biopsy patients. Moreover, the model detected up to 18% of lesions missed by radiologists, and overall had a sensitivity and specificity that approached that of radiologists in detecting clinically significant cancer. Conclusions: Our SPCNet model accurately detected aggressive prostate cancer. Its performance approached that of radiologists, and it helped identify lesions otherwise missed by radiologists. Our model has the potential to assist physicians in specifically targeting the aggressive component of prostate cancers during biopsy or focal treatment.

AimsZinc-alpha 2-glycoprotein (AZGP1) is a promising tissue biomarker to predict outcomes in men undergoing treatment for localised prostate cancer (PCa). We aimed to examine the association between AZGP1 expression and the endpoints: risk of biochemical failure (BF), initiating castration-based treatment, developing castration-resistant PCa (CRPC) and PCa-specific mortality following radical prostatectomy (RP).MethodsThe study included a prospective cohort of 302 patients who underwent RP for PCa from 2002 to 2005. AZGP1 expression was analysed using immunohistochemistry on tissue microarray RP specimens and was scored semiquantitively as low or high expression. Risk of all endpoints was analysed using stratified cumulative incidences and cause-specific Cox regression, and validated with receiver operating curves, calibration and discrimination in competing-risk analyses. A meta-analysis was performed including previous studies investigating AZGP1 expression and risk of BF following RP.ResultsMedian time of follow-up was 14.0 years. The cumulative incidence of all endpoints was significantly higher in patients with low AZGP1 expression compared with patients with high AZGP1 expression (pConclusionsLow AZGP1 expression is associated with the risk of aggressive time-dependent outcomes in men undergoing RP for localised PCa.

Objective The Registered Physician in Vascular Interpretation (RPVI) credential is a prerequisite for certification by the Vascular Surgery Board of the American Board of Surgery. Of concern, as more current trainees and recent program graduates take the Physician Vascular Interpretation (PVI) examination, vascular surgery trainee pass rates have decreased. Residents and fellows have a lower PVI examination pass rates than practicing vascular surgeons. The purpose of this study was to assess current vascular laboratory (VL) training for vascular surgery residents and fellows and to identify gaps that residency and fellowship programs might address. Methods Program directors (PDs) of Accreditation Council for Graduate Medical Education-accredited vascular surgery programs (107 fellowships, 53 integrated residency programs) were surveyed using a web-based tool. Responses were submitted anonymously. Data collected included information about the program, the PD, accreditation status of the VL, and the curriculum used to meet the PVI prerequisites. Concurrent data (June 2017) on the credentials of all PDs were obtained from the Alliance for Physician Certification and Advancement (APCA). Results Sixty-one of 117 PDs participated in the survey (52% response rate). Of these, 44 individuals (72% of responders) reported they held the RPVI and/or Registered Vascular Technologist credential. Records from APCA indicated that 51 of 117 PDs of accredited vascular surgery residencies and fellowships (44%) had an RPVI/Registered Vascular Technologist credential. Ninety-four percent reported that their VL was accredited. Practical VL experience for trainees was reported to be 20 hours or less by 62% of respondents. The use of a structured curriculum for practical experience was reported by only 15 programs. Programs with fellowships established for more than 10 years were more likely to have a structured program for didactic instruction (P = .03). Only 23 programs reported a dedicated VL rotation. Didactic instruction provided was 20 hours or less for 75% of the cohort. Conclusions In the absence of a standardized VL curriculum, there is variation in the VL instruction provided to trainees. Fellowship programs with longer histories have more structured instruction, but time allocated to VL education is substantially less than the 30 hours of didactic and 40 hours of practical experience recommended by the APCA. Programs and learners may benefit from the development of VL training guidelines and curriculum resources.

Background: For men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification. Methods: Urine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short-term and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Results: 782 men contributed 2,069 urine specimens. After adjusting for PSA, prostate size and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR=1.3; 95% CI 1.0–1.7, p=0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker, nor marker kinetics, was associated with time to reclassification in subsequent biopsies. Conclusions: PCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy, but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies.

BACKGROUND The collection of patient-reported outcomes (PROs) is an emerging priority internationally, guiding clinical care, quality improvement projects and research studies. After the deployment of Patient-Reported Outcomes Measurement Information System (PROMIS) surveys in routine outpatient workflows at an academic cancer center, electronic health record data were used to evaluate survey completion rates and self-reported global health measures across 2 tumor types: breast and prostate cancer. METHODS This study retrospectively analyzed 11,657 PROMIS surveys from patients with breast cancer and 4411 surveys from patients with prostate cancer, and it calculated survey completion rates and global physical health (GPH) and global mental health (GMH) scores between 2013 and 2018. RESULTS A total of 36.6% of eligible patients with breast cancer and 23.7% of patients with prostate cancer completed at least 1 survey, with completion rates lower among black patients for both tumor types (P

BACKGROUND: Prognostic models for patients with metastatic renal cell carcinoma (mRCC) include select laboratory values. These models have important limitations, including reliance on a limited array of laboratory tests, and use of dichotomous (“high-low”) cutoffs. We applied a Laboratory-Wide Association Study (LWAS) framework to systematically evaluate common clinical laboratory results associated with survival for patients diagnosed with mRCC. METHODS: We used laboratory data for 3,385 patients diagnosed with mRCC from 2002 to 2017. We developed a LWAS framework, to examine the association with 53 common clinical laboratory tests results (641,712 measurements) and overall survival. We employed false-discovery rate to test the association of multiple laboratory tests with survival, and validated these results using 3 separate cohorts to generate a standardized hazard ratio (sHR), reported for a 1 standard deviation unit change in each laboratory test. RESULTS: The LWAS approach confirmed the association of laboratory values currently used in prognostic models with survival, including calcium (HR 1.35, 95%CI 1.24–1.48), leukocyte count (HR 1.40, 95%CI 1.30–1.51), platelet count (HR 1.36, 95%CI 1.27–1.51), and hemoglobin (HR 0.79, 95%CI 0.72–0.86). Use of these tests as continuous variables improved model performance. LWAS also identified acute phase reactants associated with survival not typically included in prognostic models, including serum albumin (HR 0.66, 95%CI 0.61–0.72), ferritin (HR 1.25, 95%CI 1.08–1.45), alkaline phosphatase (HR 1.31, 95%CI 1.23–1.40), and C-reactive protein (HR 1.70, 95%CI 1.14–2.53). CONCLUSIONS: Routinely measured laboratory tests can refine current prognostic models, facilitate comparisons across clinical trial cohorts, and match patients with specific systemic therapies. Published by Elsevier Inc.

Prostate cancer remains the most common non-cutaneous malignancy among men in the United States. To discover potential serum-based biomarkers for high-risk prostate cancer, we performed a high-multiplex immunoassay utilizing patient-matched pre-operative and post-operative serum samples from ten men with high-grade and high-volume prostate cancer. Our study identified six (CASP8, MSLN, FGFBP1, ICOSLG, TIE2 and S100A4) out of 174 proteins that were significantly decreased after radical prostatectomy. High levels of CASP8 were detected in pre-operative serum samples when compared to post-operative serum samples and serum samples from patients with benign prostate hyperplasia (BPH). By immunohistochemistry, CASP8 protein was expressed at higher levels in prostate cancer tissues compared to non-cancerous and BPH tissues. Likewise, CASP8 mRNA expression was significantly upregulated in prostate cancer when compared to benign prostate tissues in four independent clinical datasets. In addition, mRNA levels of CASP8 were higher in patients with recurrent prostate cancer when compared to patients with non-recurrent prostate cancer and high expression of CASP8 was associated with worse disease-free survival and overall survival in renal cancer. Together, our results suggest that CASP8 may potentially serve as a biomarker for high-risk prostate cancer and possibly renal cancer.

The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However, identifying the presence and extent of cancer on MRI remains challenging, leading to high variability in detection even among expert radiologists. Improvement in cancer detection on MRI is essential to reducing this variability and maximizing the clinical utility of MRI. To date, such improvement has been limited by the lack of accurately labeled MRI datasets. Data from patients who underwent radical prostatectomy enables the spatial alignment of digitized histopathology images of the resected prostate with corresponding pre-surgical MRI. This alignment facilitates the delineation of detailed cancer labels on MRI via the projection of cancer from histopathology images onto MRI. We introduce a framework that performs 3D registration of whole-mount histopathology images to pre-surgical MRI in three steps. First, we developed a novel multi-image super-resolution generative adversarial network (miSRGAN), which learns information useful for 3D registration by producing a reconstructed 3D MRI. Second, we trained the network to learn information between histopathology slices to facilitate the application of 3D registration methods. Third, we registered the reconstructed 3D histopathology volumes to the reconstructed 3D MRI, mapping the extent of cancer from histopathology images onto MRI without the need for slice-to-slice correspondence. When compared to interpolation methods, our super-resolution reconstruction resulted in the highest PSNR relative to clinical 3D MRI (32.15 dB vs 30.16 dB for BSpline interpolation). Moreover, the registration of 3D volumes reconstructed via super-resolution for both MRI and histopathology images showed the best alignment of cancer regions when compared to (1) the state-of-the-art RAPSODI approach, (2) volumes that were not reconstructed, or (3) volumes that were reconstructed using nearest neighbor, linear, or BSpline interpolations. The improved 3D alignment of histopathology images and MRI facilitates the projection of accurate cancer labels on MRI, allowing for the development of improved MRI interpretation schemes and machine learning models to automatically detect cancer on MRI.

Ferroptosis is a type of programmed cell death induced by the accumulation of lipid peroxidation and lipid reactive oxygen species in cells. It has been recently demonstrated that cancer cells are vulnerable to ferroptosis inducers (FIN). However, the therapeutic potential of FINs in prostate cancer in preclinical settings has not been explored. In this study, we demonstrate that mediators of ferroptosis, solute carrier family 7 member 11, SLC3A2, and glutathione peroxidase, are expressed in treatment-resistant prostate cancer. We further demonstrate that treatment-resistant prostate cancer cells are sensitive to two FINs, erastin and RSL3. Treatment with erastin and RSL3 led to a significant decrease in prostate cancer cell growth and migration in vitro and significantly delayed the tumor growth of treatment-resistant prostate cancer in vivo, with no measurable side effects. Combination of erastin or RSL3 with standard-of-care second-generation antiandrogens for advanced prostate cancer halted prostate cancer cell growth and migration in vitro and tumor growth in vivo. These results demonstrate the potential of erastin or RSL3 independently and in combination with standard-of-care second-generation antiandrogens as novel therapeutic strategies for advanced prostate cancer. Significance: These findings reveal that induction of ferroptosis is a new therapeutic strategy for advanced prostate cancer as a monotherapy and in combination with second-generation antiandrogens.

Loss of the von Hippel–Lindau (VHL) tumor suppressor is a hallmark feature of renal clear cell carcinoma. VHL inactivation results in the constitutive activation of the hypoxia-inducible factors (HIFs) HIF-1 and HIF-2 and their downstream targets, including the proangiogenic factors VEGF and PDGF. However, antiangiogenic agents and HIF-2 inhibitors have limited efficacy in cancer therapy due to the development of resistance. Here we employed an innovative computational platform, Mining of Synthetic Lethals (MiSL), to identify synthetic lethal interactions with the loss of VHL through analysis of primary tumor genomic and transcriptomic data. Using this approach, we identified a synthetic lethal interaction between VHL and the m(6)A RNA demethylase FTO in renal cell carcinoma. MiSL identified FTO as a synthetic lethal partner of VHL because deletions of FTO are mutually exclusive with VHL loss in pan cancer datasets. Moreover, FTO expression is increased in VHL-deficient ccRCC tumors compared to normal adjacent tissue. Genetic inactivation of FTO using multiple orthogonal approaches revealed that FTO inhibition selectively reduces the growth and survival of VHL-deficient cells in vitro and in vivo. Notably, FTO inhibition reduced the survival of both HIF wild type and HIF-deficient tumors, identifying FTO as an HIF-independent vulnerability of VHL-deficient cancers. Integrated analysis of transcriptome-wide m(6)A-seq and mRNA-seq analysis identified the glutamine transporter SLC1A5 as an FTO target that promotes metabolic reprogramming and survival of VHL-deficient ccRCC cells. These findings identify FTO as a potential HIF-independent therapeutic target for the treatment of VHL-deficient renal cell carcinoma.

PURPOSE While prostate-specific antigen (PSA) screening protocols vary, many clinicians have anecdotes of screened men with low PSA levels that rise significantly and are associated with high-risk prostate cancer (PC). We sought to better understand the frequency of high-risk cases that appear suddenly in a screened population. METHODS We utilized data from a Commercial and Medicare advantage claims database to identify all US men ages 50 and above undergoing PSA screening who then had a sudden interval rise in PSA (e.g., PSA ≥ 20) and diagnosis of PC. We determined associations with age, race, screening intensity, and baseline PSA levels. RESULTS In all, 526,120 men met entry criteria with an average age of 60.7 and follow-up of 5.6 years. As the baseline PSA increased, the rate of high-risk PC increased from 2/10,000 persons among men with the lowest baseline PSA (

Background: Adolescence is a period of rapid prostatic growth, yet is understudied for susceptibility for future risk of prostate cancer. We examined cardiorespiratory fitness (CRF) in late adolescence in relation to long-term prostate cancer risk. Methods: A population-based cohort study was conducted of all 699,125 Swedish military conscripts during 1972–1985 (97%–98% of 18-year-old men) in relation to risk of prostate cancer overall, aggressive prostate cancer, and prostate cancer mortality during 1998–2017 (ages 50–65 years). CRF was measured by maximal aerobic workload, and prostate cancer was ascertained using the National Prostate Cancer Register. Muscle strength was examined as a secondary predictor. Results: In 38.8 million person-years of follow-up, 10,782 (1.5%) men were diagnosed with prostate cancer. Adjusting for sociodemographic factors, height, weight, and family history of prostate cancer, high CRF was associated with a slightly increased risk of any prostate cancer [highest vs. lowest quintile: incidence rate ratio (IRR), 1.10; 95% CI, 1.03–1.19; P = 0.008], but was neither significantly associated with aggressive prostate cancer (1.01; 0.85–1.21; P = 0.90) nor prostate cancer mortality (1.24; 0.73–2.13; P = 0.42). High muscle strength also was associated with a modestly increased risk of any prostate cancer (highest vs. lowest quintile: IRR, 1.14; 95% CI, 1.07–1.23; P < 0.001), but neither with aggressive prostate cancer (0.88; 0.74–1.04; P = 0.14) nor prostate cancer mortality (0.81; 0.48–1.37; P = 0.43). Conclusions: High CRF or muscle strength in late adolescence was associated with slightly increased future risk of prostate cancer, possibly related to increased screening, but neither with risk of aggressive prostate cancer nor prostate cancer mortality. Impact: These findings illustrate the importance of distinguishing aggressive from indolent prostate cancer and assessing for potential detection bias.

PurposeWe investigated the ability of prostate magnetic resonance imaging to detect Gleason Grade Group 2 or greater cancer in a standardized, multi-institutional active surveillance cohort.Materials and methodsWe evaluated men enrolled in Canary Prostate Active Surveillance Study with Gleason Grade Group less than 2 and who underwent biopsy within 12 months of multiparametric magnetic resonance imaging. Our primary outcome was biopsy reclassification to Gleason Grade Group 2 or greater. We evaluated the performance of magnetic resonance imaging PI-RADS® score and clinical factors. Multivariable logistic regression models were fit with magnetic resonance imaging and clinical factors and used to perform receiver operating curve analyses.ResultsThere were 361 participants with 395 prostate magnetic resonance imaging studies with a median followup of 4.1 (IQR 2.0-7.6) years. Overall 108 (27%) biopsies showed reclassification. Defining positive magnetic resonance imaging as PI-RADS 3-5, the negative predictive value and positive predictive value for detecting Gleason Grade Group 2 or greater cancer was 83% (95% CI 76-90) and 31% (95% CI 26-37), respectively. PI-RADS was significantly associated with reclassification (PI-RADS 5 vs 1 and 2 OR 2.71, 95% CI 1.21-6.17, p=0.016) in a multivariable model but did not improve upon a model with only clinical factors (AUC 0.768 vs 0.762). In 194 fusion biopsies higher grade cancer was found in targeted cores in 21 (11%) instances, while 25 (13%) had higher grade cancer in the systematic cores.ConclusionsThis study adds the largest cohort data to the body of literature for magnetic resonance imaging in active surveillance, recommending systematic biopsy in patients with negative magnetic resonance imaging and the inclusion of systematic biopsy in patients with positive magnetic resonance imaging.

PURPOSE The 17-gene Onco type DX Genomic Prostate Score (GPS) test predicts adverse pathology (AP) in patients with low-risk prostate cancer treated with immediate surgery. We evaluated the GPS test as a predictor of outcomes in a multicenter active surveillance cohort. MATERIALS AND METHODS Diagnostic biopsy tissue was obtained from men enrolled at 8 sites in the Canary Prostate Active Surveillance Study. The primary endpoint was AP (Gleason Grade Group [GG] ≥ 3, ≥ pT3a) in men who underwent radical prostatectomy (RP) after initial surveillance. Multivariable regression models for interval-censored data were used to evaluate the association between AP and GPS. Inverse probability of censoring weighting was applied to adjust for informative censoring. Predictiveness curves were used to evaluate how models stratified risk of AP. Association between GPS and time to upgrade on surveillance biopsy was evaluated using Cox proportional hazards models. RESULTS GPS results were obtained for 432 men (median follow-up, 4.6 years); 101 underwent RP after a median 2.1 years of surveillance, and 52 had AP. A total of 167 men (39%) upgraded at a subsequent biopsy. GPS was significantly associated with AP when adjusted for diagnostic GG (hazards ratio [HR]/5 GPS units, 1.18; 95% CI, 1.04 to 1.44; P = .030), but not when also adjusted for prostate-specific antigen density (PSAD; HR, 1.85; 95% CI, 0.99 to 4.19; P = .066). Models containing PSAD and GG, or PSAD, GG, and GPS may stratify risk better than a model with GPS and GG. No association was observed between GPS and subsequent biopsy upgrade ( P = .48). CONCLUSION In our study, the independent association of GPS with AP after initial active surveillance was not statistically significant, and there was no association with upgrading in surveillance biopsy. Adding GPS to a model containing PSAD and diagnostic GG did not significantly improve stratification of risk for AP over the clinical variables alone.

Patients with kidney cancer are at risk for chronic kidney disease after radical and partial nephrectomy. We determined if the urine albumin-to-creatinine ratio is independently associated with progressive chronic kidney disease after nephrectomy.We performed a cohort study based within a large, integrated health care system. We identified patients who underwent radical or partial nephrectomy from 2004 to 2014 with urine albumin-to-creatinine ratio measured in the 12 months before surgery. We fit multivariable models to determine if the urine albumin-to-creatinine ratio was associated with the time to chronic kidney disease progression (defined as reaching stage 4 or 5 chronic kidney disease, estimated glomerular filtration rate less than 30 ml/minute/1.73 mA total of 1,930 patients underwent radical or partial nephrectomy and had preoperative urine albumin-to-creatinine ratio and preoperative and postoperative estimated glomerular filtration rate. Of these patients 658 (34%) and 157 (8%) had moderate (urine albumin-to-creatinine ratio 30 to 300 mg/gm) or severe albuminuria (urine albumin-to-creatinine ratio greater than 300 mg/gm), respectively. Albuminuria severity was independently associated with progressive chronic kidney disease after radical (moderate albuminuria HR 1.7, 95% CI 1.4-2.2; severe albuminuria HR 2.3, 95% CI 1.7-3.1) and partial nephrectomy (moderate albuminuria HR 1.8, 95% CI 1.2-2.7; severe albuminuria HR 4.3, 95% CI 2.7-7.0). Albuminuria was also associated with survival following radical and partial nephrectomy.In patients undergoing radical or partial nephrectomy the severity of albuminuria can stratify risk of progressive chronic kidney disease.

Prostate cancer is the most commonly diagnosed non-cutaneous malignancy in men in the United States (US).1 While the majority of prostate cancers in the US are diagnosed at the localized stage,1 their clinical course varies widely from indolent to fatal. To facilitate prognostication and disease management, localized prostate cancer can be further classified into low, intermediate, and high risk of progression based on Gleason score, stage, and prostate-specific antigen (PSA) value at diagnosis. Many men harbor low-risk disease that will remain clinically insignificant throughout their lifetime. Recognizing that over-treatment of these men would expose them to potentially serious morbidity without deriving any benefit from immediate treatment, major guidelines recommend active surveillance for initial management of this group.2,3 However, in contrast to those with low-risk disease, men with high-risk tumors have a significant risk of symptomatic progression and death from prostate cancer.4,5 In this context, definitive therapy has been shown to decrease disease-specific mortality,6 and the National Comprehensive Cancer Network guidelines recommend radiation therapy with 2–3 years of androgen deprivation therapy, radiation therapy with brachytherapy with or without 2–3 years of androgen deprivation therapy, or radical prostatectomy with pelvic lymph node dissection as initial treatment of all high-risk localized prostate cancer, barring contraindications2. Despite these recommendations, under-treatment of high-risk disease has been noted in specific groups of patients including the otherwise healthy elderly,7 the un- and under-insured,8,9 and non-White minorities.8–10 Latinos comprise the nation’s largest minority group,11 yet there is a paucity of information regarding prostate cancer treatment in this population. Of concern are reports of an emerging treatment disparity in Latinos with high-risk disease.10 California is home to almost 15 million Latinos, representing 39% of the state’s population, and its largest ethnic group.12 We leveraged the large size of the Latino population and the wealth of data in the California Cancer Registry (CCR) to examine “real-world” treatment patterns and factors affecting the receipt of definitive treatment for high-risk prostate cancer among understudied Latino men.

Background It can be challenging to predict the risk of biochemical recurrence (BR) during follow-up after radical prostatectomy (RP) in men who have undetectable prostate-specific antigen (PSA), even years after surgery. Objective To establish and validate a contemporary nomogram that predicts the absolute risk of BR every year after RP in men with undetectable PSA while accounting for competing risks of death. Design, setting, and participants A total of 3746 patients from Rigshospitalet (Copenhagen, Denmark) and Stanford Urology (Stanford, CA, USA) who underwent RP between 1995 and 2013 were included. Outcome measurements and statistical analysis Time to BR was defined as the first PSA result ≥0.2 ng/ml. BR risk was computed using multiple cause-specific Cox regression including preoperative PSA, pT category, RP Gleason score (GS), and surgical margin (R) status. Death without BR was considered a competing event. The nomogram presents the future risk of BR for a man who is alive and without BR at the time of follow-up. Validation assessed the discrimination and accuracy using time-dependent area under the curve and Brier scores. Results and limitations The nomogram predicts risk of BR up to 12 yr after RP at an individual level. As example, the risk of BR for a man with pT3a, R−, GS 3 + 4, and preoperative PSA ≤10 ng/ml followed for 5 yr with undetectable PSA is 18% for the next 5 yr. External validation demonstrated both high accuracy and discrimination. The CPC Risk Calculator is available as a free Android and iOS App. Declining discrimination and accuracy after 7 yr of follow-up is the main limitation. Conclusions This nomogram can be used as a tool to inform men with undetectable PSA during follow-up after RP about their future risk of BR, and may aid in decisions on the necessity for further follow-up. The nomogram is the first to be available as a free app. Patient summary We developed an easily interpretable nomogram to evaluate the risk of prostate-specific antigen elevation (cancer recurrence) following complete removal of the prostate (radical prostatectomy). The tool can aid both physicians and patients in evaluating the future risk of cancer recurrence during follow-up after surgery. The model is available as a free mobile app that can be downloaded from the App Store.

BACKGROUND: Many patients who are on active surveillance (AS) for prostate cancer will have surveillance prostate needle biopsies (PNBs) without any cancer evident. OBJECTIVE: To define the association between negative surveillance PNBs and risk of reclassification on AS. DESIGN, SETTING, AND PARTICIPANTS: All men were enrolled in the Canary Prostate Active Surveillance Study (PASS) between 2008 and 2016. Men were included if they had Gleason ≤3 + 4 prostate cancer and

This study aims to evaluate whether cancer treatments differ in infertile men compared to men who have undergone vasectomy and age-matched controls. We analyzed subjects from the Truven Health MarketScan Claims database from 2001 to 2009. Infertile men were identified through diagnosis and treatment codes. Comparison groups included vasectomized men and an age-matched cohort who were not infertile and had not undergone vasectomy. We considered cancer types previously associated with infertility that were diagnosed after the diagnosis of infertility. The treatment regimens were determined based on the presence of claims with CPT codes for chemotherapy (CTX), radiation (RTX) or surgical treatment (ST) for each entity in all study groups. Cases with multimodal treatments were also identified. As a result, CTX was similarly distributed among the infertile, vasectomized, and control groups. In contrast, RTX treatment length was shorter in infertile men. The frequency of multimodal treatment (i.e., radiation and chemotherapy) was twofold lower in men with infertility compared to other men. By focusing on treatment patterns for each cancer type among these groups, the duration of RTX and CTX was shorter in infertile men diagnosed with NHL compared to controls. We conclude that Infertile men diagnosed with cancer and specific cancer types experience different treatment courses, with shorter RTX and less combined RTX/CTX compared to fertile and vasectomized men. These differences could reflect differences in stage at presentation, biological behavior, or treatment responses in infertile men.

The comparative effectiveness of partial nephrectomy versus radical nephrectomy to preserve kidney function has not been well established. We determined the risk of clinically significant (stage 4 and higher) CKD after radical or partial nephrectomy among veterans treated for kidney cancer in the Veterans Health Administration (2001–2013). Among patients with preoperative eGFR≥30 ml/min per 1.73 m2, the incidence of CKD stage 4 or higher after radical (n=9759) or partial nephrectomy (n=4370) was 7.9% overall. The median time to stage 4 or higher CKD after surgery was 5 months, after which few patients progressed. In propensity score–matched cohorts, partial nephrectomy associated with a significantly lower relative risk of incident CKD stage 4 or higher (hazard ratio, 0.34; 95% confidence interval [95% CI], 0.26 to 0.43, versus radical nephrectomy). In a parallel analysis of patients with normal or near-normal preoperative kidney function (eGFR≥60 ml/min per 1.73 m2), partial nephrectomy was also associated with a significantly lower relative risk of incident CKD stage 3b or higher (hazard ratio, 0.15; 95% CI, 0.11 to 0.19, versus radical nephrectomy) in propensity score–matched cohorts. Competing risk regression models produced consistent results. Finally, patients treated with a partial nephrectomy had reduced risk of mortality (hazard ratio, 0.55; 95% CI, 0.49 to 0.62). In conclusion, compared with radical nephrectomy, partial nephrectomy was associated with a marked reduction in the incidence of clinically significant CKD and with enhanced survival. Postoperative decline in kidney function occurred mainly in the first year after surgery and appeared stable over time.

Background Diagnosis of Gleason 6 prostate cancer can leave uncertainty about the presence of undetected aggressive disease. Objective To evaluate the utility of a four kallikrein (4K) panel in predicting the presence of high-grade cancer in men on active surveillance. Design, setting, and participants Plasma collected before the first and subsequent surveillance biopsies was assessed for 718 men prospectively enrolled in the multi-institutional Canary PASS trial. Biopsy data were split 2:1 into training and test sets. We developed statistical models that included clinical information and either the 4Kpanel or serum prostate-specific antigen (PSA). Outcome measurements and statistical analysis The endpoint was reclassification to Gleason ≥7. We used receiver operating characteristic (ROC) curve analyses and area under the curve (AUC) to assess discriminatory capacity, and decision curve analysis (DCA) to report clinical net benefit. Results and limitations Significant predictors for reclassification were 4Kpanel (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.31–1.81) or PSA (OR 2.11, 95% CI 1.53–2.91), ≥20% cores positive (OR 2.10, 95% CI 1.33–3.32), two or more prior negative biopsies (OR 0.19, 95% CI 0.04–0.85), prostate volume (OR 0.47, 95% CI 0.31–0.70), and body mass index (OR 1.09, 95% CI 1.04–1.14). ROC curve analysis comparing 4K and base models indicated that the 4Kpanel improved accuracy for predicting reclassification (AUC 0.78 vs 0.74) at the first surveillance biopsy. Both models performed comparably for prediction of reclassification at subsequent biopsies (AUC 0.75 vs 0.76). In DCA, both models showed higher net benefit compared to biopsy-all and biopsy-none strategies. Limitations include the single cohort nature of the study and the small numbers; results should be validated in another cohort before clinical use. Conclusions The 4Kpanel provided incremental value over routine clinical information in predicting high-grade cancer in the first biopsy after diagnosis. The 4Kpanel did not add predictive value to the base model at subsequent surveillance biopsies. Patient summary Active surveillance is a management strategy for many low-grade prostate cancers. Repeat biopsies monitor for previously undetected high-grade cancer. We show that a model with clinical variables, including a panel of four kallikreins, indicates the presence of high-grade cancer before a biopsy is performed.

During active surveillance for localized prostate cancer, the timing of the first surveillance biopsy varies. We analyzed the Canary PASS (Prostate Cancer Active Surveillance Study) to determine biopsy timing influence on rates of prostate cancer adverse reclassification at the first active surveillance biopsy.Of 1,085 participants in PASS, 421 had fewer than 34% of cores involved with cancer and Gleason sum 6 or less, and thereafter underwent on-study active surveillance biopsy. Reclassification was defined as an increase in Gleason sum and/or 34% or more of cores with prostate cancer. First active surveillance biopsy reclassification rates were categorized as less than 8, 8 to 13 and greater than 13 months after diagnosis. Multivariable logistic regression determined association between reclassification and first biopsy timing.Of 421 men, 89 (21.1%) experienced reclassification at the first active surveillance biopsy. Median time from prostate cancer diagnosis to first active surveillance biopsy was 11 months (IQR 7.8-13.8). Reclassification rates at less than 8, 8 to 13 and greater than 13 months were 24%, 19% and 22% (p = 0.65). On multivariable analysis, compared to men biopsied at less than 8 months the OR of reclassification at 8 to 13 and greater than 13 months were 0.88 (95% CI 0.5,1.6) and 0.95 (95% CI 0.5,1.9), respectively. Prostate specific antigen density 0.15 or greater (referent less than 0.15, OR 1.9, 95% CI 1.1, 4.1) and body mass index 35 kg/mTiming of the first active surveillance biopsy was not associated with increased adverse reclassification but prostate specific antigen density and body mass index were. In low risk patients on active surveillance, it may be reasonable to perform the first active surveillance biopsy at a later time, reducing the overall cost and morbidity of active surveillance.

// Xue Gong 1,2 , Zurab Siprashvili 3 , Okyaz Eminaga 1,4 , Zhewei Shen 2 , Yusuke Sato 5,6 , Haruki Kume 6 , Yukio Homma 6 , Seishi Ogawa 5 , Paul A. Khavari 3 , Jonathan R. Pollack 2 and James D. Brooks 1 1 Department of Urology, School of Medicine, Stanford University, Stanford, California, USA 2 Department of Pathology, School of Medicine, Stanford University, Stanford, California, USA 3 Program in Epithelial Biology, School of Medicine, Stanford University, Stanford, California, USA 4 Department of Urology, University Hospital Cologne, Cologne, Germany 5 Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto, Japan 6 Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan Correspondence to: Jonathan R. Pollack, email: // James D. Brooks, email: // Keywords : lincRNA, renal cell carcinoma, kidney cancer, biomarker, prognostication Received : November 04, 2016 Accepted : January 24, 2017 Published : February 24, 2017 Abstract Clear cell renal cell carcinomas (ccRCC) show a broad range of clinical behavior, and prognostic biomarkers are needed to stratify patients for appropriate management. We sought to determine whether long intergenic non-coding RNAs (lincRNAs) might predict patient survival. Candidate prognostic lincRNAs were identified by mining The Cancer Genome Atlas (TCGA) transcriptome (RNA-seq) data on 466 ccRCC cases (randomized into discovery and validation sets) annotated for ~21,000 lncRNAs. A previously uncharacterized lincRNA, SLINKY (Survival-predictive LINcRNA in KidneY cancer), was the top-ranked prognostic lincRNA, and validated in an independent University of Tokyo cohort ( P =0.004). In multivariable analysis, SLINKY expression predicted overall survival independent of tumor stage and grade [TCGA HR=3.5 (CI, 2.2-5.7), P < 0.001; Tokyo HR=8.4 (CI, 1.8-40.2), P = 0.007], and by decision tree, ROC and decision curve analysis, added independent prognostic value. In ccRCC cell lines, SLINKY knockdown reduced cancer cell proliferation (with cell-cycle G 1 arrest) and induced transcriptome changes enriched for cell proliferation and survival processes. Notably, the genes affected by SLINKY knockdown in cell lines were themselves prognostic and correlated with SLINKY expression in the ccRCC patient samples. From a screen for binding partners, we identified direct binding of SLINKY to Heterogeneous Nuclear Ribonucleoprotein K (HNRNPK), whose knockdown recapitulated SLINKY knockdown phenotypes. Thus, SLINKY is a robust prognostic biomarker in ccRCC, where it functions possibly together with HNRNPK in cancer cell proliferation.

Hispanic men in the USA experience the second-highest incidence rate of testicular germ cell tumors (TGCTs), behind non-Hispanic (NH) White men, and have experienced steep increases in TGCT in recent decades. It is unknown whether increases in incidence differ according to neighborhood sociodemographic factors. We conducted a population-based study of n = 3759 Hispanic and n = 8469 NH White men (n = 12,228 total) diagnosed with TGCT in California during the three most recent pericensal periods. We calculated incidence rates according to neighborhood socioeconomic status (nSES) and among Hispanics, according to ethnic enclave. We calculated incidence rate ratios to compare rates across nSES and ethnic enclave and to examine changes in rates over pericensal time periods according to these neighborhood factors for major histologic types (i.e., seminoma and nonseminoma). Hispanic men residing in high SES, compared to low SES, neighborhoods had greater incidence of seminoma and nonseminoma testicular cancer across pericensal periods, as did Hispanic men in low enclave (less ethnic), compared to high enclave, neighborhoods. Between the periods 1998–2002 and 2008–2012, Hispanic men residing in low SES neighborhoods experienced a 39% increased incidence of seminoma, while those residing in low and middle SES neighborhoods experienced 87% and 48% increased incidence of nonseminoma, respectively. While TGCT incidence has increased among all Hispanic men, incidence increases appear to be driven disproportionately by those residing in lower SES and lower enclave neighborhoods, particularly for nonseminoma.

Purpose Accurate life expectancy estimates are required to inform prostate cancer treatment decisions. However, few models are specific to the population served or easily implemented in a clinical setting. We sought to create life expectancy estimates specific to Veterans diagnosed with prostate cancer. Materials and methods Using national Veterans Health Administration electronic health records, we identified Veterans diagnosed with prostate cancer between 2000 and 2015. We abstracted demographics, comorbidities, oncologic staging, and treatment information. We fit Cox Proportional Hazards models to determine the impact of age, comorbidity, cancer risk, and race on survival. We stratified life expectancy estimates by age, comorbidity and cancer stage. Results Our analytic cohort included 145,678 patients. Survival modeling demonstrated the importance of age and comorbidity across all cancer risk categories. Life expectancy estimates generated from age and comorbidity data were predictive of overall survival (C-index 0.676, 95% CI 0.674–0.679) and visualized using Kaplan-Meier plots and heatmaps stratified by age and comorbidity. Separate life expectancy estimates were generated for patients with localized or advanced disease. These life expectancy estimates calibrate well across prostate cancer risk categories. Conclusions Life expectancy estimates are essential to providing patient-centered prostate cancer care. We developed accessible life expectancy estimation tools for Veterans diagnosed with prostate cancer that can be used in routine clinical practice to inform medical-decision making.

Imaging technologies that simultaneously provide anatomical, functional, and molecular information are emerging as an attractive choice for disease screening and management. Since the 1980s, transrectal ultrasound (TRUS) has been routinely used to visualize prostatic anatomy and guide needle biopsy, despite limited specificity. Photoacoustic imaging (PAI) provides functional and molecular information at ultrasonic resolution based on optical absorption. Combining the strengths of TRUS and PAI approaches, we report the development and bench-to-bedside translation of an integrated TRUS and photoacoustic (TRUSPA) device. TRUSPA uses a miniaturized capacitive micromachined ultrasonic transducer array for simultaneous imaging of anatomical and molecular optical contrasts [intrinsic: hemoglobin; extrinsic: intravenous indocyanine green (ICG)] of the human prostate. Hemoglobin absorption mapped vascularity of the prostate and surroundings, whereas ICG absorption enhanced the intraprostatic photoacoustic contrast. Future work using the TRUSPA device for biomarker-specific molecular imaging may enable a fundamentally new approach to prostate cancer diagnosis, prognostication, and therapeutic monitoring.

Background: Efficient capture of routine clinical care and patient outcomes is needed at a population-level, as is evidence on important treatment-related side effects and their effect on well-being and clinical outcomes. The increasing availability of electronic health records (EHR) offers new opportunities to generate population-level patient-centered evidence on oncologic care that can better guide treatment decisions and patient-valued care. Methods: This study includes patients seeking care at an academic medical center, 2008 to 2018. Digital data sources are combined to address missingness, inaccuracy, and noise common to EHR data. Clinical concepts were identified and extracted from EHR unstructured data using natural language processing (NLP) and machine/deep learning techniques. All models are trained, tested, and validated on independent data samples using standard metrics. Results: We provide use cases for using EHR data to assess guideline adherence and quality measurements among patients with cancer. Pretreatment assessment was evaluated by guideline adherence and quality metrics for cancer staging metrics. Our studies in perioperative quality focused on medications administered and guideline adherence. Patient outcomes included treatment-related side effects and patient-reported outcomes. Conclusions: Advanced technologies applied to EHRs present opportunities to advance population-level quality assessment, to learn from routinely collected clinical data for personalized treatment guidelines, and to augment epidemiologic and population health studies. The effective use of digital data can inform patient-valued care, quality initiatives, and policy guidelines. Impact: A comprehensive set of health data analyzed with advanced technologies results in a unique resource that facilitates wide-ranging, innovative, and impactful research on prostate cancer. This work demonstrates new ways to use the EHRs and technology to advance epidemiologic studies and benefit oncologic care. See all articles in this CEBP Focus section, “Modernizing Population Science.”

PurposeTo develop a magneto-nanosensor (MNS) based multiplex assay to measure protein and autoantibody biomarkers from human serum for prostate cancer (CaP) diagnosis.Materials and methodsA 4-panel MNS autoantibody assay and a MNS protein assay were developed and optimized in our labs. Using these assays, serum concentration of six biomarkers including prostate-specific antigen (PSA) protein, free/total PSA ratio, as well as four autoantibodies against Parkinson disease 7 (PARK7), TAR DNA-binding protein 43 (TARDBP), Talin 1 (TLN1), and Caldesmon 1 (CALD1) and were analyzed. Human serum samples from 99 patients (50 with non-cancer and 49 with clinically localized CaP) were evaluated.ResultsThe MNS assay showed excellent performance characteristics and no cross-reactivity. All autoantibody assays showed a statistically significant difference between CaP and non-cancer samples except for PARK7. The most significant difference was the combination of the four autoantibodies as a panel in addition to the free/total PSA ratio. This combination had the highest area under the curve (AUC)- 0.916 in ROC analysis.ConclusionsOur results suggest that this autoantibody panel along with PSA and free PSA have potential to segregate patients without cancer from those with prostate cancer with higher sensitivity and specificity than PSA alone.

ObjectivesTo develop and test a method for automatic assessment of a quality metric, provider-documented pretreatment digital rectal examination (DRE), using the outputs of a natural language processing (NLP) framework.SettingAn electronic health records (EHR)-based prostate cancer data warehouse was used to identify patients and associated clinical notes from 1 January 2005 to 31 December 2017. Using a previously developed natural language processing pipeline, we classified DRE assessment as documented (currently or historically performed), deferred (or suggested as a future examination) and refused.Primary and secondary outcome measuresWe investigated the quality metric performance, documentation 6 months before treatment and identified patient and clinical factors associated with metric performance.ResultsThe cohort included 7215 patients with prostate cancer and 426 227 unique clinical notes associated with pretreatment encounters. DREs of 5958 (82.6%) patients were documented and 1257 (17.4%) of patients did not have a DRE documented in the EHR. A total of 3742 (51.9%) patient DREs were documented within 6 months prior to treatment, meeting the quality metric. Patients with private insurance had a higher rate of DRE 6 months prior to starting treatment as compared with Medicaid-based or Medicare-based payors (77.3%vs69.5%, p=0.001). Patients undergoing chemotherapy, radiation therapy or surgery as the first line of treatment were more likely to have a documented DRE 6 months prior to treatment.ConclusionEHRs contain valuable unstructured information and with NLP, it is feasible to accurately and efficiently identify quality metrics with current documentation clinician workflow.

Background Patients meeting criteria for intervention of carotid stenosis with a history of prior cervical radiation or neck dissection are considered “high risk” for carotid endarterectomy. This is a well-established indication for carotid artery stenting (CAS). The long-term outcomes of CAS in this population are less frequently published in the literature but are poor. The purpose of this study was to review long-term results of CAS in veteran patients with a prior history of treatment for head and/or neck cancer. Methods This is a retrospective review of a veteran patient population from 1998 to 2016. All patients at our institution with a prior history of treatment for head and/or neck cancer who underwent CAS were included in the analysis. During this time period, 44 patients met inclusion criteria and were treated with 57 carotid stenting interventions. The Kaplan-Meier analysis was used to determine survival and primary patency. The secondary aims were to analyze early outcomes and to identify predictive risk factors for mortality and reintervention. Results The mean follow-up was 42.9 ± 36.6 months. The cumulative survival at 1, 5, and 10 years was 91%, 67%, and 48%, respectively. The primary patency at 1, 5, and 10 years was 95%, 86%, and 86%, respectively. The reintervention rate was 11% (n = 6) with an assisted primary patency rate of 100%. No neurologic events occurred within 30 days. There were 3 strokes in late follow-up and no stroke-related deaths. Eighteen patients (41%) died during the follow-up period, 15 of whom died during the first 5 years of follow-up. Ten (66%) of those patients died of recurrent or active index cancer. On univariate analysis, tumor, node, metastasis stage IV was significantly associated with death (P = 0.02). Multivariate models were not statistically significant for predicting mortality or reintervention Conclusions On the basis of the results in this series, CAS can be performed in these patients with low long-term rates of neurologic events and need for reintervention. However, the survival of patients with head and neck cancer undergoing CAS in this cohort is poor, which is consistent with other published series of patients undergoing CAS for head/neck cancer with at least 5-year follow-up. In this specific patient population, a more critical analysis of the patient's overall prognosis, especially as related to cancer, should be undertaken before offering CAS.

Background The shift toward value-based care in the United States emphasizes the role of quality measures in payment models. Many diseases, such as prostate cancer, have a proliferation of quality measures, resulting in resource burden and physician burnout. This study aimed to identify and summarize proposed prostate cancer quality measures and describe their frequency and use in peer-reviewed literature. Methods The PubMed database was used to identify quality measures relevant to prostate cancer care, and included articles in English through April 2018. A gray literature search for other documents was also conducted. After the selection process of the pertinent articles, measure characteristics were abstracted, and uses were summarized for the 10 most frequently utilized measures in the literature. Results A total of 26 articles were identified for review. Of the 71 proposed prostate cancer quality measures, only 47 were used, and less than 10% of these were endorsed by the National Quality Forum. Process measures were most frequently reported (84.5%). Only 6 outcome measures (8.5%) were proposed—none of which were among the most frequently utilized. Conclusion Although a high number of proposed prostate cancer quality measures are reported in the literature, few were assessed, and the majority of these were non-endorsed process measures. Process measures were most commonly assessed; outcome measures were rarely evaluated. In a step to close the quality chasm, a "top 5" core set of quality measures for prostate cancer care, including structure, process, and outcomes measures, is suggested. Future studies should consider this comprehensive set of quality measures.