New Aspects of the Risk Assessment Guidelines: Practical Highlights, Scientific Evidence and Future Goals

Identifying those at the highest risk of developing atherosclerotic cardiovascular disease (ASCVD) can guide appropriate intensity of screening and allocation of preventive therapy. Recently, the American Heart Association and the American College of Cardiology released updated guidelines on cardiovascular risk assessment with an accompanying scientific statement outlining the supporting evidence. How should the latest recommendations change your clinical practice?

The basic themes of the 2013 guidelines are largely preserved with an adjusted framework accentuating the value of non-traditional risk factors, enhancing the role for coronary artery calcium (CAC) scoring and introducing low-density lipoprotein cholesterol (LDL-C) thresholds for consideration of intensifying lipid lowering therapy. Additionally, the guidelines further emphasize shared decision making regarding preventive pharmacotherapy in light of evolving evidence and areas of equipoise.

The new framework encompasses tools to refine baseline risk assessment: risk enhancing factors and coronary artery calcium

In the new guidelines, adults age 20-59 are candidates for lifetime risk estimation in order to motivate preventive lifestyle changes. Between ages 40 and 75, estimation of 10-year risk is emphasized to determine whether an individual falls into a risk group with clear demonstrated benefit from statin therapy in addition to lifestyle management. This is similar to prior guidelines and therefore should reinforce existing practice.

The guideline authors provide a step-wise framework for refining risk estimation. First, use a risk estimator to stratify the individual into a broad preliminary risk category. Second, re-classify the individual if indicated based on known risk modifiers not measured in traditional calculators. Third, if a therapy decision remains uncertain to either the patient or clinician, obtain a CAC score to guide decision making. Fourth, routinely monitor lifestyle parameters and lipids to determine whether additional lipid-lowering therapy is necessary.

Estimation of baseline ASCVD risk: new risk categories

The risk estimator of choice remains the 2013 Pooled Cohort Equations (PCE), though the authors acknowledge that the calibration and discrimination of the PCE fall short in certain contemporary populations. The PCE have the advantage of simplicity, incorporating readily available demographic data and commonly measured biomarkers to ensure that nearly every individual seen in a primary care setting can undergo risk assessment.

Two groups retain a recommendation for statin therapy regardless of baseline estimated risk: those with primary hypercholesterolemia whose LDL-C is 190 mg/dL or more (high intensity, Class I) and patients with diabetes having an LDL-C ≥70 mg/dL (moderate intensity, I).1 Among those with diabetes, 10-year ASCVD risk ≥7.5% is an indication to consider high-intensity statin therapy (Class IIa).

Individuals are preliminarily classified based on estimated risk: 10-year ASCVD risk <5% is low risk; 5%-7.5% is borderline risk; 7.5-20% is intermediate risk, and ≥20% is high risk. High risk individuals should be strongly recommended statin therapy on the basis of risk alone after a clinician patient risk discussion. Conversely, those in the low risk category do not benefit from statin therapy and should focus on healthy habits for CV prevention. The remaining groups, classified as borderline or intermediate risk, have been expanded from prior guidelines and represent approximately half of the US population within the screening ages of 45-70.2

The PCE is a starting point for risk assessment and discussion, rather than an exact prediction of an individual's CV risk and trigger for therapy. The PCE can overestimate risk in contemporary multi-ethnic cohorts, partly due to higher prevalence of preventive care and the modern practice of revascularization prior to hard CV events.3-5 The notable exception is a recent analysis of the REGARDS (REasons for Geographic and Racial Differences in Stroke) cohort, demonstrating good calibration of the PCE, specifically near the risk prediction threshold of 5%.6

There is particular concern for overestimation of risk in older individuals and in those of higher socioeconomic status. Those with chronic inflammatory conditions, of South Asian ancestry and of low socioeconomic status typically are at higher than predicted CV risk.7 Examination of reported outcomes from the Women's Health Initiative with the added resource of CMS reporting data suggested that incomplete event reporting in validation cohorts may contribute to apparent risk overestimation.8 However, among statin-eligible individuals in MESA (Multi-Ethnic Study in Atherosclerosis), 41% had no evidence of atherosclerosis by CAC and are unlikely to gain benefit from statin therapy.9

For individuals at intermediate estimated risk, the presence of risk enhancing factors favors statin therapy

After estimating ASCVD risk, an individual may be reclassified based on established risk enhancers, if present. These represent comorbid conditions or biomarkers not recommended for routine screening, but which offer additional prognostication if measured for another indication.

Elevated high-sensitivity C-reactive protein (hsCRP), low ankle-brachial index (ABI), elevated apolipoprotein B (ApoB) and family history of premature ASCVD have well-established independent association with ASCVD risk; however, their power to improve discrimination to the PCE is modest.10,11 Similarly, premature menopause and prior pre-eclampsia are emerging as independent risk factors for disease, though without robust data to quantify the risk-modulating effect.12 Chronic inflammatory disorders, including rheumatoid arthritis, HIV/AIDS and systemic lupus erythematous are associated with atherosclerotic risk approaching that of diabetes, and traditional risk factor models are shown to be poorly calibrated in affected individuals.13,14

For those of borderline estimated risk (5% to ≤7.5%), the presence of one or more risk factors may favor a risk discussion about possible statin therapy (Class IIb). For those in the intermediate risk category (7.5% to 20%), identification of risk enhancers should more strongly favor statin therapy (Class I).

When risk status is uncertain, CAC can predict who will and will not benefit from statin therapy

If the therapy decision is still unclear, CAC scoring is recommended. CAC provides a window into the presence and relative degree of subclinical atherosclerosis and integrates measured and unmeasured risk factors to provide information generalizable across ages and ethnicities. In 2013, the recommendation for CAC as a deciding factor in cases of intermediate risk was downgraded from class IIa to IIb. Now, with even more compelling evidence for its utility as a tie breaker in statin decision making, the recommendation has returned to class IIa.

There is robust evidence that CAC adds additional risk stratification to traditional risk factors in modern cohorts.15-21 CAC successfully reclassifies individuals with estimated ASCVD risk between 5% and 20%, even at the extremes of age (≤45, ≥75).21 In particular, CAC was far superior to hsCRP, ABI and family history in improving the discriminative ability of the PCE, raising the question of whether individuals judged to be in the indeterminate risk zone and who would be open to preventive therapies should progress directly to CAC scoring rather than making therapeutic decisions based on additional biomarkers of unclear risk magnitude.10

CAC can be considered a decision aid, rather than a screening tool. Due to valid concern for cost, radiation exposure and the burden of incidental findings, CAC will likely never be a population-wide screening tool and should be reserved for such scenarios of uncertainty regarding preventive pharmacotherapy.

The greatest role for CAC appears to be high confidence when the test identifies absence of atherosclerosis (Agatston score 0). Those with CAC = 0 have low 10-year risk likely falling below the threshold of statin benefit as shown in MESA and other epidemiologic studies.9,16,20,22 This finding allows clinicians to recommend deferred or delayed statin therapy for those who would otherwise qualify on the basis of age or another risk factor alone.9

Among intermediate-risk elderly in the BioImage study, the number needed to screen to find one person with absent coronary calcifications was 2.6.22 By eliminating those at low risk of events, resources can be directed towards those truly at elevated risk. The risks of overprescribing, including polypharmacy and side effects, are minimized. However, the guideline writers note that CAC should generally not supersede certain very high risk factors, particularly ongoing tobacco use, a strong family history of premature ASCVD and diabetes.

The Society of Cardiovascular Computed Tomography (SCCT) recently proposed a framework for integrating CAC into a stratified guide for statin initiation and statin intensity. This concrete recommendation, in comparison to the "up-classification" concept introduced in the risk assessment guidelines is a potentially streamlined way to simplify preventive therapy decisions in the busy clinical practice setting.23

CAC ≥100 Agatston Units or above the 75th demographic-adjusted percentile is an indication for moderate- or high-intensity statin therapy, a lower threshold than the score of 300 recommended in the 2013 guidelines. Both the SCCT framework and the new risk assessment guidelines also recommend consideration of statin therapy for those with CAC <100 or <75th percentile.

Introduction of LDL-C targets: lower is better

Regardless of risk group, monitoring of lipid parameters and routine re-assessment of CV risk factors ensures optimal risk factor modification across the life span. Response to any statin initiation or dosing change should be assessed via a fasting lipid panel 4-12 weeks later. The new guidelines include LDL-C thresholds for intensifying lipid lowering treatment. This derives cohort studies and data from trials for proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors demonstrating that naturally low LDL-C is cardioprotective and that benefit of lipid-lowering therapy is tied to absolute lowering of LDL-C. Moreover, those treated to very low LDL-C have demonstrated stabilization or regression of atherosclerosis and fewer ASCVD events with safety down to at least a level of 25 mg/dL.23-26

The decision whether to use statin therapy in primary prevention should be made after a detailed clinician-patient risk discussion

The 2018 guidelines expanded on a concept introduced in the 2013 cholesterol guidelines: shared decision making. Patients are equipped to make a decision regarding preventive therapies when provided informed prediction of their expected risk of events based on current parameters – and residual risk after the proposed intervention. Addressing individual values of cost, potential for adverse effects, drug-drug interactions, and actual potential for benefit (number needed to treat) further empowers patients to participate in therapeutic decisions. The clinician patient risk discussion is given a Class I recommendation in the new guidelines.

The addition of expanded risk factors for consideration only serves to enhance individualization of this risk discussion; however, a paucity of data offering refined quantification of the degree of risk modification and lack of recommendation regarding net reclassification effect of each risk modifier may serve as a source of uncertainty on the part of patients and clinicians. It may broadly be inferred that the presence of any risk modifier should re-classify a patient to the next risk level with therapeutic recommendation reflecting the new categorization.

Decision making does not start or end with pharmacotherapy. The cardiovascular community has in recent years built an emphasis on the positive element of heart health rather than simply the absence of disease. Clinicians should engage in preventive counseling with each patient routinely to recommend changes to optimize CV risk or to affirm healthy lifestyle habits.

In conclusion: new aspects of the risk assessment guidelines

The latest risk assessment guidelines incorporate up-to-date evidence demonstrating poor discrimination of the PCE in certain demographics, identification of novel demographic and biomarker CV risk enhancing factors, robust support for selective use of CAC in offering refined risk stratification and the CV benefit of aggressive lowering of LDL-C with statins as well as non-statin agents. There is opportunity for ongoing advancement via improved calibration of the PCE or alternative risk estimators using modern multi-ethnic populations, though future models should maintain the simplicity of the 2013 version. Additionally, future guidelines may improve quantification of the risk-modifying effect of secondary factors, offer more concrete recommendations based on CAC score when indicated and provide further guidance regarding cessation of statin therapy in the elderly who may experience diminishing returns.

In summary, these guidelines empower us as clinicians to engage in data-driven individualized risk discussions with our patients by broadening the intermediate risk category, adding risk enhancers as decision aids, strengthening the recommendation for CAC as a tie-breaker in shared decision making and emphasizing risk awareness to cultivate and promote optimal CV health behaviors.

Table 1: Recommendations Regarding Statin Therapy Based on Initial and Refined ASCVD Risk Stratification

Adults Age 40-75 With LDL-C 70-189 and Without Diabetes

Low Risk
(<5%)

Emphasize lifestyle

Borderline risk
(5-<7.5%)

Risk enhancers may favor statin therapy.  (Class IIb)

Consider CAC scoring if therapy decision is uncertain (Class IIa)

CAC 0: may defer statin therapy
CAC 1-99: favor statin therapy
CAC ≥100 OR ≥75th percentile*: statin therapy indicated

Intermediate risk (7.5-<20%)

Risk enhancers favor statin therapy. (Class I)

High risk
(≥20%)

Initiate high intensity statin therapy (Class I)

Adults age 40-75 with LDL-C 70-189 and with diabetes

Risk <7.5%

Initiate moderate-intensity statin (Class I)

Risk ≥7.5%
Or risk modifiers

Consider high-intensity statin (Class IIa)

Adults age 40-75 with LDL-C ≥190

 

Initiate high-intensity statin

Table 2: ASCVD Risk Enhancing Factors With Prognostic Value to Support Risk Category Re-Classification

Family history of premature ASCVD

Males, age <55; Females age <65

Primary hypercholesterolemia

LDL-C, 160-189 mg/dL [4.1-4.8 mmol/L);
non-HDL-C 190-219 mg/dL [4.9-5.6 mmol/L])

Metabolic syndrome 

Abdominal obesity, hypertriglyceridemia, low HDL-C, hypertension, and hyperglycemia

Chronic kidney disease

eGFR 15-59 mL/min/1.73 m2 with or without albuminuria; not treated with dialysis or kidney transplantation

Chronic inflammatory conditions

Example: psoriasis, rheumatoid arthritis, HIV/AIDS

History of premature menopause
history of pregnancy-associated conditions

Before age 40
Example: pre-eclampsia

High-risk race/ethnicities

Example: South Asian ancestry

Persistently elevated, primary hypertriglyceridemia

≥175 mg/dL

Elevated high-sensitivity C-reactive protein

≥2.0 mg/L

Elevated Lipoprotein (a)

≥50 mg/dL or ≥125 nmol/L

Elevated apolipoprotein B

≥130 mg/dL

Ankle-brachial index

<0.9

References

  1. Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014;63:2889-934.
  2. Goff DC, 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.
  3. DeFilippis AP, Young R, McEvoy JW, et al. Risk score overestimation: the impact of individual cardiovascular risk factors and preventive therapies on the performance of the American Heart Association-American College of Cardiology-Atherosclerotic Cardiovascular Disease risk score in a modern multi-ethnic cohort. Eur Heart J 2017;38:598-608.
  4. Rana JS, Tabada GH, Solomon MD, et al. Accuracy of the atherosclerotic cardiovascular risk equation in a large contemporary, multiethnic population. J Am Coll Cardiol 2016;67:2118-30.
  5. Pylypchuk R, Wells S, Kerr A, et al. Cardiovascular disease risk prediction equations in 400,000 primary care patients in New Zealand: a derivation and validation study. Lancet 2018;391:1897-901.
  6. Muntneer P, Colantonio LD, Cushman M, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA 2014;311:1406-15.
  7. Dalton JE, Perzynski AT, Zidar DA, et al. Accuracy of cardiovascular risk prediction varies by neighborhood socioeconomic position: a retrospective cohort study. Ann Intern Med 2017;1678:456-64.
  8. Mora S, Wenger NK, Cook NR, et al. Evaluation of the pooled cohort risk equations for cardiovascular risk prediction in a multiethnic cohort from the Women's Health Initiative. JAMA Intern Med 2017;178:1231-40.
  9. Nasir K, Bittencourt MS, Blaha MJ, et al. Implications of coronary artery calcium testing among statin candidates according to American College of Cardiology/American Heart Association Cholesterol Management Guidelines: MESA (Multi-Ethnic Study of Atheroslcerosis). J Am Coll Cardiol 2015;66:1657-68.
  10. 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.
  11. Graversen P, Abildstrom SZ, Jespersen L, Borglykke A, Prescott E. Cardiovascular risk prediction: can Systematic Coronary Risk Evaluation (SCORE) be improved by adding simple risk markers? Results from the Copenhagen City Heart Study. Eur J Prev Cardiol 2016;23:1546-56.
  12. Kessous R, Shoham-Vardi I, Pariente G, Sergienko R, Sheiner E. Long-term maternal atherosclerotic morbidity in women with pre-eclampsia. Heart 2015;101:442-6.
  13. Triant VA, Perez J, Regan S, et al. Cardiovascular risk prediction functions underestimate risk in HIV infection. Circulation 2018;137:2203-14.
  14. Rahman F, Martin SS, Whelton SP, Mody FV, Vaishnav J, McEvoy JW. Inflammation and cardiovascular disease risk: a case study of HIV and inflammatory joint disease. Am J Med 2018;131:e1-442.
  15. Qureshi WT, Rana JS, Yeboah J, Bin Nasir U, Al-Mallah MH. Risk stratification for primary prevention of coronary artery disease: roles of C-reactive protein and coronary artery calcium. Curr Cardiol Rep 2015;17:110.
  16. Budoff MJ, McClelland RL, Nasir K, et al. Cardiovascular events with absent or minimal coronary calcification: the Multi-Ethnic Study of Atherosclerosis (MESA). Am Heart J 2009;158:554-61.
  17. Nasir K, Bittencourt MS, Blaha MJ, et al. Implications of coronary artery calcium testing among statin candidates according to American College of Cardiology/American Heart Association cholesterol management guidelines: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol 2015;66:1657-68.
  18. 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.
  19. Blaha MJ, Budoff MJ, DeFilippis AP, et al. Association between C-reactive protein, coronary artery calcium, and cardiovascular events: implications for the JUPITER population from MESA, a population-based cohort study. Lancet 2011;378:684-92.
  20. Silverman MG, Blaha MJ, Krumholz HM, et al. Impact of coronary artery calcium on coronary heart disease events in individuals at the extremes of traditional risk factor burden: the Multi-Ethnic Study of Atherosclerosis. Eur Heart J 2014;35:2232-41.
  21. Tota-Maharaj R, Blaha MJ, Blankstein R, et al. Association of coronary artery calcium and coronary heart disease events in young and elderly participants in the multi-ethnic study of atherosclerosis: a secondary analysis of a prospective, population-based cohort. Mayo Clin Proc 2014;89:1350-9.
  22. Mortensen MB, Fuster V, Muntendam P, et al. A simple disease-guided approach to personalize ACC/AHA-recommended statin allocation in elderly people: the BioImage study. J Am Coll Cardiol 2016;68:881-91.
  23. Hecht HS, Blaha MJ, Kazerooni EA, et al. CAC-DRS: coronary artery calcium data and reporting system. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT). J Cardiovasc Comput Tomogr 2018;12:185-91.
  24. Martin SS, Metkus TS, Horne A, et al. Waiting for the national cholesterol education program adult treatment panel IV guidelines, and in the meantime, some challenges and recommendations. Am J Cardiol 2012;110:307-13.
  25. O'Keefe JH Jr, Cordain L, Harris WH, Moe RM, Vogel R. Optimal low-density lipoprotein is 50 to 70 mg/dl: lower is better and physiologically normal. J Am Coll Cardiol 2004;43:2142-6.
  26. Robinson JG, Rosenson RS, Farnier M, et al. Safety of very low low-density lipoprotein cholesterol levels with alirocumab: pooled data from randomized trials. J Am Coll Cardiol 2017;69:471-82.

Clinical Topics: Anticoagulation Management, Cardiovascular Care Team, Diabetes and Cardiometabolic Disease, Dyslipidemia, Noninvasive Imaging, Prevention, Homozygous Familial Hypercholesterolemia, Lipid Metabolism, Nonstatins, Novel Agents, Statins

Keywords: Dyslipidemias, Acquired Immunodeficiency Syndrome, American Heart Association, Ankle Brachial Index, Apolipoproteins B, Arthritis, Rheumatoid, Atherosclerosis, Biomarkers, Cardiovascular Diseases, Centers for Medicare and Medicaid Services, U.S., Cholesterol, Cholesterol, LDL, Cohort Studies, Coronary Vessels, C-Reactive Protein, Decision Making, Decision Support Techniques, Demography, Diabetes Mellitus, Epidemiologic Studies, Drug Interactions, Factor IX, Habits, Health Behavior, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hypercholesterolemia, Incidental Findings, Life Style, Lipids, Menopause, Premature, Polypharmacy, Precipitating Factors, Pre-Eclampsia, Prevalence, Primary Health Care, Primary Prevention, Risk Assessment, Risk Factors, Stroke, Subtilisins, Tobacco Use, Tomography


< Back to Listings