Inequities in atherosclerotic cardiovascular disease prevention.

Atherosclerotic cardiovascular (CV) disease (ASCVD) prevention encompasses interventions across the lifecourse: from primordial to primary and secondary prevention. Primordial prevention begins in childhood and involves the promotion of ideal CV health (CVH) via optimizing physical activity, body mass index, blood glucose levels, total cholesterol levels, blood pressure, and sleep while minimizing tobacco use. Primary and secondary prevention of ASCVD thereafter centers around mitigating ASCVD risk factors via medical therapy and lifestyle interventions. Disparities in optimal preventive efforts exist among historically marginalized groups in each of these three prongs of ASCVD prevention. Children and adults with a high burden of social determinants of health also face inequity in preventive measures. Inadequate screening, risk factor management and prescription of preventive therapeutics permeate the care of certain groups, especially women, Black, and Hispanic individuals in the United States. Beyond this, individuals belonging to historically marginalized groups also are much more likely to experience other ASCVD risk-enhancing factors, placing them at higher risk for ASCVD over their lifetime. These disparities translate to worse outcomes, with higher rates of ASCVD and CV mortality among these groups. Possible solutions to promoting equity involve community-based youth lifestyle interventions, improved risk-factor screening, and increasing accessibility to healthcare resources and novel preventive diagnostics and therapeutics.

Unfavorable social determinants of health are associated with higher burden of financial toxicity among patients with atherosclerotic cardiovascular disease in the US: findings from the National Health Interview Survey.

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is a major cause of financial toxicity, defined as excess financial strain from healthcare, in the US. Identifying factors that put patients at greatest risk can help inform more targeted and cost-effective interventions. Specific social determinants of health (SDOH) such as income are associated with a higher risk of experiencing financial toxicity from healthcare, however, the associations between more comprehensive measures of cumulative social disadvantage and financial toxicity from healthcare are poorly understood. METHODS: Using the National Health Interview Survey (2013-17), we assessed patients with self-reported ASCVD. We identified 34 discrete SDOH items, across 6 domains: economic stability, education, food poverty, neighborhood conditions, social context, and health systems. To capture the cumulative effect of SDOH, an aggregate score was computed as their sum, and divided into quartiles, the highest (quartile 4) containing the most unfavorable scores. Financial toxicity included presence of: difficulty paying medical bills, and/or delayed/foregone care due to cost, and/or cost-related medication non-adherence. RESULTS: Approximately 37% of study participants reported experiencing financial toxicity from healthcare, with a prevalence of 15% among those in SDOH Q1 vs 68% in SDOH Q4. In fully-adjusted regression analyses, individuals in the 2nd, 3rd and 4th quartiles of the aggregate SDOH score had 1.90 (95% CI 1.60, 2.26), 3.66 (95% CI 3.11, 4.35), and 8.18 (95% CI 6.83, 9.79) higher odds of reporting any financial toxicity from healthcare, when compared with participants in the 1st quartile. The associations were consistent in age-stratified analyses, and were also present in analyses restricted to non-economic SDOH domains and to 7 upstream SDOH features. CONCLUSIONS: An unfavorable SDOH profile was strongly and independently associated with subjective financial toxicity from healthcare. This analysis provides further evidence to support policies and interventions aimed at screening for prevalent financial toxicity and for high financial toxicity risk among socially vulnerable groups.

Assessment of Coronary Artery Calcium Scoring to Guide Statin Therapy Allocation According to Risk-Enhancing Factors: The Multi-Ethnic Study of Atherosclerosis.

Importance: The 2018 American Heart Association/American College of Cardiology Guideline on the Management of Blood Cholesterol recommends the use of risk-enhancing factor assessment and the selective use of coronary artery calcium (CAC) scoring to guide the allocation of statin therapy among individuals with an intermediate risk of atherosclerotic cardiovascular disease (ASCVD). Objective: To examine the association between risk-enhancing factors and incident ASCVD by CAC burden among those at intermediate risk of ASCVD. Design, Setting, and Participants: The Multi-Ethnic Study of Atherosclerosis is a multicenter population-based prospective cross-sectional study conducted in the US. Baseline data for the present study were collected between July 15, 2000, and July 14, 2002, and follow-up for incident ASCVD events was ascertained through August 20, 2015. Participants were aged 45 to 75 years with no clinical ASCVD or diabetes at baseline, were at intermediate risk of ASCVD (≥7.5% to <20.0%), and had a low-density lipoprotein cholesterol level of 70 to 189 mg/dL. Exposures: Family history of premature ASCVD, premature menopause, metabolic syndrome, chronic kidney disease, lipid and inflammatory biomarkers, and low ankle-brachial index. Main Outcomes and Measures: Incident ASCVD over a median follow-up of 12.0 years. Results: A total of 1688 participants (mean [SD] age, 65 [6] years; 976 men [57.8%]). Of those, 648 individuals (38.4%) were White, 562 (33.3%) were Black, 305 (18.1%) were Hispanic, and 173 (10.2%) were Chinese American. A total of 722 participants (42.8%) had a CAC score of 0. Among those with 1 to 2 risk-enhancing factors vs those with 3 or more risk-enhancing factors, the prevalence of a CAC score of 0 was 45.7% vs 40.3%, respectively. Over a median follow-up of 12.0 years (interquartile range [IQR], 11.5-12.6 years), the unadjusted incidence rate of ASCVD among those with a CAC score of 0 was less than 7.5 events per 1000 person-years for all individual risk-enhancing factors (with the exception of ankle-brachial index, for which the incidence rate was 10.4 events per 1000 person-years [95% CI, 1.5-73.5]) and combinations of risk-enhancing factors, including participants with 3 or more risk-enhancing factors. Although the individual and composite addition of risk-enhancing factors to the traditional risk factors was associated with improvement in the area under the receiver operating curve, the use of CAC scoring was associated with the greatest improvement in the C statistic (0.633 vs 0.678) for ASCVD events. For incident ASCVD, the net reclassification improvement for CAC was 0.067. Conclusions and Relevance: In this cross-sectional study, among participants with CAC scores of 0, the presence of risk-enhancing factors was generally not associated with an overall ASCVD risk that was higher than the recommended treatment threshold for the initiation of statin therapy. The use of CAC scoring was associated with significant improvements in the reclassification and discrimination of incident ASCVD. The results of this study support the utility of CAC scoring as an adjunct to risk-enhancing factor assessment to more accurately classify individuals with an intermediate risk of ASCVD who might benefit from statin therapy.

Author Self-disclosure Compared with Pharmaceutical Company Reporting of Physician Payments.

BACKGROUND: Industry manufacturers are required by the Sunshine Act to disclose payments to physicians. These data recently became publicly available, but some manufacturers prereleased their data since 2009. We tested the hypotheses that there would be discrepancies between manufacturers' and physicians' disclosures. METHODS: The financial disclosures by authors of all 39 American College of Cardiology and American Heart Association guidelines between 2009 and 2012 were matched to the public disclosures of 15 pharmaceutical companies during that same period. Duplicate authors across guidelines were assessed independently. Per the guidelines, payments <$10,000 are modest and ≥$10,000 are significant. Agreement was determined using a κ statistic; Fisher's exact and Mann-Whitney tests were used to detect statistical significance. RESULTS: The overall agreement between author and company disclosure was poor (κ = 0.238). There was a significant difference in error rates of disclosure among companies and authors (P = .019). Of disclosures by authors, companies failed to match them with an error rate of 71.6%. Of disclosures by companies, authors failed to match them with an error rate of 54.7%. CONCLUSIONS: Our analysis shows a concerning level of disagreement between guideline authors' and pharmaceutical companies' disclosures. Without ability for physicians to challenge reports, it is unclear whether these discrepancies reflect undisclosed relationships with industry or errors in reporting, and caution should be advised in interpretation of data from the Sunshine Act.