Approaches to cardiovascular disease risk assessment range in focus from the broad endpoint of global composite cardiovascular disease, including myocardial infarction (MI), stroke, coronary or peripheral revascularization, incident heart failure and atrial fibrillation, to more narrow approaches focused only on coronary events or cardiovascular mortality or to approaches in the middle looking at hard atherosclerotic cardiovascular disease (ASCVD) events such as MI or stroke. The 2013 Risk Assessment Guidelines recommended the latter approach. Numerous risk scores have been developed in US cohorts in the past, including the Framingham Coronary Heart Disease (CHD) score and Reynolds Risk Scores for men and women.^1-3

The 2013 ACC/AHA Guidelines on the Assessment of Cardiovascular Risk advised using the Pooled Cohort Equations (PCE) to predict 10-year risk of a first hard ASCVD event.⁴ The PCE variables include age, total cholesterol, high density lipoprotein (HDL) cholesterol, systolic blood pressure, diabetes and current smoking status to provide a sex and race-specific estimate of the 10-year ASCVD risk for African American and white men and women. The risk output is validated and provides reasonable risk estimation using a significant number of African Americans and whites.⁴ However, the PCE may overestimate risk in other races/ethnicities and in populations with less social deprivation,⁵ which requires attention when making medical decisions.

Many studies have demonstrated that use of a coronary artery calcium (CAC) score often helps improve risk assessment.^6-8 In this setting, the Multi-Ethnic Study of Atherosclerosis (MESA) investigators developed a risk score integrating CAC.⁹ However, this risk score only predicts coronary heart disease risk and does not include stroke; in addition, it was derived from a cohort of 45-85 year olds. Due to a need for improved risk assessment for a younger population in high risk occupations, such as astronauts, the National Space Biomedical Research Institute (NSBRI) recently sponsored a study developing the Astronaut Cardiovascular Health and Risk Modification (Astro-CHARM) calculator.¹⁰

Astro-CHARM was developed as the first integrated ASCVD risk calculator, incorporating traditional risk factors, as used in the PCE, and CAC, along with high-sensitivity C-reactive protein (hsCRP) and family history of MI. Data were derived from individual participant level data from three large, population-based cohorts: MESA, the Dallas Heart Study (DHS), and the Prospective Army Coronary Calcium Project (PACC). An external validation cohort was derived from the Framingham Heart Study (FHS) Offspring and Third Generation cohorts.

Baseline risk factors were defined by each derivation cohort. For instance, family history of MI was defined as any first degree relative with MI at any age for MESA and DHS, but as a history of sudden death, MI or coronary revascularization in any first or second degree relative for PACC and as family history of coronary disease in FHS, but in both studies only for events before age 55 for men and age 65 for women. For all studies, CAC was determined using standard Agatston unit methodology. The primary endpoint of the study included a composite of non-fatal MI, non-fatal stroke or death from CHD or stroke. These components were available for MESA, DHS and FHS, but only non-fatal MI and CVD death were available for PACC.

Baseline characteristics included an average age of 51 years, with roughly equal numbers of men and women (55% and 45%, respectively). Approximately 30% of individuals were black, 45% were white, and 17% were Hispanic. Statin use at baseline was uncommon with only 9% reporting use in the overall cohort. Participants were relatively healthy with only 8% having diabetes, 16% with current smoking and 22% on antihypertensive medications. Additionally, the mean baseline CAC was 0, and event rate was low at 4.27 per 1000 person-years, with 304 hard ASCVD events occurring. Median follow-up was 10.9 years.

The c-statistics for the baseline risk factor model and full Astro-CHARM model were 0.78 and 0.82 (p < 0.0001), respectively. Consistent with its incorporation of CAC, the Astro-CHARM model was superior for prediction of MI (c-statistic risk factor model was 0.74 and Astro-CHARM 0.83) as compared to stroke (c-statistic risk factor model was 0.78 and Astro-CHARM 0.78). Overall, the Astro-CHARM model was well-calibrated internally and showed good discrimination in the external validation cohort (FHS).

Astro-CHARM was developed as the first integrated ASCVD risk calculator, incorporating most notably CAC into risk calculation. Current ACC/AHA guidelines recommend aspirin and statin use based upon 10-year ASCVD risk.⁴ Guidelines note that a CAC >300 or >75th percentile for age, sex and ethnicity can be used to increase precision in decisions regarding pharmacologic therapy. However, given that CAC scores occur on a continuum, Astro-CHARM provides a unique opportunity for fuller integration of CAC into risk assessment in those patients.

Additionally, hsCRP and family history were also independently predictive of ASCVD and were therefore included in the full Astro-CHARM model. Family history was defined in different ways among the three cohorts in the derivation group (MESA, DHS and PACC) and in the external validation cohort (FHS). This is simplified to family history of heart attack in the online calculator (http://astrocharm.org/calculator-working/) and the limitations of this simplification are uncertain.

One of the other proposed advantages of Astro-CHARM over the existing MESA CHD risk calculator is its inclusion of stroke within ASCVD in risk assessment.⁹ While Astro-CHARM includes stroke as an endpoint, its prediction was stronger for MI than for stroke; this suggests that perhaps Astro-CHARM is more useful as a risk prediction model for coronary heart disease compared to stroke. Another intended advantage of Astro-CHARM is its risk prediction for a younger population. While the Astro-CHARM model predicts risk for a mean age lower than PCE (Astro-CHARM age range is 40-65 years and PCE age range is 40-79 years), the risk prediction still begins starting at age 40 years for both, so persons under age 40 are excluded from both models.

In summary, Astro-CHARM provides a new risk prediction model, intended for a young, relatively healthy population, with unique incorporation of CAC, hsCRP and family history of MI. The Astro-CHARM model appears to increase precision in risk assessment and thereby has the potential to improve shared decision-making regarding initiation of preventive medications. As the global population continues to have growing risk factors for the development of atherosclerosis, accurate risk estimation will become increasingly more important. Models such as Astro-CHARM will likely provide an advantage in targeting individuals for earlier and more appropriate medication initiation.

References

1. Wilson PW, D'Agostino RB, Levy D, Belanger AM, SIlbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998;97:1837-47.
2. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA 2007;297:611-9.
3. Ridker PM, Paynter NP, Rifai N, Gaziano JM, Cook NR. C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men. Circulation 2008;118:2243-51.
4. Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014;63:2935-59.
5. Colantonio LD, Richman JS, Carson AP, et al. Performance of the atherosclerotic cardiovascular disease pooled cohort risk equations by social deprivation status. J Am Heart Assoc 2017;6.
6. Hoffmann U, Massaro JM, D'Agostino RB Sr, Kathiresan S, Fox CS, O'Donnell CJ. Cardiovascular event prediction and risk reclassification by coronary, aortic, and valvular calcification in the Framingham Heart Study. J Am Heart Assoc 2016;5.
7. Paixao AR, Ayers CR, El Sabbagh A, et al. Coronary artery calcium improves risk classification in younger populations. JACC Cardiovasc Imaging 2015;8:1285-93.
8. Yeboah J, Young R, McClelland RL, et al. Utility of nontraditional risk markers in atherosclerotic cardiovascular disease risk assessment. J Am Coll Cardiol 2016;67:139-47.
9. McClelland RL, Jorgensen NW, Budoff M, et al. 10-year coronary heart disease risk prediction using coronary artery calcium and traditional risk factors: derivation in the MESA (Multi-Ethnic Study of Atherosclerosis) with validation in the HNR (Heinz Nixdorf Recall) study and the DHS (Dallas Heart Study). J Am Coll Cardiol 2015;66:1643-53.
10. Khera A, Budoff MJ, O'Donnell CJ, et al. The Astronaut Cardiovascular Health and Risk Modification (Astro-CHARM) coronary calcium atherosclerotic cardiovascular disease risk calculator. Circulation. Epub ahead of print.

Keywords: Dyslipidemias, Risk Factors, Antihypertensive Agents, Hydroxymethylglutaryl-CoA Reductase Inhibitors, C-Reactive Protein, Cholesterol, HDL, Calcium, Atrial Fibrillation, Aspirin, Blood Pressure, Coronary Vessels, Research Personnel, Cardiovascular Diseases, Myocardial Infarction, Stroke, Risk Assessment, Atherosclerosis, Coronary Disease, Heart Failure, Diabetes Mellitus, Decision Making, Biomedical Research

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