CAC Guided Strategy May Be Cost-Effective for Those at Intermediate ASCVD Risk

Quick Takes

  • For asymptomatic, intermediate risk adults with a family history of coronary heart disease (CHD), CAC screening and treatment is more cost-effective than standard management using a statin treatment threshold of ≥7.5%.
  • Considering higher lifetime risk in the setting of a family history of CHD, repeat CAC testing may be considered if initial CAC=0 to help guide statin allocation.

Commentary based on Venkataraman P, Kawakami H, Huynh Q, et al. Cost-effectiveness of coronary artery calcium scoring in people with a family history of coronary disease. JACC Cardiovasc Imaging 2021;14:1206-17.1

Rationale for Study: Is the use of coronary artery calcium (CAC) compared with standard risk prediction alone cost-effective to guide risk evaluation and statin therapy among adults with a family history of premature coronary artery disease (FHCAD)?

Methods:  A microsimulation model was constructed in TreeAge Healthcare Pro using data from 1,083 participants in the CAUGHT-CAD (Coronary Artery Calcium Score: Use to Guide Management of HerediTary Coronary Artery Disease) trial to evaluate two strategies for commencing statins: 1) Pooled Cohort Equations (PCE) 10-year predicted risk ≥7.5% (standard care); and 2) PCE risk ≥2% and CAC >0 (CAC-guided strategy). CAC scoring was performed on asymptomatic men and women, aged 40 to 70 years, with FHCAD events (first-degree male relative <55 years, female relative <65 years, or second-degree relative <50 years of age) and a predicted 5-year Australian Absolute Cardiovascular Disease Risk Calculator (derived from the Framingham Risk Score) between 2% to 15%. Outcomes assessed were quality-adjusted life years (QALYs); cost-effectiveness was assessed over a 15-year time interval.

Results: Overall, statin therapy was indicated in 24.6% of participants with a predicted PCE-risk of ≥7.5% and 45.8% of participants with a CAC>0. Comparatively, the CAC strategy was more costly ($145 per person) but more effective (averting 476 deaths and 1,314 symptomatic cardiovascular events) and led to increased QUALYs/patient by 0.0097, with an incremental cost-effective ratio (ICER) of $15,014/QALY. The number needed to scan with CAC to prevent 1 ASCVD event was 152, compared to a no-scan strategy. At a willingness to pay a threshold of $50,000, a CAC strategy remained cost-effective even when statin treatment efficacy was attenuated to reflect real-world data rather than generalizable trial data.

Conclusions:  In individuals with FHCAD, a CAC-guided strategy is cost-effective when compared to standard statin treatment thresholds (PCE ≥7.5%)

Perspective:  The 2018 multisociety guideline on the management of blood cholesterol recommends assessment of atherosclerotic cardiovascular disease (ASCVD) risk using the PCE among those aged 40-75 years of age with a low-density lipoprotein cholesterol (LDL-C) ≥70 mg/dL and <190 mg/dL, and free of ASCVD and diabetes mellitus.2

For those who are classified as borderline (5% - <7.5%) or intermediate (≥7.5% - 20%) risk, a patient-clinician discussion is suggested to identify ASCVD risk enhancing factors such as family history of premature ASCVD, which would otherwise favor the initiation of a moderate intensity statin when present. Notably, the family history variable is an inexpensive and evidence-based tool to refine ASCVD risk estimation as its presence likely imparts a greater lifetime risk of ASCVD.3,4

In the context of the patient-clinician discussion, if a decision about statin therapy remains unclear, quantification of CAC can be considered as a decision aid for additional risk reclassification. Specifically, to those with a validated strong family history of coronary heart disease (CHD), the guidelines offer that even in absence of CAC (CAC=0), statin therapy should still be considered given a higher likelihood of the presence of non-calcified plaque or accelerated atherosclerosis (i.e., a shorter "warranty period" for CAC=0).5,6 In the short term (10-year), however, absolute event numbers remain low among those with a family history of  CHD and CAC=0 (<5 per 1000 person years).7 In this setting, given the moderate discriminative power of PCE and tendency to overpredict risk, a "statin-first" approach could potentially result in treating those with low absolute risk with no or little associated benefit in ASCVD risk reduction over the next decade.8

Although clinical practice guidelines endorse CAC to further stratify ASCVD risk, reimbursement for this test remains variable.2 Indeed, the appropriate use of CAC has been shown to increase utilization of testing among often undertreated populations such as women, African Americans, and those living in lower income neighborhoods, and contributes to uptake in preventive medications and improvement in risk factors and lipid biomarkers.9,10

In this setting, Venkataraman et al. constructed a sophisticated microsimulation model, showing that CAC screening and treatment of asymptomatic, intermediate risk individuals with FHCAD and subclinical disease was more cost-effective when compared to standard care (ASCVD risk estimation).1 Despite different assumptions, study populations, and methodologies, the current study's conclusion aligns with recent publications for those at intermediate risk when comparing the cost-effectiveness of CAC to standard PCE risk assessment.1,11-14

Ultimately, a "CAC-guided" strategy could tailor prevention management for individuals with evidence of atherosclerosis to include more aggressive lifestyle modifications and pursuing pharmacotherapy; the absence of atherosclerosis would obviate against the need for statin therapy. Indeed, among individuals at intermediate risk with FHCAD, ASCVD rates were generally lower than the recommended threshold to initiate statin therapy when CAC=0.15 Considering the presence of a premature family history of CHD imparts a higher lifetime risk of ASCVD and carries an odd ratio of 1.55 (p <0.01) for the incident development of CAC (baseline CAC=0, mean interval between CAC scans 3.1±1.3 years), repeat CAC testing may be indicated and should follow available guidelines to help guide allocation of preventive pharmacotherapy.2,6


  1. Venkataraman P, Kawakami H, Huynh Q, et al. Cost-effectiveness of coronary artery calcium scoring in people with a family history of coronary disease. JACC Cardiovasc Imaging 2021;14:1206-17.
  2. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;73:e285-e350.
  3. Patel J, Al Rifai M, Scheuner MT, et al. Basic vs more complex definitions of family history in the prediction of coronary heart disease: the multi-ethnic study of atherosclerosis. Mayo Clin Proc 2018;93:1213-23.
  4. Lloyd-Jones DM, Nam BH, D'Agostino RB Sr, et al. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. JAMA 2004;291:2204-11.
  5. Cohen R, Budoff M, McClelland RL, et al. Significance of a positive family history for coronary heart disease in patients with a zero coronary artery calcium score (from the multi-ethnic study of atherosclerosis). Am J Cardiol 2014;114:1210-14.
  6. Pandey AK, Blaha MJ, Sharma K, et al. Family history of coronary heart disease and the incidence and progression of coronary artery calcification: multi-ethnic study of atherosclerosis (MESA). Atherosclerosis 2014;232:369-76.
  7. Patel J, Al Rifai M, Blaha MJ, et al. Coronary artery calcium improves risk assessment in adults with a family history of premature coronary heart disease: results from multi-ethnic study of atherosclerosis. Circ Cardiovasc Imaging 2015;8:e003186.
  8. DeFilippis AP, Young R, Carrubba CJ, et al. An analysis of calibration and discrimination among multiple cardiovascular risk scores in a modern multiethnic cohort. Ann Intern Med 2015;162:266–75.
  9. Al-Kindi SG, Costa M, Tashtish N, et al. No-charge coronary artery calcium screening for cardiovascular risk assessment. J Am Coll Cardiol 2020;76:1259-62.
  10. Kalia NK, Cespedes L, Youssef G, Li D, Budoff MJ. Motivational effects of coronary artery calcium scores on statin adherence and weight loss. Coron Artery Dis 2015;26:225-30.
  11. Hong JC, Blankstein R, Shaw LJ, et al. Implications of coronary artery calcium testing for treatment decisions among statin candidates according to the ACC/AHA cholesterol management guidelines: a cost-effectiveness analysis. JACC Cardiovasc Imaging 2017;10:938-52.
  12. Spahillari A, Zhu J, Ferket BS, et al. Cost-effectiveness of contemporary statin use guidelines with or without coronary artery calcium assessment in African American individuals. JAMA Cardiol 2020;5:871-80.
  13. Pletcher MJ, Pignone M, Earnshaw S, et al. Using the coronary artery calcium score to guide statin therapy: a cost-effectiveness analysis. Circ Cardiovasc Qual Outcomes 2014;7:276-84.
  14. Roberts ET, Horne A, Martin SS, et al. Cost-effectiveness of coronary artery calcium testing for coronary heart and cardiovascular disease risk prediction to guide statin allocation: the multi-ethnic study of atherosclerosis (MESA). PLoS One 2015;10:e0116377.
  15. Patel J, Pallazola VA, Dudum R, et al. Assessment of coronary artery calcium scoring to guide statin therapy allocation according to risk-enhancing factors: the multi-ethnic study of atherosclerosis. JAMA Cardiol 2021;Jul 14:[Epub ahead of print].

Clinical Topics: Cardiovascular Care Team, Diabetes and Cardiometabolic Disease, Dyslipidemia, Atherosclerotic Disease (CAD/PAD), Lipid Metabolism, Nonstatins, Novel Agents, Statins

Keywords: Dyslipidemias, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Cholesterol, LDL, Calcium, Quality-Adjusted Life Years, Cost-Benefit Analysis, Coronary Artery Disease, African Americans, Cardiovascular Diseases, Atherosclerosis, Plaque, Atherosclerotic, Risk Assessment, Risk Factors, Treatment Outcome, Diabetes Mellitus, Biomarkers, Risk Reduction Behavior, Life Style, Delivery of Health Care, Resource Allocation, Decision Support Techniques, Reference Standards

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