CAC Screening Cost-effective for Statin Decisions in Hereditary CAD

Among patients with a family history of coronary artery disease, the systematic use of coronary artery calcium (CAC) screening to guide treatment is more cost-effective than using the current pooled cohort equation thresholds for initiating statin therapy, according to a new analysis.

Specifically, when compared with treating patients who have an early family history of disease and a 10-year risk of atherosclerotic cardiovascular disease (ASCVD) ≥ 7.5%, using CAC as a decision aid for statin treatment in those with subclinical disease was $145 more expensive upfront but translated into an incremental cost-effectiveness ratio (ICER) of $15,014 per quality-adjusted life-year (QALY) gained. Use of CAC even remained cost-effective when the benefits of statin therapy were adjusted downward to reflect real-world use instead of the benefits reported in clinical trials.

The researchers, led by Prasanna Venkataraman, MBBS (Monash University/Baker Heart and Diabetes Research Institute, Melbourne, Australia), say the study suggests that improving access to CAC screening, which may require support from payers, “is both clinically justified and economically prudent.”

The paper was published January 13, 2021, in JACC: Cardiovascular Imaging.

Fatima Rodriguez, MD (Stanford University School of Medicine, CA), who wasn’t involved in the study, said that if a patient has a family history of “early and aggressive” ASCVD but their estimated risk of disease is low according to the American College of Cardiology/American Heart Association (ACC/AHA) pooled cohort equations, she will request a CAC scan to help with the treatment decision, using the information alongside other risk markers, such as lipoprotein(a). If the CAC scan will not change treatment, such as in a patient with diabetes who should already be on a statin anyway, she won’t bother with the test. CAC can also be a tool to help identify high-risk patients who might benefit from primary prevention with aspirin, she added.

“However, the cost is not covered by most insurance companies, so patients must pay an out-of-pocket,” she told TCTMD via email. “This study adds to the growing literature that suggests that risk assessment with CAC is cost-effective and should be covered by insurance companies, particularly in patients where treatment decisions are uncertain.”

Similarly, Howard Weintraub, MD (NYU Grossman School of Medicine, New York, NY), said he frequently relies on family history, Lp(a), and CAC to guide treatment decisions in primary prevention, noting that CAC can be a good motivating visual for “statin-reluctant” patients. “Remember, CAC is usually not covered [by payers] so we have to convince the patient to pay $100 to $150, which is usually not a major problem but sometimes a real issue,” he said.

CAC as a Risk Enhancer

Both the primary prevention and cholesterol guidelines from the ACC/AHA recommend pooled cohort equations as the main tool to assess ASCVD risk, although the equations are known to have flaws when used in certain patient populations. The latest iteration of the guidelines introduced CAC scoring to help refine primary prevention risk assessment, particularly for those with a borderline or intermediate risk of CVD. The absence of calcium—the so-called “power of zero”—has been shown in several studies to identify patients at a very low risk of ASCVD.

There are also times when a statin is clearly indicated but patients are reluctant to start a long-term medication. In these cases, CAC is extremely helpful in guiding shared decision-making and promoting adherence. Fatima Rodriguez

The new cost-effective analysis is a microsimulation model based on 1,083 participants in CAUGHT-CAD, a study that used CAC to guide treatment in hereditary CAD. All participants in the study had a family history of premature CAD, were 40 to 70 years old, and had at least a 10-year risk of ASCVD ≥ 2.0% based on the ACC/AHA pooled cohort equations. The protocol assumed two treatment approaches: statin therapy in all patients with a 10-year risk of ASCVD ≥ 7.5% or treatment only in patients with a CAC score greater than zero. The model assumed patients were treated with atorvastatin 40 mg. In CAUGHT-CAD, 45.8% of patients had a positive CAC score and 24.6% had a predicted 10-year risk ≥ 7.5%.

Systematic CAC screening averted 476 more deaths and 1,314 symptomatic CVD events compared with the conventional ACC/AHA pooled cohort equation strategy and increased the per-patient QALYs by 0.0097. The average 15-year cost of the CAC approach was $6,059 versus $5,914 with the pooled cohort equations, while the number needed to scan to prevent one CVD event was 152. Systematic use of CAC screening “dominated” the pooled cohort equation approach when used in men and those older than 60 years. For men younger than 50 years and for women, the ICER was $358,656/QALY and $66,054/QALY, respectively.

Overall, the CAC strategy was cost-saving when compared standard risk assessment when the baseline 10-year of risk of ASCVD was ≥ 7.5%. It was cost-effective when applied to patients at borderline risk (5-7.5%) but was not cost-effective when applied to individuals at low risk of ASCVD (< 5.0%).

Some Caveats, and a Call for an RCT

In an editorial, Joseph Yeboah, MD (Wake Forest School of Medicine, Winston-Salem, NC), highlights several aspects of CAUGHT-CAD where trialists deviated from the ACC/AHA guidelines. For example, they used a modified definition of family history that included second-degree relatives with clinical CAD younger than 50 years. Additionally, they used 15 years of clinical ASCVD follow-up data as opposed to the pooled cohort equations that are based on ASCVD risk in the next 10 years. Importantly, they also assigned statin treatment to individuals with a 10-year risk of ASCVD ≥ 2.0% and CAC > 0. The ACC/AHA guidelines do not recommend treatment in these low-risk patients, instead advocating for statin therapy in those with a 10-year risk ranging from 5% to 20% and a CAC > 0.

To TCTMD, Weintraub also highlighted the aforementioned deviation from the clinical guidelines, but noted there are “plenty of patients” with a low 10-year risk of ASCVD based on the pooled cohort equation due to their age who are actually at high risk given their LDL cholesterol and Lp(a) levels. While the absence of zero calcification on screening is a compelling reason to avoid treatment, he added, it would never override other clinical variables, such as elevated LDL (> 160 mg/dL), diabetes, smoking, and, in his opinion, a significantly elevated Lp(a).

Rodriguez also noted that CAC is only recommended in those with a borderline or intermediate risk of ASCVD based on the pooled cohort equations; yet Hispanic and Asian patients, as well as very young or very old patients, were not studied in the validation cohorts used to develop the risk calculators. In those patients with a family history of CAD, a CAC test might be useful to guide treatment. She has seen patients with a low 10-year risk of ASCVD who have coronary calcium discovered in nongated chest CTs.

“In these cases, I usually go with the CAC and start the patient on a statin unless there are any contraindications or patient preference,” she said. “There are also times when a statin is clearly indicated but patients are reluctant to start a long-term medication. In these cases, CAC is extremely helpful in guiding shared decision-making and promoting adherence.”

In his editorial, Yeboah calls for a randomized trial to test the comparative efficacy of treatment based on the pooled cohort equation versus an approach that utilizes the risk calculator and risk-enhancing factors, such as CAC. Proof of efficacy of the CAC-guided approach, as well as a subsequent cost-effectiveness analysis, “would be the sure and unambiguous way to nudge insurance companies to reimburse CAC scoring for primary ASCVD prevention,” he writes.