A Systematic Examination of the 2013 ACC/AHA Pooled Cohort Risk Assessment Tool for Atherosclerotic Cardiovascular Disease

AbstractBackgroundThe 2013 American College of Cardiology/American Heart Association updated cholesterol guidelines recommend the use of Pooled Cohort Equations to estimate 10-year absolute risk for atherosclerotic cardiovascular disease (ASCVD) in primary prevention.ObjectivesThis study sought to systematically examine the Pooled Cohort Equations to determine risk factor levels required to exceed risk thresholds outlined in new cholesterol guidelines.MethodsWe entered continuous risk factor levels in isolation and in specified combinations with the risk tool, and we observed predicted risk output patterns. We used the 10-year ASCVD risk threshold of ≥7.5% as a clinically relevant risk threshold.ResultsWe demonstrated that a hypothetical man or woman can reach clinically relevant risk thresholds throughout the eligible age spectrum of 40 to 79 years of age, depending on the associated risk factor burden in all race-sex groups. Age continues to be a major determinant of 10-year ASCVD risk for both men and women. Compared with the previous risk assessment tool used in cholesterol guidelines, the inclusion of a stroke endpoint and use of race-specific coefficients permit identification of at-risk African Americans and non-Hispanic white women at much younger ages and lower risk factor levels.ConclusionsThese data provide context of specific risk factor levels and groups of individuals who are likely to have 10-year ASCVD risk estimates ≥7.5%. Age continues to be a major driver of risk, which highlights the importance of the clinician-patient discussion before statin therapy is initiated

Risk scoring for the primary prevention of cardiovascular disease.

BACKGROUND: The current paradigm for cardiovascular disease (CVD) emphasises absolute risk assessment to guide treatment decisions in primary prevention. Although the derivation and validation of multivariable risk assessment tools, or CVD risk scores, have attracted considerable attention, their effect on clinical outcomes is uncertain. OBJECTIVES: To assess the effects of evaluating and providing CVD risk scores in adults without prevalent CVD on cardiovascular outcomes, risk factor levels, preventive medication prescribing, and health behaviours. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (2016, Issue 2), MEDLINE Ovid (1946 to March week 1 2016), Embase (embase.com) (1974 to 15 March 2016), and Conference Proceedings Citation Index-Science (CPCI-S) (1990 to 15 March 2016). We imposed no language restrictions. We searched clinical trial registers in March 2016 and handsearched reference lists of primary studies to identify additional reports. SELECTION CRITERIA: We included randomised and quasi-randomised trials comparing the systematic provision of CVD risk scores by a clinician, healthcare professional, or healthcare system compared with usual care (i.e. no systematic provision of CVD risk scores) in adults without CVD. DATA COLLECTION AND ANALYSIS: Three review authors independently selected studies, extracted data, and evaluated study quality. We used the Cochrane 'Risk of bias' tool to assess study limitations. The primary outcomes were: CVD events, change in CVD risk factor levels (total cholesterol, systolic blood pressure, and multivariable CVD risk), and adverse events. Secondary outcomes included: lipid-lowering and antihypertensive medication prescribing in higher-risk people. We calculated risk ratios (RR) for dichotomous data and mean differences (MD) or standardised mean differences (SMD) for continuous data using 95% confidence intervals. We used a fixed-effects model when heterogeneity (I²) was at least 50% and a random-effects model for substantial heterogeneity (I² > 50%). We evaluated the quality of evidence using the GRADE framework. MAIN RESULTS: We identified 41 randomised controlled trials (RCTs) involving 194,035 participants from 6422 reports. We assessed studies as having high or unclear risk of bias across multiple domains. Low-quality evidence evidence suggests that providing CVD risk scores may have little or no effect on CVD events compared with usual care (5.4% versus 5.3%; RR 1.01, 95% confidence interval (CI) 0.95 to 1.08; I² = 25%; 3 trials, N = 99,070). Providing CVD risk scores may reduce CVD risk factor levels by a small amount compared with usual care. Providing CVD risk scores reduced total cholesterol (MD -0.10 mmol/L, 95% CI -0.20 to 0.00; I² = 94%; 12 trials, N = 20,437, low-quality evidence), systolic blood pressure (MD -2.77 mmHg, 95% CI -4.16 to -1.38; I² = 93%; 16 trials, N = 32,954, low-quality evidence), and multivariable CVD risk (SMD -0.21, 95% CI -0.39 to -0.02; I² = 94%; 9 trials, N = 9549, low-quality evidence). Providing CVD risk scores may reduce adverse events compared with usual care, but results were imprecise (1.9% versus 2.7%; RR 0.72, 95% CI 0.49 to 1.04; I² = 0%; 4 trials, N = 4630, low-quality evidence). Compared with usual care, providing CVD risk scores may increase new or intensified lipid-lowering medications (15.7% versus 10.7%; RR 1.47, 95% CI 1.15 to 1.87; I² = 40%; 11 trials, N = 14,175, low-quality evidence) and increase new or increased antihypertensive medications (17.2% versus 11.4%; RR 1.51, 95% CI 1.08 to 2.11; I² = 53%; 8 trials, N = 13,255, low-quality evidence). AUTHORS' CONCLUSIONS: There is uncertainty whether current strategies for providing CVD risk scores affect CVD events. Providing CVD risk scores may slightly reduce CVD risk factor levels and may increase preventive medication prescribing in higher-risk people without evidence of harm. There were multiple study limitations in the identified studies and substantial heterogeneity in the interventions, outcomes, and analyses, so readers should interpret results with caution. New models for implementing and evaluating CVD risk scores in adequately powered studies are needed to define the role of applying CVD risk scores in primary CVD prevention

Point-of-care testing to promote cardiovascular disease risk assessment: A proof of concept study

Updated cholesterol guidelines emphasize multivariable cardiovascular disease (CVD) risk estimation to guide treatment decision-making in primary prevention. This study tested the preliminary feasibility, acceptability and efficacy of point-of-care testing (POCT) and quantitative CVD risk assessment in high-risk adults to increase guideline-recommended statin use in primary prevention. Participants were aged 40–75 years, without CVD or diabetes mellitus, and potentially-eligible for consideration of statins based on estimated 10-year CVD risk from last-measured risk factor levels in the electronic health record. We performed POCT to facilitate quantitative CVD risk assessment with the Pooled Cohort Equations immediately before a scheduled primary care provider (PCP) visit. Outcomes were: physician documentation of a CVD risk discussion and statin prescription on the study date. We also assessed acceptability of the intervention through structured questionnaire. We recruited 18 participants (8 from an academic practice and 10 from a federally-qualified health clinic). After the intervention, 83% of participants discussed CVD risk with their PCP, 47% received a statin recommendation from their PCP, and 29% received a new statin prescription during the PCP visit. Participants reported high levels of satisfaction with the intervention. This study demonstrates that in initial testing pre-visit POCT and quantitative CVD risk assessment appears to be a feasible and acceptable intervention that may promote guideline-recommended statin initiation in primary prevention. Future research with an adequately powered trial is warranted to determine the effectiveness of this approach in clinical practice

Women Up, Men Down: The Clinical Impact of Replacing the Framingham Risk Score with the Reynolds Risk Score in the United States Population

<div><h3>Background</h3><p>The Reynolds Risk Score (RRS) is one alternative to the Framingham Risk Score (FRS) for cardiovascular risk assessment. The Adult Treatment Panel III (ATP III) integrated the FRS a decade ago, but with the anticipated release of ATP IV, it remains uncertain how and which risk models will be integrated into the recommendations. We sought to define the effects in the United States population of a transition from the FRS to the RRS for cardiovascular risk assessment.</p> <h3>Methods</h3><p>Using the National Health and Nutrition Examination Surveys, we assessed FRS and RRS in 2,502 subjects representing approximately 53.6 Million (M) men (ages 50–79) and women (ages 45–79), without cardiovascular disease or diabetes. We calculated the proportion reclassified by RRS and the subset whose LDL-C goal achievement changed.</p> <h3>Results</h3><p>Compared to FRS, the RRS assigns a higher risk category to 13.9% of women and 9.1% of men while assigning a lower risk to 35.7% of men and 2% of women. Overall, 4.7% of women and 1.1% of men fail to meet newly intensified LDL-C goals using the RRS. Conversely, 10.5% of men and 0.6% of women now meet LDL-C goal using RRS when they had not by FRS.</p> <h3>Conclusion</h3><p>In the U.S. population the RRS assigns a new risk category for one in six women and four of nine men. In general, women increase while men decrease risk. In conclusion, adopting the RRS for the 53.6 million eligible U.S. adults would result in intensification of clinical management in 1.6 M additional women and 2.10 M fewer men.</p> </div

Subject Characteristics.

<p>Subject Characteristics.</p

Reynolds Risk Score Applied to Population of U.S. Women.

*<p>N/A: Risk category reclassification not possible in that direction.</p><p>(95% confidence intervals).</p>†<p>Percentage is based on proportion of risk category experiencing risk category reassignment.</p

Trends in Low-Density Lipoprotein Cholesterol Goal Achievement in High Risk United States Adults: Longitudinal Findings from the 1999–2008 National Health and Nutrition Examination Surveys

<div><p>Background</p><p>Previous studies have demonstrated gaps in achievement of low-density lipoprotein-cholesterol (LDL-C) goals among U.S. individuals at high cardiovascular disease risk; however, recent studies in selected populations indicate improvements.</p> <p>Objective</p><p>We sought to define the longitudinal trends in achieving LDL-C goals among high-risk United States adults from 1999–2008.</p> <p><i>Methods</i> We analyzed five sequential population-based cross-sectional National Health and Nutrition Examination Surveys 1999–2008, which included 18,656 participants aged 20–79 years. We calculated rates of LDL-C goal achievement and treatment in the high-risk population.</p> <p>Results</p><p>The prevalence of high-risk individuals increased from 13% to 15.5% (p = 0.046). Achievement of LDL-C <100 mg/dL increased from 24% to 50.4% (p<0.0001) in the high-risk population with similar findings in subgroups with (27% to 64.8% p<0.0001) and without (21.8% to 43.7%, p<0.0001) coronary heart disease (CHD). Achievement of LDL-C <70 mg/dL improved from 2.4% to 17% (p<0.0001) in high-risk individuals and subgroups with (3.4% to 21.4%, p<0.0001) and without (1.7% to 14.9%, p<0.0001) CHD. The proportion with LDL-C ≥130 mg/dL and not on lipid medications decreased from 29.4% to 18% (p = 0.0002), with similar findings among CHD (25% to 11.9% p = 0.0013) and non-CHD (35.8% to 20.8% p<0.0001) subgroups.</p> <p>Conclusion</p><p>The proportions of the U.S. high-risk population achieving LDL-C <100 mg/dL and <70 mg/dL increased over the last decade. With 65% of the CHD subpopulation achieving an LDL-C <100 mg/dL in the most recent survey, U.S. LDL-C goal achievement exceeds previous reports and approximates rates achieved in highly selected patient cohorts.</p> </div

Inclusions/Exclusions.

*<p>Variable only collected in 1999–2000.</p>†<p>MEC Mobile Exam Center.</p>#<p>Peripheral Vascular Disease only collected in 99–00, 01–02, 03–04.</p

Prevalence of High Risk Conditions in Analyzed Populations NHANES 1999–2008.

<p>(95% CI).</p>*<p>p-value for test for trend over time.</p><p>CHD = coronary heart disease, FRS = Framingham Risk Score.</p