Disparities in heart failure between White, Black, and Hispanic young adults: insights from the National Health and Nutrition Examination Survey.

BACKGROUND: The prevalence of heart failure (HF) is increasing among young adults in the United States with pervasive racial and ethnic differences in this population. OBJECTIVE: To evaluate contemporary associations between race and ethnicity, clinical comorbidities, and outcomes among young to middle-aged adults with HF. METHODS: A retrospective analysis was performed using the National Health and Nutrition Examination Survey. All participants with a self-report of HF aged 20-64 years from 2005 to 2018 were included and stratified by race and ethnicity [non-Hispanic (NH) Whites, NH Blacks, and Hispanics]. Data on baseline characteristics including age, sex, marital status, citizenship, education level, body mass index, insurance, waist circumference, cigarette smoking, marijuana use, and relevant clinical comorbidities were included. Weighted logistic regression was performed to estimate adjusted odds ratios (aOR) to determine the association of race and ethnicity with HF. Cox proportional-hazards models were used to assess the association of race and ethnicity with all-cause and cardiac mortality. RESULTS: A total of 1,940,447 young to middle-aged adults had self-reported HF between 2005 and 2018, of whom 61% were NH White, 40% were NH Black, and 22% were Hispanic. When compared with NH White adults, NH Black adults had higher odds of HF adjusted for age, sex, insurance status, marital status, education level, citizenship status, and clinical comorbidities (adjusted aOR 2.63, 95% CI: 1.71-4.05, p < 0.001). There was no significant difference in the odds of HF between Hispanic and NH White adults (aOR 1.18, 95% CI: 0.64-2.18, p = 0.585). NH Black adults had higher mean systolic and diastolic blood pressure, and a comparable or lower burden of cardiovascular and non-cardiovascular clinical comorbidities compared with NH White and Hispanic adults. No statistical significance was noted by race and ethnicity for all-cause and cardiac mortality during a follow-up of 5 years. CONCLUSION: NH Black young to middle-aged adults were more likely to have HF which may be related to higher blood pressure given the largely similar burden of clinically relevant comorbidities compared with other racial and ethnic groups.

A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis.

BACKGROUND: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. METHODS: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. RESULTS: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. CONCLUSIONS: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.

2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.

AIM: The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease." METHODS: A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE: This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.

AIM: The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease." METHODS: A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE: This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

Prevalence of Hospital-Onset Bacteremia Pre- and Post-Implementation of a Needleless Blood Sampling Device From Existing Peripheral Catheters.

Repeated access of peripheral intravenous (IV) devices theoretically increases the risk of bacterial exposure. PIVO™ (VelanoVascular) is a needleless, single-use device that enables blood sampling from an existing peripheral IV. The goal of this retrospective observational exploratory study was to evaluate the influence of PIVO use on rates of hospital-onset bacteremia and fungemia (HOB) by comparing HOB rates in the year before and after PIVO introduction in hospitals implementing PIVO and over similar time periods in "control" hospitals with no PIVO. Two hospitals implementing PIVO (Hospital 1, a large community hospital; Hospital 2, a tertiary oncology center), and 71 control hospitals were included. During the 1-year period before and after PIVO introduction, HOB rates decreased in hospitals 1 and 2 by 31.9% and 41.8%, respectively. Control hospitals that did not use PIVO had a 12.4% decrease in HOB rates. Multivariable logistic regression analyses found that PIVO was associated with a lower risk (Hospital 1 odds ratio [OR]: 0.63; 95% CI, 0.42-0.94) or no change (Hospital 2 OR: 1.05; 95% CI, 0.72-1.52) in HOB rates. Control hospitals also showed no change in HOB rates between the 2 time periods. These data do not support concerns about increased risk of bacteremia with PIVO.

Nickel-Catalyzed Sulfonylation of Aryl Bromides Enabled by Potassium Metabisulfite as a Uniquely Effective SO2 Surrogate.

The development and mechanistic investigation of a nickel-catalyzed sulfonylation of aryl bromides is disclosed. The reaction proceeds in good yields for a variety of substrates and utilizes an inexpensive, stench-free, inorganic sulfur salt (K2 S2 O5 ) as a uniquely effective SO2 surrogate. The active oxidative addition complex was synthesized, isolated, and fully characterized by a combination of NMR spectroscopy and X-ray crystallography analysis. The use of the isolated oxidative addition complex in both stoichiometric and catalytic reactions revealed that SO2 insertion occurs via dissolved SO2 , likely released upon thermal decomposition of K2 S2 O5 . Key to the success of the reaction is the role of K2 S2 O5 as a reservoir of SO2 that is slowly released, thus preventing catalyst poisoning.

High continuous positive airway pressures versus non-invasive positive pressure ventilation in preterm neonates: protocol for a multicentre pilot randomised controlled trial.

INTRODUCTION: Low pressure nasal continuous positive airway pressure (nCPAP) has long been the mainstay of non-invasive respiratory support for preterm neonates, at a constant distending pressure of 5-8 cmH2O. When traditional nCPAP pressures are insufficient, other modes including nasal intermittent positive pressure ventilation (NIPPV) are used. In recent years, high nCPAP pressures (≥9 cmH2O) have also emerged as an alternative. However, the comparative benefits and risks of these modalities remain unknown. METHODS AND ANALYSIS: In this multicentre pilot randomised controlled trial, infants <29 weeks' gestational age (GA) who either: (A) fail treatment with traditional nCPAP or (B) being extubated from invasive mechanical ventilation with mean airway pressure ≥10 cmH2O, will be randomised to receive either high nCPAP (positive end-expiratory pressure 9-15 cmH2O) or NIPPV (target mean Paw 9-15 cmH2O). Primary outcome is feasibility of the conduct of a larger, definitive trial as assessed by rates of recruitment and protocol violations. The main secondary outcome is failure of assigned treatment within 7 days postrandomisation. Multiple other clinical outcomes including bronchopulmonary dysplasia will be ascertained. All randomised participants will be analysed using intention to treat. Baseline and demographic variables as well as outcomes will be summarised and compared using univariate analyses, and a p<0.05 will be considered significant. ETHICS AND DISSEMINATION: The trial has been approved by the respective research ethics boards at each institution (McMaster Children's Hospital: Hamilton integrated REB approval #2113; Royal Alexandra Hospital: Health Research Ethics Board approval ID Pro00090244; Westmead Hospital: Human Research Ethics Committee approval ID 2022/ETH01343). Written, informed consent will be obtained from all parents/guardians prior to study enrolment. The findings of this pilot study will be disseminated via presentations at national and international conferences and via publication in a peer-reviewed journal. Social media platforms including Twitter will also be used to generate awareness. TRIAL REGISTRATION NUMBER: NCT03512158.

K-RAS Associated Gene-Mutation-Based Algorithm for Prediction of Treatment Response of Patients with Subtypes of Breast Cancer and Especially Triple-Negative Cancer.

Purpose: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision. Methods: Random Forest ML was applied to screen the algorithms of various combinations of gene mutation profiles of primary tumors at diagnosis using a TCGA Cohort (n = 399) with up to 150 months follow-up as a training set and validated in a MSK Cohort (n = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2−) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan−Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses. Results: A novel algorithm termed the 12-Gene Algorithm based on mutation profiles of KRAS, PIK3CA, MAP3K1, MAP2K4, PTEN, TP53, CDH1, GATA3, KMT2C, ARID1A, RunX1, and ESR1, was identified. The performance of this algorithm to distinguish non-progressed (responder) vs. progressed (non-responder) to treatment in the TCGA Cohort as determined using AUC was 0.96 (95% CI 0.94−0.98). It predicted progression-free survival (PFS) with hazard ratio (HR) of 21.6 (95% CI 11.3−41.5) (p < 0.0001) in all patients. The algorithm predicted PFS in the triple-negative subgroup with HR of 19.3 (95% CI 3.7−101.3) (n = 42, p = 0.000). The 12-Gene Algorithm was validated in the MSK Cohort with a similar AUC of 0.97 (95% CI 0.96−0.98) to distinguish responder vs. non-responder patients, and had a HR of 18.6 (95% CI 4.4−79.2) to predict PFS in the triple-negative subgroup (n = 75, p < 0.0001). Conclusions: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality.

A Unified Strategy to Fluorinated Nucleoside Analogues Via an Electrophilic Manifold.

Herein, we present a strategy for the preparation of 3'-fluorinated nucleoside analogues via the aminocatalytic, electrophilic fluorination of readily accessible and bench-stable 2'-ketonucleosides. Initially developed to facilitate the manufacture of 3'-fluoroguanosine (3'-FG)─a substructure of anticancer therapeutic MK-1454─this strategy has been extended to the synthesis of a variety of 3'-fluoronucleosides. Finally, we demonstrate the utility of the 2'-ketonucleoside synthon as a platform for further diversification and suggest that this methodology should be broadly applicable to the discovery of novel nucleoside analogues.

Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients.

Purpose: Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors. Methods: Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters. Results: A novel 7-Gene Algorithm based on mutation profiles of seven KRAS-associated genes was identified. The algorithm was able to distinguish non-progressed (responder) vs. progressed (non-responder) patients with AUC of 0.97 and had predictive power for PFS with a hazard ratio (HR) of 16.9 (p < 0.001) in the MSK cohort. The predictive power of this algorithm for PFS was more pronounced in mCRC (HR = 16.9, p < 0.001, n = 388). Similarly, in the TCGA validation cohort, the algorithm had AUC of 0.98 and a significant predictive power for PFS (p < 0.001). Conclusion: The novel 7-Gene Algorithm can be further developed as a biomarker model for prediction of treatment response in mCRC patients to improve personalized therapies.

Impact of a Rheumatology Clinic Protocol on Tobacco Cessation Quit Line Referrals.

OBJECTIVE: Smoking increases cardiopulmonary and rheumatic disease risk, yet tobacco cessation intervention is rare in rheumatology clinics. This study aimed to implement a rheumatology staff-driven protocol, Quit Connect, to increase the rate of electronic referrals (e-referrals) to free, state-run tobacco quit lines. METHODS: We conducted a quasi-experimental cohort study of Quit Connect at 3 rheumatology clinics comparing tobacco quit line referrals from 4 baseline years to referrals during a 6-month intervention period. Nurses and medical assistants were trained to use 2 standardized electronic health record (EHR) prompts to check readiness to quit smoking within 30 days, advise cessation, and connect patients using tobacco quit line e-referral orders. Our objective was to use EHR data to examine the primary outcome of tobacco quit line referrals using pre/post design. RESULTS: Across 54,090 pre- and post-protocol rheumatology clinic visits, 4,601 were with current smokers. We compared outcomes between 4,078 eligible pre-implementation visits and 523 intervention period visits. Post-implementation, the odds of tobacco quit line referral were 26-fold higher compared to our pre-implementation rate (unadjusted odds ratio [OR] 26 [95% confidence interval (95% CI) 6-106]). Adjusted odds of checking readiness to quit in the next 30 days increased over 100-fold compared to pre-implementation (adjusted OR 132 [95% CI 99-177]). Intervention led to e-referrals for 71% of quit-ready patients in <90 seconds; 24% of referred patients reported a quit attempt. CONCLUSION: Implementing Quit Connect in rheumatology clinics was feasible and improved referrals to a state-run tobacco quit line. Given the importance of smoking cessation to reduce cardiopulmonary and rheumatic disease risk, future studies should investigate disseminating cessation protocols like Quit Connect that leverage tobacco quit lines.

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients.

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available. Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups. Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups. Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

Ten things to know about ten cardiovascular disease risk factors.

Given rapid advancements in medical science, it is often challenging for the busy clinician to remain up-to-date on the fundamental and multifaceted aspects of preventive cardiology and maintain awareness of the latest guidelines applicable to cardiovascular disease (CVD) risk factors. The "American Society for Preventive Cardiology (ASPC) Top Ten CVD Risk Factors 2021 Update" is a summary document (updated yearly) regarding CVD risk factors. This "ASPC Top Ten CVD Risk Factors 2021 Update" summary document reflects the perspective of the section authors regarding ten things to know about ten sentinel CVD risk factors. It also includes quick access to sentinel references (applicable guidelines and select reviews) for each CVD risk factor section. The ten CVD risk factors include unhealthful nutrition, physical inactivity, dyslipidemia, hyperglycemia, high blood pressure, obesity, considerations of select populations (older age, race/ethnicity, and sex differences), thrombosis/smoking, kidney dysfunction and genetics/familial hypercholesterolemia. For the individual patient, other CVD risk factors may be relevant, beyond the CVD risk factors discussed here. However, it is the intent of the "ASPC Top Ten CVD Risk Factors 2021 Update" to provide a succinct overview of things to know about ten common CVD risk factors applicable to preventive cardiology.

Interaction of RIPK1 and A20 modulates MAPK signaling in murine acetaminophen toxicity.

Acetaminophen (APAP)-induced liver necrosis is a form of regulated cell death (RCD) in which APAP activates the mitogen-activated protein kinases (MAPKs) and specifically the c-Jun-N-terminal kinase (JNK) pathway, leading to necrotic cell death. Previously, we have shown that receptor interacting protein kinase-1 (RIPK1) knockdown is also protective against APAP RCD upstream of JNK. However, whether the kinase or platform function of RIPK1 is involved in APAP RCD is not known. To answer this question, we used genetic mouse models of targeted hepatocyte RIPK1 knockout (RIPK1HepCKO) or kinase dead knock-in (RIPK1D138N) and adult hepatocyte specific knockout of the cytoprotective protein A20 (A20HepCKO), known to interact with RIPK1, to study its potential involvement in MAPK signaling. We observed no difference in injury between WT and RIPK1D138N mice post APAP. However, RIPK1HepCKO was protective. We found that RIPK1HepCKO mice had attenuated pJNK activation, while A20 was simultaneously upregulated. Conversely, A20HepCKO markedly worsened liver injury from APAP. Mechanistically, we observed a significant upregulation of apoptosis signal-regulating kinase 1 (ASK1) and increased JNK activation in A20HepCKO mice compared with littermate controls. We also demonstrated that A20 coimmunoprecipitated (co-IP) with both RIPK1 and ASK1, and that in the presence of RIPK1, there was less A20-ASK1 association than in its absence. We conclude that the kinase-independent platform function of RIPK1 is involved in APAP toxicity. Adult RIPK1HepCKO mice are protected against APAP by upregulating A20 and attenuating JNK signaling through ASK1, conversely, A20HepCKO worsens injury from APAP.

Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification.

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939-0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964-0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879-0.763) for PSA and 0.860 (95% CI 0.910-0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968-0.878) than PSA [AUC of 0.773 (95% CI 0.852-0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854-0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892-0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706-0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up.

BACKGROUND: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. METHODS: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. RESULTS: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. CONCLUSIONS: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

Association of Cardiovascular Risk Factors with Cerebral Perfusion in Whites and African Americans.

BACKGROUND: Midlife cardiovascular risk factors increase risk for Alzheimer's disease (AD). Despite disproportionately high cardiovascular disease and dementia rates, African Americans are under-represented in studies of AD risk and research-based guidance on targeting vascular risk factors is lacking. OBJECTIVE: This study investigated relationships between specific cardiovascular risk factors and cerebral perfusion in White and African American adults enriched for AD risk. METHODS: Participants included 397 cognitively unimpaired White (n = 330) and African American (n = 67) adults enrolled in the Wisconsin Alzheimer's Disease Research Center who underwent pseudo-continuous arterial spin labeling MRI. Multiple linear regression models examined independent relationships between cardiovascular risk factors and mean cerebral perfusion. Subsequent interaction and stratified models assessed the role for APOE genotype and race. RESULTS: When risk factor p-values were FDR-adjusted, diastolic blood pressure was significantly associated with mean perfusion. Tobacco use, triglycerides, waist-to-hip ratio, and a composite risk score were not associated with perfusion. Without FDR adjustment, a relationship was also observed between perfusion and obesity, cholesterol, and fasting glucose. Neither APOE genotype nor race moderated relationships between risk factors and perfusion. CONCLUSION: Higher diastolic blood pressure predicted lower perfusion more strongly than other cardiovascular risk factors. This relationship did not vary by racial group or genetic risk for AD, although the African American sample had greater vascular risk burden and lower perfusion rates. Our findings highlight the need to prioritize inclusion of underrepresented groups in neuroimaging studies and to continue exploring the link between modifiable risk factors, cerebrovascular health, and AD risk in underrepresented populations.