Jonathon M. Firnhaber, MD

Prevention of cardiovascular disease (CVD) requires timely identification of people who are at increased risk in order to target effective dietary, lifestyle, or pharmacotherapeutic intervention—or a combination of the 3. Risk factors for CVD are well understood, but the relative impact of each factor on an individual’s overall risk is difficult to accurately quantify, making a validated CVD risk calculator an important clinical tool.

Despite numerous available CVD risk calculators, one best tool has yet to emerge. This state of affairs has limited the ability of front-line providers who are tasked with primary prevention of CVD—including family physicians (FPs)—to provide the best evidence-based recommendations to patients.

Implications of CVD risk assessment

Baseline CVD risk assessment is the cornerstone of recommendations for primary prevention of CVD, including aspirin and statin therapy. Interventions to lower CVD risk are of greatest benefit to those at highest risk at initiation of therapy. Overall, statins reduce the risk of a first cardiovascular event in otherwise healthy people by approximately 25% over 10 years.¹ Because relative risk reduction is fairly consistent across different levels of absolute risk, a 25% relative reduction confers more actual benefit if risk starts at, say, 40% than at 10%.² In that example, the same 25% reduction in relative risk results in 1) an absolute risk reduction of 10% when risk starts at 40%, compared to an absolute risk reduction of 2.5% when risk starts at 10% and 2) a number needed to treat (NNT) of, respectively, 10 and 40 (over 10 years).

Identifying a person with an elevated risk of developing CVD has multiple implications. Ideally, that patient is motivated to pursue positive therapeutic lifestyle modifications and make changes that positively affect long-term CVD risk. Conversely, that asymptomatic person identified as at elevated risk also becomes a patient with a medical problem that might adversely affect insurance premiums and self-esteem, and may trigger the use of medications with cost and potential adverse effects. Although the benefit of preventive therapy is greater for a patient at higher risk of disease, the harm of a therapy is relatively constant across all risk groups. Accurately discriminating high and low risk of CVD is, therefore, imperative.

The venerable Framingham risk score

Cardiovascular risk prediction has its roots in the late 1940s, when primary risk factors for CVD were not well-understood, with the inception of the Framingham Heart Study. (A greater understanding of CVD risk today notwithstanding, coronary artery disease [CAD] remains the leading cause of death among American adults.) In the late 1940s, blood pressure (BP) was recognized as the single most useful variable for identifying people at high risk of CVD; other variables were understood to be predictive as well. A composite score—the Framingham Risk Score (FRS)—was thereby developed to calculate the probability that CVD would occur over 8 years in a person who was initially free of such disease.³

While the benefit of a preventive therapy is greater for those at higher risk of disease, the harm of a therapy is relatively constant across all risk groups.

The original FRS included glucose intolerance and left ventricular hypertrophy (LVH) identified by electrocardiography (EKG) in its algorithm.³ Other, older algorithms also include a family history of premature CVD. In each risk calculator, these variables are treated as dichotomous (Yes or No), but actual risk associated with each variable is in fact more along a continuum. It is now well-recognized that the sensitivity of EKG for accurately detecting LVH is relatively low; more recent algorithms no longer include this component. A family history of premature CVD variably contributes to an individual’s CVD risk; however, its true impact is nearly impossible to accurately quantify, so this variable is also not included in more modern risk calculators.

Caution: The FRS has meaningful limitations

Although the original Framingham cohort has been expanded multiple times since its inception, clinicians and researchers continue to express concern that the predominantly white, middle-class Framingham, Massachusetts, population might not be representative of the United States in general—which would limit the accuracy of the FRS predictive tool when it is applied to a more diverse population. Furthermore, cholesterol-lowering medications were not available when the FRS was first developed. The FRS, therefore, might not accurately estimate risk in more modern populations, in whom aggressive modification of CVD risk factors has resulted in a lower overall rate of atherosclerotic CVD than when the FRS was developed.⁴

Continue to: Although demographic changes have increasingly...

Although demographic changes have increasingly led to an extension of primary prevention strategies for CAD to elderly people, the FRS has been demonstrated to perform less well in patients older than 70 years, particularly men.⁵ An ideal CAD prediction model for elderly people should take into account that, with growing age and frailty, CAD events may be increasingly preempted by death from competing non-coronary causes. In addition, the predictive association of typical CVD risk factors diminishes with increasing age.^6,7 Koller and colleagues developed a CAD risk prediction model that accounted for death from non-coronary causes and was validated specifically in patients 65 years and older. Koller’s prediction model provided well-calibrated risk estimates, but it was still not substantially more accurate than the FRS—illustrating the overall difficulty in predicting CAD risk in elderly people.⁸

Alternative risk calculators have come on the scene

Over the past 2 decades, numerous models have been developed in an attempt to overcome the perceived shortcomings of the FRS. A recent systematic review identified 363 prediction models described in the medical literature prior to July 2013.⁹ The usefulness of most models remains unclear, however, owing to:

• methodological shortcomings,
• considerable heterogeneity in the definitions of outcomes, and
• lack of external validation.

Even models that are well-validated for a specific population suffer from lack of applicability to a broad multinational population.

In the United Kingdom (UK), electronic health record systems now have the QRISK2 tool embedded to calculate 10-year CVD risk. This algorithm incorporates multiple traditional and nontraditional risk factors (TABLE¹⁰). With the inclusion of additional risk factors and validation performed in a population similar to the one from which the algorithm was derived, QRISK2 predicts CVD risk in the UK population more accurately than the modified FRS does.¹⁰ It is not clear, however, whether the same algorithm can be applied to the general US population.

New tool: 2013 ACC/AHA pooled cohort risk equations

In the context of multiple imperfect CVD risk-prediction algorithms, the American College of Cardiology/American Heart Association (ACC/AHA) Task Force on Practice Guidelines published the 2013 Pooled Cohort Risk (PCR) equations to predict 10-year risk of a first atherosclerotic CVD event. The Task Force acknowledged concern that the FRS is based on a cohort that might not accurately represent the general US population. Accordingly, PCR equations were developed from 5 large National Institutes of Health (NIH)-funded cohorts: the Framingham Heart Study, the Framingham Offspring Study, the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Coronary Artery Risk Development in Young Adults Study.

Continue to: The resulting CVD risk calculator incorporates...

The resulting CVD risk calculator incorporates 4 risk equations: 1 each for African-American and non-Hispanic white males and females.¹¹ Of note, PCR equations are typically used to estimate 10-year CVD risk, but they can be modified to estimate risk over any period. The associated Guideline on the Assessment of Cardiovascular Risk recommends statin therapy for primary prevention of CVD in patients with a predicted 10-year risk ≥7.5% and consideration of statin therapy for patients with a predicted 10-year risk between 5% and 7.5%.¹²

In late 2016, the US Preventive Services Task Force (USPSTF) recommended low- to moderate-dosage statin therapy in adults 40 to 75 years of age without a history of CVD but with at least 1 CVD risk factor (dyslipidemia, diabetes, hypertension, or smoking), and a PCR-calculated 10-year CVD risk of ≥10%. For people with a PCR-calculated risk of 7.5% to 10%, the USPSTF recommended that clinicians “selectively offer” low- to moderate-dosage statin therapy, noting a smaller likelihood of benefit and uncertainty in an individual’s risk prediction.¹³

Pooled cohort risk equations have predictive validity

Estimates are that nearly 50% of US adults and as many as 65% of European adults would be candidates for statin therapy if, using PCR equations, the 2013 ACC/AHA guidelines were broadly applied.¹⁴ Since PCR equations were released, multiple groups have attempted to evaluate the predictive validity of the algorithm in various populations, with mixed findings.

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated, in terms of hard clinical outcomes.

Data from the 1999-2010 NHANES—the National Health and Nutrition Examination Survey—were used to calculate estimated CVD risk for patients free of atherosclerotic CVD at baseline. Risk prediction using PCR equations was compared to true all-cause and CVD mortality using the National Center for Health Statistics National Death Index. In this large, US adult population without CVD at baseline, PCR-estimated CVD risk was significantly associated with all-cause and CVD-specific mortality risk.¹⁵

In a community-based primary prevention cohort, 39% of participants were found statin-eligible—ie, they had an estimated 10-year CVD risk ≥7.5%—by ACC/AHA guidelines, compared with 14% found statin-eligible by the guidelines of the National Cholesterol Education Program’s 2004 updated “Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III).” Despite the larger percentage, participants who were statin-eligible by ACC/AHA guidelines had an increased hazard ratio for incident CVD compared with those who were statin-eligible by ATP III; investigators concluded that ACC/AHA guidelines using PCR equations were associated with greater accuracy and efficiency in identifying increased risk of incident CVD.¹⁶

Continue to: Pooled cohort risk equations might overestimate CVD risk

In contrast, a more recent study followed a large, integrated US health-care delivery system population over 5 years, starting in 2008.¹⁷ In this group of adults without diabetes, PCR equations substantially overestimated actual 5-year risk of CVD in both sexes and across multiple socioeconomic strata. Similar overestimation of CVD risk was demonstrated in non-Hispanic white, non-Hispanic black, Asian/Pacific Islander, and Hispanic subjects. The latter 2 ethnic groups are considered “white or other” in the atherosclerotic CVD risk equation, raising additional concern that PCR equations may not be accurate for broad, multiethnic application.¹⁷ The ACC/AHA Cardiovascular Risk Assessment guideline recognizes this concern, as well, noting that PCR equations may overestimate risk for Hispanic and Asian Americans.¹²

ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit.

Predicted 10-year CVD risk using PCR equations was compared with observed event rates in 3 large-scale primary prevention cohorts: the Women’s Health Study, the Physicians’ Health Study, and the Women’s Health Initiative Observational Study.¹⁸ In each cohort, the ACC/AHA risk prediction algorithm overestimated observed risk by 75% to 150%. The authors concluded that 40% to 50% of the 33 million middle-aged Americans deemed statin-eligible by ACC/AHA guidelines may not have actual CVD risk that exceeds the 7.5% threshold recommended for statin treatment.¹⁸

Therefore, the discrimination of PCR equations—their ability to differentiate between individuals who are more or less likely to develop clinical CVD—is good. The calibration of the equations—the difference between predicted and observed risk—is not as good, however: PCR equations appear to overestimate actual risk in many groups.¹⁵

Additional limitations to pooled cohort risk equations

The predictive value of PCR equations is hampered by several factors:

• Despite expansion of the studied cohorts beyond the original Framingham population, the groups still include people screened for study participation or enrolled in clinical trials. The generalizability of this study population to the diverse population treated in a typical clinical practice is, potentially, limited.
• Use of strategies for primary prevention of CVD (eg, statin therapy, antiplatelet therapy, BP control, blood glucose control) continues to increase. Lowering the risk of CVD in the general population with a broad primary prevention approach effectively widens the gap between observed and equation-predicted CVD risk—and thus strengthens the impression of overestimation of risk by PCR equations.
• Lack of comprehensive surveillance in some studies may result in underassessment of CVD events. In this case, PCR equations would, again, appear to overestimate risk.¹⁹

Novel tools are available; their use is qualified

First, newer risk markers offer additional options for improving risk prediction offered by the ACC/AHA PCR equations: Coronary artery calcium, ankle-brachial index, high-sensitivity C-reactive protein, and a family history of CAD are all independently associated with incident CAD. ACC/AHA guidelines suggest that assessment of 1 or more of these variables might be considered an adjunct when risk assessment using PCR equations alone does not offer information for making a clear treatment decision.¹²

Continue to: Of the 4 risk markers...

Of the 4 risk markers, coronary artery calcium provides the most significant increase in discrimination compared to the FRS alone; comparative data using PCR equations is unavailable.²⁰ ACC/AHA guidelines specifically recommend against routine measurement of carotid intima-media thickness for assessment of risk of a first atherosclerotic event.¹²

Second, a revised set of PCR equations offers improved discrimination and calibration compared to the 2013 PCR equations. A National Institutes of Health (NIH)-sponsored group updated the equations’ cohort by 1) eliminating the original Framingham Heart Study (FHS) data, which was first collected in 1948, and 2) adding data from the Jackson Heart Study and the Multi-Ethnic Study of Atherosclerosis (MESA). Both new cohorts include patient data from 2000 to 2012. Additionally, the NIH group modified the statistical methods used to derive PCR equations. Although these revised PCR equations offer a substantially more accurate estimate of CVD risk, they have not yet been validated for routine clinical use.²¹

Bottom line: In prediction there persists imperfection

It is widely held that CVD risk prediction, with subsequent treatment to reduce identified risk, is an important component of an overall strategy to reduce the burden of CVD. Cardiovascular risk factors, such as BP and lipid values, do show limited improvement among populations in which systematic screening is practiced, but the true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.²²

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.

CVD risk prediction is most widely used to inform recommendations for statin treatment. However, ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit. Nonetheless, PCR equations do offer good discrimination between higher-risk and lower-risk people.

CVD risk prediction remains an imperfect science—science that is best used as an adjunct to discussion of comprehensive CVD risk factor modification with the individual patient.

CORRESPONDENCE
Jonathon M. Firnhaber, MD, Brody School of Medicine, East Carolina University, 101 Heart Drive, Greenville, NC 27834; firnhaberj@ecu.edu.

Prevention of cardiovascular disease (CVD) requires timely identification of people who are at increased risk in order to target effective dietary, lifestyle, or pharmacotherapeutic intervention—or a combination of the 3. Risk factors for CVD are well understood, but the relative impact of each factor on an individual’s overall risk is difficult to accurately quantify, making a validated CVD risk calculator an important clinical tool.

Despite numerous available CVD risk calculators, one best tool has yet to emerge. This state of affairs has limited the ability of front-line providers who are tasked with primary prevention of CVD—including family physicians (FPs)—to provide the best evidence-based recommendations to patients.

Implications of CVD risk assessment

Baseline CVD risk assessment is the cornerstone of recommendations for primary prevention of CVD, including aspirin and statin therapy. Interventions to lower CVD risk are of greatest benefit to those at highest risk at initiation of therapy. Overall, statins reduce the risk of a first cardiovascular event in otherwise healthy people by approximately 25% over 10 years.¹ Because relative risk reduction is fairly consistent across different levels of absolute risk, a 25% relative reduction confers more actual benefit if risk starts at, say, 40% than at 10%.² In that example, the same 25% reduction in relative risk results in 1) an absolute risk reduction of 10% when risk starts at 40%, compared to an absolute risk reduction of 2.5% when risk starts at 10% and 2) a number needed to treat (NNT) of, respectively, 10 and 40 (over 10 years).

Identifying a person with an elevated risk of developing CVD has multiple implications. Ideally, that patient is motivated to pursue positive therapeutic lifestyle modifications and make changes that positively affect long-term CVD risk. Conversely, that asymptomatic person identified as at elevated risk also becomes a patient with a medical problem that might adversely affect insurance premiums and self-esteem, and may trigger the use of medications with cost and potential adverse effects. Although the benefit of preventive therapy is greater for a patient at higher risk of disease, the harm of a therapy is relatively constant across all risk groups. Accurately discriminating high and low risk of CVD is, therefore, imperative.

The venerable Framingham risk score

Cardiovascular risk prediction has its roots in the late 1940s, when primary risk factors for CVD were not well-understood, with the inception of the Framingham Heart Study. (A greater understanding of CVD risk today notwithstanding, coronary artery disease [CAD] remains the leading cause of death among American adults.) In the late 1940s, blood pressure (BP) was recognized as the single most useful variable for identifying people at high risk of CVD; other variables were understood to be predictive as well. A composite score—the Framingham Risk Score (FRS)—was thereby developed to calculate the probability that CVD would occur over 8 years in a person who was initially free of such disease.³

While the benefit of a preventive therapy is greater for those at higher risk of disease, the harm of a therapy is relatively constant across all risk groups.

The original FRS included glucose intolerance and left ventricular hypertrophy (LVH) identified by electrocardiography (EKG) in its algorithm.³ Other, older algorithms also include a family history of premature CVD. In each risk calculator, these variables are treated as dichotomous (Yes or No), but actual risk associated with each variable is in fact more along a continuum. It is now well-recognized that the sensitivity of EKG for accurately detecting LVH is relatively low; more recent algorithms no longer include this component. A family history of premature CVD variably contributes to an individual’s CVD risk; however, its true impact is nearly impossible to accurately quantify, so this variable is also not included in more modern risk calculators.

Caution: The FRS has meaningful limitations

Although the original Framingham cohort has been expanded multiple times since its inception, clinicians and researchers continue to express concern that the predominantly white, middle-class Framingham, Massachusetts, population might not be representative of the United States in general—which would limit the accuracy of the FRS predictive tool when it is applied to a more diverse population. Furthermore, cholesterol-lowering medications were not available when the FRS was first developed. The FRS, therefore, might not accurately estimate risk in more modern populations, in whom aggressive modification of CVD risk factors has resulted in a lower overall rate of atherosclerotic CVD than when the FRS was developed.⁴

Continue to: Although demographic changes have increasingly...

Although demographic changes have increasingly led to an extension of primary prevention strategies for CAD to elderly people, the FRS has been demonstrated to perform less well in patients older than 70 years, particularly men.⁵ An ideal CAD prediction model for elderly people should take into account that, with growing age and frailty, CAD events may be increasingly preempted by death from competing non-coronary causes. In addition, the predictive association of typical CVD risk factors diminishes with increasing age.^6,7 Koller and colleagues developed a CAD risk prediction model that accounted for death from non-coronary causes and was validated specifically in patients 65 years and older. Koller’s prediction model provided well-calibrated risk estimates, but it was still not substantially more accurate than the FRS—illustrating the overall difficulty in predicting CAD risk in elderly people.⁸

Alternative risk calculators have come on the scene

Over the past 2 decades, numerous models have been developed in an attempt to overcome the perceived shortcomings of the FRS. A recent systematic review identified 363 prediction models described in the medical literature prior to July 2013.⁹ The usefulness of most models remains unclear, however, owing to:

• methodological shortcomings,
• considerable heterogeneity in the definitions of outcomes, and
• lack of external validation.

Even models that are well-validated for a specific population suffer from lack of applicability to a broad multinational population.

In the United Kingdom (UK), electronic health record systems now have the QRISK2 tool embedded to calculate 10-year CVD risk. This algorithm incorporates multiple traditional and nontraditional risk factors (TABLE¹⁰). With the inclusion of additional risk factors and validation performed in a population similar to the one from which the algorithm was derived, QRISK2 predicts CVD risk in the UK population more accurately than the modified FRS does.¹⁰ It is not clear, however, whether the same algorithm can be applied to the general US population.

New tool: 2013 ACC/AHA pooled cohort risk equations

In the context of multiple imperfect CVD risk-prediction algorithms, the American College of Cardiology/American Heart Association (ACC/AHA) Task Force on Practice Guidelines published the 2013 Pooled Cohort Risk (PCR) equations to predict 10-year risk of a first atherosclerotic CVD event. The Task Force acknowledged concern that the FRS is based on a cohort that might not accurately represent the general US population. Accordingly, PCR equations were developed from 5 large National Institutes of Health (NIH)-funded cohorts: the Framingham Heart Study, the Framingham Offspring Study, the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Coronary Artery Risk Development in Young Adults Study.

Continue to: The resulting CVD risk calculator incorporates...

The resulting CVD risk calculator incorporates 4 risk equations: 1 each for African-American and non-Hispanic white males and females.¹¹ Of note, PCR equations are typically used to estimate 10-year CVD risk, but they can be modified to estimate risk over any period. The associated Guideline on the Assessment of Cardiovascular Risk recommends statin therapy for primary prevention of CVD in patients with a predicted 10-year risk ≥7.5% and consideration of statin therapy for patients with a predicted 10-year risk between 5% and 7.5%.¹²

In late 2016, the US Preventive Services Task Force (USPSTF) recommended low- to moderate-dosage statin therapy in adults 40 to 75 years of age without a history of CVD but with at least 1 CVD risk factor (dyslipidemia, diabetes, hypertension, or smoking), and a PCR-calculated 10-year CVD risk of ≥10%. For people with a PCR-calculated risk of 7.5% to 10%, the USPSTF recommended that clinicians “selectively offer” low- to moderate-dosage statin therapy, noting a smaller likelihood of benefit and uncertainty in an individual’s risk prediction.¹³

Pooled cohort risk equations have predictive validity

Estimates are that nearly 50% of US adults and as many as 65% of European adults would be candidates for statin therapy if, using PCR equations, the 2013 ACC/AHA guidelines were broadly applied.¹⁴ Since PCR equations were released, multiple groups have attempted to evaluate the predictive validity of the algorithm in various populations, with mixed findings.

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated, in terms of hard clinical outcomes.

Data from the 1999-2010 NHANES—the National Health and Nutrition Examination Survey—were used to calculate estimated CVD risk for patients free of atherosclerotic CVD at baseline. Risk prediction using PCR equations was compared to true all-cause and CVD mortality using the National Center for Health Statistics National Death Index. In this large, US adult population without CVD at baseline, PCR-estimated CVD risk was significantly associated with all-cause and CVD-specific mortality risk.¹⁵

In a community-based primary prevention cohort, 39% of participants were found statin-eligible—ie, they had an estimated 10-year CVD risk ≥7.5%—by ACC/AHA guidelines, compared with 14% found statin-eligible by the guidelines of the National Cholesterol Education Program’s 2004 updated “Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III).” Despite the larger percentage, participants who were statin-eligible by ACC/AHA guidelines had an increased hazard ratio for incident CVD compared with those who were statin-eligible by ATP III; investigators concluded that ACC/AHA guidelines using PCR equations were associated with greater accuracy and efficiency in identifying increased risk of incident CVD.¹⁶

Continue to: Pooled cohort risk equations might overestimate CVD risk

In contrast, a more recent study followed a large, integrated US health-care delivery system population over 5 years, starting in 2008.¹⁷ In this group of adults without diabetes, PCR equations substantially overestimated actual 5-year risk of CVD in both sexes and across multiple socioeconomic strata. Similar overestimation of CVD risk was demonstrated in non-Hispanic white, non-Hispanic black, Asian/Pacific Islander, and Hispanic subjects. The latter 2 ethnic groups are considered “white or other” in the atherosclerotic CVD risk equation, raising additional concern that PCR equations may not be accurate for broad, multiethnic application.¹⁷ The ACC/AHA Cardiovascular Risk Assessment guideline recognizes this concern, as well, noting that PCR equations may overestimate risk for Hispanic and Asian Americans.¹²

ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit.

Predicted 10-year CVD risk using PCR equations was compared with observed event rates in 3 large-scale primary prevention cohorts: the Women’s Health Study, the Physicians’ Health Study, and the Women’s Health Initiative Observational Study.¹⁸ In each cohort, the ACC/AHA risk prediction algorithm overestimated observed risk by 75% to 150%. The authors concluded that 40% to 50% of the 33 million middle-aged Americans deemed statin-eligible by ACC/AHA guidelines may not have actual CVD risk that exceeds the 7.5% threshold recommended for statin treatment.¹⁸

Therefore, the discrimination of PCR equations—their ability to differentiate between individuals who are more or less likely to develop clinical CVD—is good. The calibration of the equations—the difference between predicted and observed risk—is not as good, however: PCR equations appear to overestimate actual risk in many groups.¹⁵

Additional limitations to pooled cohort risk equations

The predictive value of PCR equations is hampered by several factors:

• Despite expansion of the studied cohorts beyond the original Framingham population, the groups still include people screened for study participation or enrolled in clinical trials. The generalizability of this study population to the diverse population treated in a typical clinical practice is, potentially, limited.
• Use of strategies for primary prevention of CVD (eg, statin therapy, antiplatelet therapy, BP control, blood glucose control) continues to increase. Lowering the risk of CVD in the general population with a broad primary prevention approach effectively widens the gap between observed and equation-predicted CVD risk—and thus strengthens the impression of overestimation of risk by PCR equations.
• Lack of comprehensive surveillance in some studies may result in underassessment of CVD events. In this case, PCR equations would, again, appear to overestimate risk.¹⁹

Novel tools are available; their use is qualified

First, newer risk markers offer additional options for improving risk prediction offered by the ACC/AHA PCR equations: Coronary artery calcium, ankle-brachial index, high-sensitivity C-reactive protein, and a family history of CAD are all independently associated with incident CAD. ACC/AHA guidelines suggest that assessment of 1 or more of these variables might be considered an adjunct when risk assessment using PCR equations alone does not offer information for making a clear treatment decision.¹²

Continue to: Of the 4 risk markers...

Of the 4 risk markers, coronary artery calcium provides the most significant increase in discrimination compared to the FRS alone; comparative data using PCR equations is unavailable.²⁰ ACC/AHA guidelines specifically recommend against routine measurement of carotid intima-media thickness for assessment of risk of a first atherosclerotic event.¹²

Second, a revised set of PCR equations offers improved discrimination and calibration compared to the 2013 PCR equations. A National Institutes of Health (NIH)-sponsored group updated the equations’ cohort by 1) eliminating the original Framingham Heart Study (FHS) data, which was first collected in 1948, and 2) adding data from the Jackson Heart Study and the Multi-Ethnic Study of Atherosclerosis (MESA). Both new cohorts include patient data from 2000 to 2012. Additionally, the NIH group modified the statistical methods used to derive PCR equations. Although these revised PCR equations offer a substantially more accurate estimate of CVD risk, they have not yet been validated for routine clinical use.²¹

Bottom line: In prediction there persists imperfection

It is widely held that CVD risk prediction, with subsequent treatment to reduce identified risk, is an important component of an overall strategy to reduce the burden of CVD. Cardiovascular risk factors, such as BP and lipid values, do show limited improvement among populations in which systematic screening is practiced, but the true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.²²

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.

CVD risk prediction is most widely used to inform recommendations for statin treatment. However, ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit. Nonetheless, PCR equations do offer good discrimination between higher-risk and lower-risk people.

CVD risk prediction remains an imperfect science—science that is best used as an adjunct to discussion of comprehensive CVD risk factor modification with the individual patient.

CORRESPONDENCE
Jonathon M. Firnhaber, MD, Brody School of Medicine, East Carolina University, 101 Heart Drive, Greenville, NC 27834; firnhaberj@ecu.edu.

Prevention of cardiovascular disease (CVD) requires timely identification of people who are at increased risk in order to target effective dietary, lifestyle, or pharmacotherapeutic intervention—or a combination of the 3. Risk factors for CVD are well understood, but the relative impact of each factor on an individual’s overall risk is difficult to accurately quantify, making a validated CVD risk calculator an important clinical tool.

Despite numerous available CVD risk calculators, one best tool has yet to emerge. This state of affairs has limited the ability of front-line providers who are tasked with primary prevention of CVD—including family physicians (FPs)—to provide the best evidence-based recommendations to patients.

Implications of CVD risk assessment

Baseline CVD risk assessment is the cornerstone of recommendations for primary prevention of CVD, including aspirin and statin therapy. Interventions to lower CVD risk are of greatest benefit to those at highest risk at initiation of therapy. Overall, statins reduce the risk of a first cardiovascular event in otherwise healthy people by approximately 25% over 10 years.¹ Because relative risk reduction is fairly consistent across different levels of absolute risk, a 25% relative reduction confers more actual benefit if risk starts at, say, 40% than at 10%.² In that example, the same 25% reduction in relative risk results in 1) an absolute risk reduction of 10% when risk starts at 40%, compared to an absolute risk reduction of 2.5% when risk starts at 10% and 2) a number needed to treat (NNT) of, respectively, 10 and 40 (over 10 years).

Identifying a person with an elevated risk of developing CVD has multiple implications. Ideally, that patient is motivated to pursue positive therapeutic lifestyle modifications and make changes that positively affect long-term CVD risk. Conversely, that asymptomatic person identified as at elevated risk also becomes a patient with a medical problem that might adversely affect insurance premiums and self-esteem, and may trigger the use of medications with cost and potential adverse effects. Although the benefit of preventive therapy is greater for a patient at higher risk of disease, the harm of a therapy is relatively constant across all risk groups. Accurately discriminating high and low risk of CVD is, therefore, imperative.

The venerable Framingham risk score

Cardiovascular risk prediction has its roots in the late 1940s, when primary risk factors for CVD were not well-understood, with the inception of the Framingham Heart Study. (A greater understanding of CVD risk today notwithstanding, coronary artery disease [CAD] remains the leading cause of death among American adults.) In the late 1940s, blood pressure (BP) was recognized as the single most useful variable for identifying people at high risk of CVD; other variables were understood to be predictive as well. A composite score—the Framingham Risk Score (FRS)—was thereby developed to calculate the probability that CVD would occur over 8 years in a person who was initially free of such disease.³

While the benefit of a preventive therapy is greater for those at higher risk of disease, the harm of a therapy is relatively constant across all risk groups.

The original FRS included glucose intolerance and left ventricular hypertrophy (LVH) identified by electrocardiography (EKG) in its algorithm.³ Other, older algorithms also include a family history of premature CVD. In each risk calculator, these variables are treated as dichotomous (Yes or No), but actual risk associated with each variable is in fact more along a continuum. It is now well-recognized that the sensitivity of EKG for accurately detecting LVH is relatively low; more recent algorithms no longer include this component. A family history of premature CVD variably contributes to an individual’s CVD risk; however, its true impact is nearly impossible to accurately quantify, so this variable is also not included in more modern risk calculators.

Caution: The FRS has meaningful limitations

Although the original Framingham cohort has been expanded multiple times since its inception, clinicians and researchers continue to express concern that the predominantly white, middle-class Framingham, Massachusetts, population might not be representative of the United States in general—which would limit the accuracy of the FRS predictive tool when it is applied to a more diverse population. Furthermore, cholesterol-lowering medications were not available when the FRS was first developed. The FRS, therefore, might not accurately estimate risk in more modern populations, in whom aggressive modification of CVD risk factors has resulted in a lower overall rate of atherosclerotic CVD than when the FRS was developed.⁴

Continue to: Although demographic changes have increasingly...

Although demographic changes have increasingly led to an extension of primary prevention strategies for CAD to elderly people, the FRS has been demonstrated to perform less well in patients older than 70 years, particularly men.⁵ An ideal CAD prediction model for elderly people should take into account that, with growing age and frailty, CAD events may be increasingly preempted by death from competing non-coronary causes. In addition, the predictive association of typical CVD risk factors diminishes with increasing age.^6,7 Koller and colleagues developed a CAD risk prediction model that accounted for death from non-coronary causes and was validated specifically in patients 65 years and older. Koller’s prediction model provided well-calibrated risk estimates, but it was still not substantially more accurate than the FRS—illustrating the overall difficulty in predicting CAD risk in elderly people.⁸

Alternative risk calculators have come on the scene

Over the past 2 decades, numerous models have been developed in an attempt to overcome the perceived shortcomings of the FRS. A recent systematic review identified 363 prediction models described in the medical literature prior to July 2013.⁹ The usefulness of most models remains unclear, however, owing to:

• methodological shortcomings,
• considerable heterogeneity in the definitions of outcomes, and
• lack of external validation.

Even models that are well-validated for a specific population suffer from lack of applicability to a broad multinational population.

In the United Kingdom (UK), electronic health record systems now have the QRISK2 tool embedded to calculate 10-year CVD risk. This algorithm incorporates multiple traditional and nontraditional risk factors (TABLE¹⁰). With the inclusion of additional risk factors and validation performed in a population similar to the one from which the algorithm was derived, QRISK2 predicts CVD risk in the UK population more accurately than the modified FRS does.¹⁰ It is not clear, however, whether the same algorithm can be applied to the general US population.

New tool: 2013 ACC/AHA pooled cohort risk equations

In the context of multiple imperfect CVD risk-prediction algorithms, the American College of Cardiology/American Heart Association (ACC/AHA) Task Force on Practice Guidelines published the 2013 Pooled Cohort Risk (PCR) equations to predict 10-year risk of a first atherosclerotic CVD event. The Task Force acknowledged concern that the FRS is based on a cohort that might not accurately represent the general US population. Accordingly, PCR equations were developed from 5 large National Institutes of Health (NIH)-funded cohorts: the Framingham Heart Study, the Framingham Offspring Study, the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Coronary Artery Risk Development in Young Adults Study.

Continue to: The resulting CVD risk calculator incorporates...

The resulting CVD risk calculator incorporates 4 risk equations: 1 each for African-American and non-Hispanic white males and females.¹¹ Of note, PCR equations are typically used to estimate 10-year CVD risk, but they can be modified to estimate risk over any period. The associated Guideline on the Assessment of Cardiovascular Risk recommends statin therapy for primary prevention of CVD in patients with a predicted 10-year risk ≥7.5% and consideration of statin therapy for patients with a predicted 10-year risk between 5% and 7.5%.¹²

In late 2016, the US Preventive Services Task Force (USPSTF) recommended low- to moderate-dosage statin therapy in adults 40 to 75 years of age without a history of CVD but with at least 1 CVD risk factor (dyslipidemia, diabetes, hypertension, or smoking), and a PCR-calculated 10-year CVD risk of ≥10%. For people with a PCR-calculated risk of 7.5% to 10%, the USPSTF recommended that clinicians “selectively offer” low- to moderate-dosage statin therapy, noting a smaller likelihood of benefit and uncertainty in an individual’s risk prediction.¹³

Pooled cohort risk equations have predictive validity

Estimates are that nearly 50% of US adults and as many as 65% of European adults would be candidates for statin therapy if, using PCR equations, the 2013 ACC/AHA guidelines were broadly applied.¹⁴ Since PCR equations were released, multiple groups have attempted to evaluate the predictive validity of the algorithm in various populations, with mixed findings.

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated, in terms of hard clinical outcomes.

Data from the 1999-2010 NHANES—the National Health and Nutrition Examination Survey—were used to calculate estimated CVD risk for patients free of atherosclerotic CVD at baseline. Risk prediction using PCR equations was compared to true all-cause and CVD mortality using the National Center for Health Statistics National Death Index. In this large, US adult population without CVD at baseline, PCR-estimated CVD risk was significantly associated with all-cause and CVD-specific mortality risk.¹⁵

In a community-based primary prevention cohort, 39% of participants were found statin-eligible—ie, they had an estimated 10-year CVD risk ≥7.5%—by ACC/AHA guidelines, compared with 14% found statin-eligible by the guidelines of the National Cholesterol Education Program’s 2004 updated “Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III).” Despite the larger percentage, participants who were statin-eligible by ACC/AHA guidelines had an increased hazard ratio for incident CVD compared with those who were statin-eligible by ATP III; investigators concluded that ACC/AHA guidelines using PCR equations were associated with greater accuracy and efficiency in identifying increased risk of incident CVD.¹⁶

Continue to: Pooled cohort risk equations might overestimate CVD risk

In contrast, a more recent study followed a large, integrated US health-care delivery system population over 5 years, starting in 2008.¹⁷ In this group of adults without diabetes, PCR equations substantially overestimated actual 5-year risk of CVD in both sexes and across multiple socioeconomic strata. Similar overestimation of CVD risk was demonstrated in non-Hispanic white, non-Hispanic black, Asian/Pacific Islander, and Hispanic subjects. The latter 2 ethnic groups are considered “white or other” in the atherosclerotic CVD risk equation, raising additional concern that PCR equations may not be accurate for broad, multiethnic application.¹⁷ The ACC/AHA Cardiovascular Risk Assessment guideline recognizes this concern, as well, noting that PCR equations may overestimate risk for Hispanic and Asian Americans.¹²

ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit.

Predicted 10-year CVD risk using PCR equations was compared with observed event rates in 3 large-scale primary prevention cohorts: the Women’s Health Study, the Physicians’ Health Study, and the Women’s Health Initiative Observational Study.¹⁸ In each cohort, the ACC/AHA risk prediction algorithm overestimated observed risk by 75% to 150%. The authors concluded that 40% to 50% of the 33 million middle-aged Americans deemed statin-eligible by ACC/AHA guidelines may not have actual CVD risk that exceeds the 7.5% threshold recommended for statin treatment.¹⁸

Therefore, the discrimination of PCR equations—their ability to differentiate between individuals who are more or less likely to develop clinical CVD—is good. The calibration of the equations—the difference between predicted and observed risk—is not as good, however: PCR equations appear to overestimate actual risk in many groups.¹⁵

Additional limitations to pooled cohort risk equations

The predictive value of PCR equations is hampered by several factors:

• Despite expansion of the studied cohorts beyond the original Framingham population, the groups still include people screened for study participation or enrolled in clinical trials. The generalizability of this study population to the diverse population treated in a typical clinical practice is, potentially, limited.
• Use of strategies for primary prevention of CVD (eg, statin therapy, antiplatelet therapy, BP control, blood glucose control) continues to increase. Lowering the risk of CVD in the general population with a broad primary prevention approach effectively widens the gap between observed and equation-predicted CVD risk—and thus strengthens the impression of overestimation of risk by PCR equations.
• Lack of comprehensive surveillance in some studies may result in underassessment of CVD events. In this case, PCR equations would, again, appear to overestimate risk.¹⁹

Novel tools are available; their use is qualified

First, newer risk markers offer additional options for improving risk prediction offered by the ACC/AHA PCR equations: Coronary artery calcium, ankle-brachial index, high-sensitivity C-reactive protein, and a family history of CAD are all independently associated with incident CAD. ACC/AHA guidelines suggest that assessment of 1 or more of these variables might be considered an adjunct when risk assessment using PCR equations alone does not offer information for making a clear treatment decision.¹²

Continue to: Of the 4 risk markers...

Of the 4 risk markers, coronary artery calcium provides the most significant increase in discrimination compared to the FRS alone; comparative data using PCR equations is unavailable.²⁰ ACC/AHA guidelines specifically recommend against routine measurement of carotid intima-media thickness for assessment of risk of a first atherosclerotic event.¹²

Second, a revised set of PCR equations offers improved discrimination and calibration compared to the 2013 PCR equations. A National Institutes of Health (NIH)-sponsored group updated the equations’ cohort by 1) eliminating the original Framingham Heart Study (FHS) data, which was first collected in 1948, and 2) adding data from the Jackson Heart Study and the Multi-Ethnic Study of Atherosclerosis (MESA). Both new cohorts include patient data from 2000 to 2012. Additionally, the NIH group modified the statistical methods used to derive PCR equations. Although these revised PCR equations offer a substantially more accurate estimate of CVD risk, they have not yet been validated for routine clinical use.²¹

Bottom line: In prediction there persists imperfection

It is widely held that CVD risk prediction, with subsequent treatment to reduce identified risk, is an important component of an overall strategy to reduce the burden of CVD. Cardiovascular risk factors, such as BP and lipid values, do show limited improvement among populations in which systematic screening is practiced, but the true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.²²

The true impact of systematic CVD risk assessment alone for healthy people has yet to be demonstrated in terms of hard clinical outcomes.

CVD risk prediction is most widely used to inform recommendations for statin treatment. However, ACC/AHA PCR equations might substantially overestimate CVD risk and lead to expanded use of statins in patient populations for which such treatment has less potential benefit. Nonetheless, PCR equations do offer good discrimination between higher-risk and lower-risk people.

CVD risk prediction remains an imperfect science—science that is best used as an adjunct to discussion of comprehensive CVD risk factor modification with the individual patient.

CORRESPONDENCE
Jonathon M. Firnhaber, MD, Brody School of Medicine, East Carolina University, 101 Heart Drive, Greenville, NC 27834; firnhaberj@ecu.edu.

Non-statin interventions that upregulate LDL-receptor expression reduce the relative risk of vascular events to a similar extent as statins.

Over the past 3 decades, age-adjusted mortality for cardiovascular disease (CVD) in the United States has dropped by more than 50%.¹ While multiple factors have contributed to this remarkable decline, the introduction and widespread use of statin therapy is unquestionably one key factor. Despite nearly overwhelming evidence that statins effectively lower low-density lipoprotein cholesterol (LDL-C) and predictably reduce cardiovascular events, less than half of patients with clinical coronary heart disease receive high-intensity statin therapy, leaving this population at increased risk for future events.²

Statins: Latest evidence on risks and benefits

Statins aren’t perfect. Not every patient is able to achieve the desired LDL-C lowering with statin therapy, and some patients develop adverse effects such as myopathy, new-onset diabetes, and occasionally hemorrhagic stroke. A recent report puts the risks of statin therapy in perspective, estimating that the treatment of 10,000 patients for 5 years would cause one case of rhabdomyolysis, 5 cases of myopathy, 75 new cases of diabetes, and 7 hemorrhagic strokes.³ The same treatment would avert approximately 1000 CVD events among those with preexisting disease, and approximately 500 CVD events among those with elevated risk, but no preexisting disease.³

In blinded randomized controlled trials, statin therapy is associated with relatively few adverse events (AEs). In open-label observational studies, however, substantially more AEs are reported. During the blinded phase of one recent study, muscle-related AEs and erectile dysfunction were reported at a similar rate by participants randomly assigned to receive atorvastatin or placebo. During the nonblinded nonrandomized phase, complaints of muscle-related AEs were 41% more likely in participants taking statins compared with those who were not.⁴

Statin therapy offers predictable CVD risk reduction. The evidence report accompanying the 2016 US Preventive Services Task Force (USPSTF) guidelines on statins for the prevention of CVD states that the use of low- or moderate-dose statin therapy was associated with an approximately 30% relative risk reduction (RRR) in CVD events and in CVD deaths, and a 10% to 15% RRR in all-cause mortality.⁵ Those with greater baseline CVD risk will have greater absolute risk reduction (ARR) than those with low baseline risk.⁵

How effective are non-statin therapies?

Multiple studies have demonstrated that some drugs can favorably modify lipid levels but not improve patient outcomes—eg, niacin, fibrates, and omega-3 fatty acids. The therapies that do improve outcomes are those that act via upregulation of LDL-receptor expression: statins, ezetimibe, bile acid sequestrants, dietary interventions, and ileal bypass surgery.

A recent meta-analysis found that with a 38.7-mg/dL (1-mmol/L) reduction in LDL-C level, the relative risk for major vascular events was 0.77 (95% CI, 0.71-0.84) for statins and 0.75 (95% CI, 0.66-0.86) for monotherapy with non-statin interventions that upregulate LDL-receptor expression.⁶

Ezetimibe. Less impressive is the incremental benefit of adding some non-statin therapies to effective statin therapy. The IMProved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) reported that adding ezetimibe to effective statin therapy in stable patients with previous acute coronary syndrome reduced the LDL-C level from 69.5 mg/dL to 53.7 mg/dL (TABLE^7-13).⁸ After 7 years of treatment, relative risk of atherosclerotic cardiovascular disease (ASCVD) outcomes decreased by 5.8%; absolute decrease in risk was 2%: from 34.7% to 32.7% (number needed to treat [NNT]=50).⁸ Consider adding ezetimibe to maximally-tolerated statin therapy for patients not meeting LDL-C goals with a statin alone.

Continue to: A new class to lower LDL-C: PCSK9 inhibitors

A new class to lower LDL-C: PCSK9 inhibitors

It is clear that additional approaches to LDL-C reduction are needed. A new drug class that effectively lowers LDL-C levels is monoclonal antibodies that inhibit PCSK9 (proprotein convertase subtilisin/kexin type 9). PCSK9 activity is directly proportional to the circulating LDL-C level: gene mutations that increase PCSK9 function are one cause of elevated LDL-C and CVD risk in familial hypercholesterolemia (FH),¹⁴ whereas mutations that decrease PCSK9 activity are associated with a decrease in LDL-C levels and risk of ASCVD.¹⁵

Circulating PCSK9 initiates LDL-receptor clearance by binding to the LDL receptor; the complex is then taken into the hepatocyte, where it undergoes degradation, and the receptor is not recycled to the cell’s surface. The resultant decreased level of cholesterol within the hepatocyte upregulates HMG-CoA reductase (the enzyme that controls the rate-limiting step in cholesterol production and is targeted by statin therapy) and LDL-receptor activity to increase the available cholesterol in the hepatocyte. Unfortunately, statins promote the upregulation of both the LDL receptor and PCSK9, thereby limiting their LDL-C-lowering potency. Combined inhibition of HMG-CoA reductase with statins and PCSK9 with monoclonal antibodies exerts additive reductions in LDL-C.¹⁶

Evolocumab and alirocumab—monoclonal antibodies that prevent circulating PCSK9 from binding to the LDL receptor—have been approved by the US Food and Drug Administration (FDA) for use as adjuncts to diet and maximally-tolerated statin therapy in adults who have heterozygous familial hypercholesterolemia (HeFH) or clinical ASCVD and who must further lower LDL-C levels. The addition of a PCSK9 inhibitor to statin therapy consistently results in an incremental decrease in LDL-C of around 60%.^10,11 Much of the data supporting the use of PCSK9 inhibitors are disease-oriented. Among patients with angiographic coronary disease treated with statins, the addition of evolocumab resulted in regression of atherosclerotic plaque measured by intravascular ultrasound after 18 months of treatment.¹⁰

Continue to: PCSK9 inhibitors reduce adverse CVD events when added to a statin

PCSK9 inhibitors reduce adverse CVD events when added to a statin. In a study designed to evaluate AEs and LDL-C lowering with evolocumab, a prespecified exploratory outcome was the incidence of adjudicated CVD events. After one year of therapy, the rate of events was reduced from 2.18% in the standard-therapy group to 0.95% in the evolocumab group—a relative decrease of 53%, but an absolute decrease of 1.23% (NNT=81).¹⁷

A similar reduction in the rate of major adverse CVD events was found in adding alirocumab to ongoing statin therapy. In a post hoc analysis of patients who received either adjunctive alirocumab or placebo, CVD events (death from coronary heart disease, nonfatal myocardial infarction [MI], fatal or nonfatal ischemic stroke, or unstable angina requiring hospitalization) were 1.7% vs 3.3% (hazard ratio=0.52; 95% confidence interval, 0.31-0.90).¹¹

FOURIER, the first major trial designed to evaluate cardiovascular outcomes with PCSK9 therapy, showed that adding evolocumab to effective statin therapy reduced the average LDL-C level from 92 mg/dL to 30 mg/dL.¹² Evolocumab decreased the composite CVD outcome (cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization) over 2.2 years from 11.3% to 9.8%—a 15% RRR and a 1.5% ARR (NNT=67). Most of the participants were receiving high-intensity statin therapy at study entry. AEs were similar between the study groups.¹²

A prespecified analysis of FOURIER data found that evolocumab did not increase the risk of new-onset diabetes in patients without diabetes or prediabetes at baseline. Fasting plasma glucose and hemoglobin A1c levels in the evolocumab and placebo groups remained similar throughout the trial in patients with diabetes, prediabetes, or normoglycemia.¹⁸ Additionally, a randomized trial involving patients who received either evolocumab or placebo in addition to statin therapy found no significant difference in cognitive function between the groups over a median of 19 months.¹⁹

Continue to: Effective, but expensive

Effective, but expensive. At its current list price of approximately $14,000 per year,⁹ evolocumab, added to standard therapy in patients with ASCVD, exceeds the generally accepted cost-effectiveness threshold of $150,000 per quality-adjusted life year (QALY) achieved.²⁰ Similar analysis in patients with HeFH estimated a cost of $503,000 per QALY achieved with evolocumab.²¹ The outcomes of cost-effectiveness analyses hinge on the event rate in the study population and the threshold for initiating therapy. For the FOURIER trial participants, with an annual event rate of 4.2 per 100 patient-years, a net annual price of approximately $6700 would be necessary to meet a $150,000 per QALY threshold.²²

At 2015 prices, the addition of PCSK9 inhibitor therapy for all eligible patients would reduce cardiovascular care costs by an estimated $29 billion over 5 years but would also increase drug costs by an estimated $592 billion, representing a 38% increase over 2015 prescription drug expenditures.²¹ Treatment of less than 20 million US adults with evolocumab at the cost of this single drug would match the entire cost for all other prescription pharmaceuticals for all diseases in the United States combined.²³

In 2012, 27.9% of US adults ages 40 years and older were taking prescribed lipid-lowering treatment; 23.2% were taking only statins.²⁴ If the 2013 American College of Cardiology/American Heart Association cholesterol treatment guidelines²⁵ were fully implemented, an estimated additional 24.3% of the US population would be treated with statins.²⁶ Full implementation of the more conservative USPSTF guidelines would result in an additional 15.8% of the US population initiating statin therapy.²⁶ The same cost-effectiveness analysis evaluating evolocumab use estimated that initiating statins in these high-risk populations not currently using statins would save $12 billion in cardiovascular care over 5 years.²¹

Adding a PCSK9 inhibitor to statin therapy consistently decreases LDL-C levels further by around 60%.

Until the cost of PCSK9 inhibitors decreases to a justifiable level and outcomes of longer term studies are available, consider prescribing other adjunctive treatments for patients who have not achieved LDL-C goals with statin therapy alone. Generally, reserve use of PCSK9 inhibitors for the highest-risk adults: those with HeFH or clinical ASCVD who must further lower LDL-C levels. Some insurers, including Medicare, are covering PCSK9 inhibitors, but many patients have difficulty obtaining coverage.²⁷

Continue to: CETP inhibitors: Not FDA approved

CETP inhibitors: Not FDA approved

In a recent trial of the cholesteryl ester transfer protein (CETP) inhibitor evacetrapib, the drug had favorable effects on lipid biomarkers but did not improve cardiovascular outcomes.²⁸ More recently, the CETP inhibitor anacetrapib was shown to decrease the composite outcome of coronary death, MI, or coronary revascularization in adults with established ASCVD who were receiving high-intensity atorvastatin therapy.¹³ At the trial midpoint, mean high-density lipoprotein (HDL) cholesterol levels increased by 43 mg/dL in the anacetrapib group compared with that of the placebo group (a relative difference of 104%); mean non-HDL cholesterol decreased by 17 mg/dL, a relative difference of −18%. Over a median follow-up period of 4.1 years, the addition of anacetrapib was associated with a 9% RRR and a 1% absolute reduction in the composite outcome over a statin alone (NNT=100).¹³ At this point, the manufacturers of both agents have halted efforts to gain FDA approval.

Future directions

Newer strategies to inhibit PCSK9 function are under development. Small peptides that inhibit PCSK9 interaction with the LDL receptor offer the potential advantage of oral administration, as opposed to the currently available injectable anti-PCSK9 antibodies.²⁹ A recent trial found that inhibition of PCSK9 messenger RNA (mRNA) synthesis with the small interfering RNA (siRNA) molecule inclisiran lowered LDL-C in patients with high cardiovascular risk and elevated LDL-C levels despite aggressive statin therapy.³⁰ The effect of these strategies on cardiovascular outcomes remains unproven.

CORRESPONDENCE
Jonathon Firnhaber, MD, Department of Family Medicine, Brody School of Medicine, 101 Heart Drive, Mail Stop 654, Greenville, NC 27834; firnhaberj@ecu.edu.

Non-statin interventions that upregulate LDL-receptor expression reduce the relative risk of vascular events to a similar extent as statins.

Over the past 3 decades, age-adjusted mortality for cardiovascular disease (CVD) in the United States has dropped by more than 50%.¹ While multiple factors have contributed to this remarkable decline, the introduction and widespread use of statin therapy is unquestionably one key factor. Despite nearly overwhelming evidence that statins effectively lower low-density lipoprotein cholesterol (LDL-C) and predictably reduce cardiovascular events, less than half of patients with clinical coronary heart disease receive high-intensity statin therapy, leaving this population at increased risk for future events.²

Statins: Latest evidence on risks and benefits

Statins aren’t perfect. Not every patient is able to achieve the desired LDL-C lowering with statin therapy, and some patients develop adverse effects such as myopathy, new-onset diabetes, and occasionally hemorrhagic stroke. A recent report puts the risks of statin therapy in perspective, estimating that the treatment of 10,000 patients for 5 years would cause one case of rhabdomyolysis, 5 cases of myopathy, 75 new cases of diabetes, and 7 hemorrhagic strokes.³ The same treatment would avert approximately 1000 CVD events among those with preexisting disease, and approximately 500 CVD events among those with elevated risk, but no preexisting disease.³

In blinded randomized controlled trials, statin therapy is associated with relatively few adverse events (AEs). In open-label observational studies, however, substantially more AEs are reported. During the blinded phase of one recent study, muscle-related AEs and erectile dysfunction were reported at a similar rate by participants randomly assigned to receive atorvastatin or placebo. During the nonblinded nonrandomized phase, complaints of muscle-related AEs were 41% more likely in participants taking statins compared with those who were not.⁴

Statin therapy offers predictable CVD risk reduction. The evidence report accompanying the 2016 US Preventive Services Task Force (USPSTF) guidelines on statins for the prevention of CVD states that the use of low- or moderate-dose statin therapy was associated with an approximately 30% relative risk reduction (RRR) in CVD events and in CVD deaths, and a 10% to 15% RRR in all-cause mortality.⁵ Those with greater baseline CVD risk will have greater absolute risk reduction (ARR) than those with low baseline risk.⁵

How effective are non-statin therapies?

Multiple studies have demonstrated that some drugs can favorably modify lipid levels but not improve patient outcomes—eg, niacin, fibrates, and omega-3 fatty acids. The therapies that do improve outcomes are those that act via upregulation of LDL-receptor expression: statins, ezetimibe, bile acid sequestrants, dietary interventions, and ileal bypass surgery.

A recent meta-analysis found that with a 38.7-mg/dL (1-mmol/L) reduction in LDL-C level, the relative risk for major vascular events was 0.77 (95% CI, 0.71-0.84) for statins and 0.75 (95% CI, 0.66-0.86) for monotherapy with non-statin interventions that upregulate LDL-receptor expression.⁶

Ezetimibe. Less impressive is the incremental benefit of adding some non-statin therapies to effective statin therapy. The IMProved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) reported that adding ezetimibe to effective statin therapy in stable patients with previous acute coronary syndrome reduced the LDL-C level from 69.5 mg/dL to 53.7 mg/dL (TABLE^7-13).⁸ After 7 years of treatment, relative risk of atherosclerotic cardiovascular disease (ASCVD) outcomes decreased by 5.8%; absolute decrease in risk was 2%: from 34.7% to 32.7% (number needed to treat [NNT]=50).⁸ Consider adding ezetimibe to maximally-tolerated statin therapy for patients not meeting LDL-C goals with a statin alone.

Continue to: A new class to lower LDL-C: PCSK9 inhibitors

A new class to lower LDL-C: PCSK9 inhibitors

It is clear that additional approaches to LDL-C reduction are needed. A new drug class that effectively lowers LDL-C levels is monoclonal antibodies that inhibit PCSK9 (proprotein convertase subtilisin/kexin type 9). PCSK9 activity is directly proportional to the circulating LDL-C level: gene mutations that increase PCSK9 function are one cause of elevated LDL-C and CVD risk in familial hypercholesterolemia (FH),¹⁴ whereas mutations that decrease PCSK9 activity are associated with a decrease in LDL-C levels and risk of ASCVD.¹⁵

Circulating PCSK9 initiates LDL-receptor clearance by binding to the LDL receptor; the complex is then taken into the hepatocyte, where it undergoes degradation, and the receptor is not recycled to the cell’s surface. The resultant decreased level of cholesterol within the hepatocyte upregulates HMG-CoA reductase (the enzyme that controls the rate-limiting step in cholesterol production and is targeted by statin therapy) and LDL-receptor activity to increase the available cholesterol in the hepatocyte. Unfortunately, statins promote the upregulation of both the LDL receptor and PCSK9, thereby limiting their LDL-C-lowering potency. Combined inhibition of HMG-CoA reductase with statins and PCSK9 with monoclonal antibodies exerts additive reductions in LDL-C.¹⁶

Evolocumab and alirocumab—monoclonal antibodies that prevent circulating PCSK9 from binding to the LDL receptor—have been approved by the US Food and Drug Administration (FDA) for use as adjuncts to diet and maximally-tolerated statin therapy in adults who have heterozygous familial hypercholesterolemia (HeFH) or clinical ASCVD and who must further lower LDL-C levels. The addition of a PCSK9 inhibitor to statin therapy consistently results in an incremental decrease in LDL-C of around 60%.^10,11 Much of the data supporting the use of PCSK9 inhibitors are disease-oriented. Among patients with angiographic coronary disease treated with statins, the addition of evolocumab resulted in regression of atherosclerotic plaque measured by intravascular ultrasound after 18 months of treatment.¹⁰

Continue to: PCSK9 inhibitors reduce adverse CVD events when added to a statin

PCSK9 inhibitors reduce adverse CVD events when added to a statin. In a study designed to evaluate AEs and LDL-C lowering with evolocumab, a prespecified exploratory outcome was the incidence of adjudicated CVD events. After one year of therapy, the rate of events was reduced from 2.18% in the standard-therapy group to 0.95% in the evolocumab group—a relative decrease of 53%, but an absolute decrease of 1.23% (NNT=81).¹⁷

A similar reduction in the rate of major adverse CVD events was found in adding alirocumab to ongoing statin therapy. In a post hoc analysis of patients who received either adjunctive alirocumab or placebo, CVD events (death from coronary heart disease, nonfatal myocardial infarction [MI], fatal or nonfatal ischemic stroke, or unstable angina requiring hospitalization) were 1.7% vs 3.3% (hazard ratio=0.52; 95% confidence interval, 0.31-0.90).¹¹

FOURIER, the first major trial designed to evaluate cardiovascular outcomes with PCSK9 therapy, showed that adding evolocumab to effective statin therapy reduced the average LDL-C level from 92 mg/dL to 30 mg/dL.¹² Evolocumab decreased the composite CVD outcome (cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization) over 2.2 years from 11.3% to 9.8%—a 15% RRR and a 1.5% ARR (NNT=67). Most of the participants were receiving high-intensity statin therapy at study entry. AEs were similar between the study groups.¹²

A prespecified analysis of FOURIER data found that evolocumab did not increase the risk of new-onset diabetes in patients without diabetes or prediabetes at baseline. Fasting plasma glucose and hemoglobin A1c levels in the evolocumab and placebo groups remained similar throughout the trial in patients with diabetes, prediabetes, or normoglycemia.¹⁸ Additionally, a randomized trial involving patients who received either evolocumab or placebo in addition to statin therapy found no significant difference in cognitive function between the groups over a median of 19 months.¹⁹

Continue to: Effective, but expensive

Effective, but expensive. At its current list price of approximately $14,000 per year,⁹ evolocumab, added to standard therapy in patients with ASCVD, exceeds the generally accepted cost-effectiveness threshold of $150,000 per quality-adjusted life year (QALY) achieved.²⁰ Similar analysis in patients with HeFH estimated a cost of $503,000 per QALY achieved with evolocumab.²¹ The outcomes of cost-effectiveness analyses hinge on the event rate in the study population and the threshold for initiating therapy. For the FOURIER trial participants, with an annual event rate of 4.2 per 100 patient-years, a net annual price of approximately $6700 would be necessary to meet a $150,000 per QALY threshold.²²

At 2015 prices, the addition of PCSK9 inhibitor therapy for all eligible patients would reduce cardiovascular care costs by an estimated $29 billion over 5 years but would also increase drug costs by an estimated $592 billion, representing a 38% increase over 2015 prescription drug expenditures.²¹ Treatment of less than 20 million US adults with evolocumab at the cost of this single drug would match the entire cost for all other prescription pharmaceuticals for all diseases in the United States combined.²³

In 2012, 27.9% of US adults ages 40 years and older were taking prescribed lipid-lowering treatment; 23.2% were taking only statins.²⁴ If the 2013 American College of Cardiology/American Heart Association cholesterol treatment guidelines²⁵ were fully implemented, an estimated additional 24.3% of the US population would be treated with statins.²⁶ Full implementation of the more conservative USPSTF guidelines would result in an additional 15.8% of the US population initiating statin therapy.²⁶ The same cost-effectiveness analysis evaluating evolocumab use estimated that initiating statins in these high-risk populations not currently using statins would save $12 billion in cardiovascular care over 5 years.²¹

Adding a PCSK9 inhibitor to statin therapy consistently decreases LDL-C levels further by around 60%.

Until the cost of PCSK9 inhibitors decreases to a justifiable level and outcomes of longer term studies are available, consider prescribing other adjunctive treatments for patients who have not achieved LDL-C goals with statin therapy alone. Generally, reserve use of PCSK9 inhibitors for the highest-risk adults: those with HeFH or clinical ASCVD who must further lower LDL-C levels. Some insurers, including Medicare, are covering PCSK9 inhibitors, but many patients have difficulty obtaining coverage.²⁷

Continue to: CETP inhibitors: Not FDA approved

CETP inhibitors: Not FDA approved

In a recent trial of the cholesteryl ester transfer protein (CETP) inhibitor evacetrapib, the drug had favorable effects on lipid biomarkers but did not improve cardiovascular outcomes.²⁸ More recently, the CETP inhibitor anacetrapib was shown to decrease the composite outcome of coronary death, MI, or coronary revascularization in adults with established ASCVD who were receiving high-intensity atorvastatin therapy.¹³ At the trial midpoint, mean high-density lipoprotein (HDL) cholesterol levels increased by 43 mg/dL in the anacetrapib group compared with that of the placebo group (a relative difference of 104%); mean non-HDL cholesterol decreased by 17 mg/dL, a relative difference of −18%. Over a median follow-up period of 4.1 years, the addition of anacetrapib was associated with a 9% RRR and a 1% absolute reduction in the composite outcome over a statin alone (NNT=100).¹³ At this point, the manufacturers of both agents have halted efforts to gain FDA approval.

Future directions

Newer strategies to inhibit PCSK9 function are under development. Small peptides that inhibit PCSK9 interaction with the LDL receptor offer the potential advantage of oral administration, as opposed to the currently available injectable anti-PCSK9 antibodies.²⁹ A recent trial found that inhibition of PCSK9 messenger RNA (mRNA) synthesis with the small interfering RNA (siRNA) molecule inclisiran lowered LDL-C in patients with high cardiovascular risk and elevated LDL-C levels despite aggressive statin therapy.³⁰ The effect of these strategies on cardiovascular outcomes remains unproven.

CORRESPONDENCE
Jonathon Firnhaber, MD, Department of Family Medicine, Brody School of Medicine, 101 Heart Drive, Mail Stop 654, Greenville, NC 27834; firnhaberj@ecu.edu.

Non-statin interventions that upregulate LDL-receptor expression reduce the relative risk of vascular events to a similar extent as statins.

Over the past 3 decades, age-adjusted mortality for cardiovascular disease (CVD) in the United States has dropped by more than 50%.¹ While multiple factors have contributed to this remarkable decline, the introduction and widespread use of statin therapy is unquestionably one key factor. Despite nearly overwhelming evidence that statins effectively lower low-density lipoprotein cholesterol (LDL-C) and predictably reduce cardiovascular events, less than half of patients with clinical coronary heart disease receive high-intensity statin therapy, leaving this population at increased risk for future events.²

Statins: Latest evidence on risks and benefits

Statins aren’t perfect. Not every patient is able to achieve the desired LDL-C lowering with statin therapy, and some patients develop adverse effects such as myopathy, new-onset diabetes, and occasionally hemorrhagic stroke. A recent report puts the risks of statin therapy in perspective, estimating that the treatment of 10,000 patients for 5 years would cause one case of rhabdomyolysis, 5 cases of myopathy, 75 new cases of diabetes, and 7 hemorrhagic strokes.³ The same treatment would avert approximately 1000 CVD events among those with preexisting disease, and approximately 500 CVD events among those with elevated risk, but no preexisting disease.³

In blinded randomized controlled trials, statin therapy is associated with relatively few adverse events (AEs). In open-label observational studies, however, substantially more AEs are reported. During the blinded phase of one recent study, muscle-related AEs and erectile dysfunction were reported at a similar rate by participants randomly assigned to receive atorvastatin or placebo. During the nonblinded nonrandomized phase, complaints of muscle-related AEs were 41% more likely in participants taking statins compared with those who were not.⁴

Statin therapy offers predictable CVD risk reduction. The evidence report accompanying the 2016 US Preventive Services Task Force (USPSTF) guidelines on statins for the prevention of CVD states that the use of low- or moderate-dose statin therapy was associated with an approximately 30% relative risk reduction (RRR) in CVD events and in CVD deaths, and a 10% to 15% RRR in all-cause mortality.⁵ Those with greater baseline CVD risk will have greater absolute risk reduction (ARR) than those with low baseline risk.⁵

How effective are non-statin therapies?

Multiple studies have demonstrated that some drugs can favorably modify lipid levels but not improve patient outcomes—eg, niacin, fibrates, and omega-3 fatty acids. The therapies that do improve outcomes are those that act via upregulation of LDL-receptor expression: statins, ezetimibe, bile acid sequestrants, dietary interventions, and ileal bypass surgery.

A recent meta-analysis found that with a 38.7-mg/dL (1-mmol/L) reduction in LDL-C level, the relative risk for major vascular events was 0.77 (95% CI, 0.71-0.84) for statins and 0.75 (95% CI, 0.66-0.86) for monotherapy with non-statin interventions that upregulate LDL-receptor expression.⁶

Ezetimibe. Less impressive is the incremental benefit of adding some non-statin therapies to effective statin therapy. The IMProved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) reported that adding ezetimibe to effective statin therapy in stable patients with previous acute coronary syndrome reduced the LDL-C level from 69.5 mg/dL to 53.7 mg/dL (TABLE^7-13).⁸ After 7 years of treatment, relative risk of atherosclerotic cardiovascular disease (ASCVD) outcomes decreased by 5.8%; absolute decrease in risk was 2%: from 34.7% to 32.7% (number needed to treat [NNT]=50).⁸ Consider adding ezetimibe to maximally-tolerated statin therapy for patients not meeting LDL-C goals with a statin alone.

Continue to: A new class to lower LDL-C: PCSK9 inhibitors

A new class to lower LDL-C: PCSK9 inhibitors

It is clear that additional approaches to LDL-C reduction are needed. A new drug class that effectively lowers LDL-C levels is monoclonal antibodies that inhibit PCSK9 (proprotein convertase subtilisin/kexin type 9). PCSK9 activity is directly proportional to the circulating LDL-C level: gene mutations that increase PCSK9 function are one cause of elevated LDL-C and CVD risk in familial hypercholesterolemia (FH),¹⁴ whereas mutations that decrease PCSK9 activity are associated with a decrease in LDL-C levels and risk of ASCVD.¹⁵

Circulating PCSK9 initiates LDL-receptor clearance by binding to the LDL receptor; the complex is then taken into the hepatocyte, where it undergoes degradation, and the receptor is not recycled to the cell’s surface. The resultant decreased level of cholesterol within the hepatocyte upregulates HMG-CoA reductase (the enzyme that controls the rate-limiting step in cholesterol production and is targeted by statin therapy) and LDL-receptor activity to increase the available cholesterol in the hepatocyte. Unfortunately, statins promote the upregulation of both the LDL receptor and PCSK9, thereby limiting their LDL-C-lowering potency. Combined inhibition of HMG-CoA reductase with statins and PCSK9 with monoclonal antibodies exerts additive reductions in LDL-C.¹⁶

Evolocumab and alirocumab—monoclonal antibodies that prevent circulating PCSK9 from binding to the LDL receptor—have been approved by the US Food and Drug Administration (FDA) for use as adjuncts to diet and maximally-tolerated statin therapy in adults who have heterozygous familial hypercholesterolemia (HeFH) or clinical ASCVD and who must further lower LDL-C levels. The addition of a PCSK9 inhibitor to statin therapy consistently results in an incremental decrease in LDL-C of around 60%.^10,11 Much of the data supporting the use of PCSK9 inhibitors are disease-oriented. Among patients with angiographic coronary disease treated with statins, the addition of evolocumab resulted in regression of atherosclerotic plaque measured by intravascular ultrasound after 18 months of treatment.¹⁰

Continue to: PCSK9 inhibitors reduce adverse CVD events when added to a statin

PCSK9 inhibitors reduce adverse CVD events when added to a statin. In a study designed to evaluate AEs and LDL-C lowering with evolocumab, a prespecified exploratory outcome was the incidence of adjudicated CVD events. After one year of therapy, the rate of events was reduced from 2.18% in the standard-therapy group to 0.95% in the evolocumab group—a relative decrease of 53%, but an absolute decrease of 1.23% (NNT=81).¹⁷

A similar reduction in the rate of major adverse CVD events was found in adding alirocumab to ongoing statin therapy. In a post hoc analysis of patients who received either adjunctive alirocumab or placebo, CVD events (death from coronary heart disease, nonfatal myocardial infarction [MI], fatal or nonfatal ischemic stroke, or unstable angina requiring hospitalization) were 1.7% vs 3.3% (hazard ratio=0.52; 95% confidence interval, 0.31-0.90).¹¹

FOURIER, the first major trial designed to evaluate cardiovascular outcomes with PCSK9 therapy, showed that adding evolocumab to effective statin therapy reduced the average LDL-C level from 92 mg/dL to 30 mg/dL.¹² Evolocumab decreased the composite CVD outcome (cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization) over 2.2 years from 11.3% to 9.8%—a 15% RRR and a 1.5% ARR (NNT=67). Most of the participants were receiving high-intensity statin therapy at study entry. AEs were similar between the study groups.¹²

A prespecified analysis of FOURIER data found that evolocumab did not increase the risk of new-onset diabetes in patients without diabetes or prediabetes at baseline. Fasting plasma glucose and hemoglobin A1c levels in the evolocumab and placebo groups remained similar throughout the trial in patients with diabetes, prediabetes, or normoglycemia.¹⁸ Additionally, a randomized trial involving patients who received either evolocumab or placebo in addition to statin therapy found no significant difference in cognitive function between the groups over a median of 19 months.¹⁹

Continue to: Effective, but expensive

Effective, but expensive. At its current list price of approximately $14,000 per year,⁹ evolocumab, added to standard therapy in patients with ASCVD, exceeds the generally accepted cost-effectiveness threshold of $150,000 per quality-adjusted life year (QALY) achieved.²⁰ Similar analysis in patients with HeFH estimated a cost of $503,000 per QALY achieved with evolocumab.²¹ The outcomes of cost-effectiveness analyses hinge on the event rate in the study population and the threshold for initiating therapy. For the FOURIER trial participants, with an annual event rate of 4.2 per 100 patient-years, a net annual price of approximately $6700 would be necessary to meet a $150,000 per QALY threshold.²²

At 2015 prices, the addition of PCSK9 inhibitor therapy for all eligible patients would reduce cardiovascular care costs by an estimated $29 billion over 5 years but would also increase drug costs by an estimated $592 billion, representing a 38% increase over 2015 prescription drug expenditures.²¹ Treatment of less than 20 million US adults with evolocumab at the cost of this single drug would match the entire cost for all other prescription pharmaceuticals for all diseases in the United States combined.²³

In 2012, 27.9% of US adults ages 40 years and older were taking prescribed lipid-lowering treatment; 23.2% were taking only statins.²⁴ If the 2013 American College of Cardiology/American Heart Association cholesterol treatment guidelines²⁵ were fully implemented, an estimated additional 24.3% of the US population would be treated with statins.²⁶ Full implementation of the more conservative USPSTF guidelines would result in an additional 15.8% of the US population initiating statin therapy.²⁶ The same cost-effectiveness analysis evaluating evolocumab use estimated that initiating statins in these high-risk populations not currently using statins would save $12 billion in cardiovascular care over 5 years.²¹

Adding a PCSK9 inhibitor to statin therapy consistently decreases LDL-C levels further by around 60%.

Until the cost of PCSK9 inhibitors decreases to a justifiable level and outcomes of longer term studies are available, consider prescribing other adjunctive treatments for patients who have not achieved LDL-C goals with statin therapy alone. Generally, reserve use of PCSK9 inhibitors for the highest-risk adults: those with HeFH or clinical ASCVD who must further lower LDL-C levels. Some insurers, including Medicare, are covering PCSK9 inhibitors, but many patients have difficulty obtaining coverage.²⁷

Continue to: CETP inhibitors: Not FDA approved

CETP inhibitors: Not FDA approved

In a recent trial of the cholesteryl ester transfer protein (CETP) inhibitor evacetrapib, the drug had favorable effects on lipid biomarkers but did not improve cardiovascular outcomes.²⁸ More recently, the CETP inhibitor anacetrapib was shown to decrease the composite outcome of coronary death, MI, or coronary revascularization in adults with established ASCVD who were receiving high-intensity atorvastatin therapy.¹³ At the trial midpoint, mean high-density lipoprotein (HDL) cholesterol levels increased by 43 mg/dL in the anacetrapib group compared with that of the placebo group (a relative difference of 104%); mean non-HDL cholesterol decreased by 17 mg/dL, a relative difference of −18%. Over a median follow-up period of 4.1 years, the addition of anacetrapib was associated with a 9% RRR and a 1% absolute reduction in the composite outcome over a statin alone (NNT=100).¹³ At this point, the manufacturers of both agents have halted efforts to gain FDA approval.

Future directions

Newer strategies to inhibit PCSK9 function are under development. Small peptides that inhibit PCSK9 interaction with the LDL receptor offer the potential advantage of oral administration, as opposed to the currently available injectable anti-PCSK9 antibodies.²⁹ A recent trial found that inhibition of PCSK9 messenger RNA (mRNA) synthesis with the small interfering RNA (siRNA) molecule inclisiran lowered LDL-C in patients with high cardiovascular risk and elevated LDL-C levels despite aggressive statin therapy.³⁰ The effect of these strategies on cardiovascular outcomes remains unproven.

CORRESPONDENCE
Jonathon Firnhaber, MD, Department of Family Medicine, Brody School of Medicine, 101 Heart Drive, Mail Stop 654, Greenville, NC 27834; firnhaberj@ecu.edu.