Medical Policy: 02.04.04 

Original Effective Date: September 2002 

Reviewed: April 2018 

Revised: April 2018 

 

Benefit Application:

Benefit determinations are based on the applicable contract language in effect at the time the services were rendered. Exclusions, limitations or exceptions may apply. Benefits may vary based on contract, and individual member benefits must be verified. Wellmark determines medical necessity only if the benefit exists and no contract exclusions are applicable. This medical policy may not apply to FEP. Benefits are determined by the Federal Employee Program.

 

This Medical Policy document describes the status of medical technology at the time the document was developed. Since that time, new technology may have emerged or new medical literature may have been published. This Medical Policy will be reviewed regularly and be updated as scientific and medical literature becomes available.

 

Description:

Cardiovascular disease (CVD) remains the single largest cause of morbidity and mortality in the developed world. As a result, accurate prediction of CVD risk is a component of medical care that has the potential to focus and direct preventative and diagnostic activities. Current methods of risk prediction in use in general clinical care are not highly accurate and, as a result, there is a potential unmet need for improved risk prediction instruments.

 

Components of cardiovascular disease (CVD) risk include family history, cigarette smoking, hypertension, and lifestyle factors such as diet and exercise. Also, numerous laboratory tests have been associated with CVD risk, most prominently lipids such as low-density lipoprotein (LDL) and high density lipoprotein (HDL). These clinical and lipid factors are often combined into simple risk prediction instruments, such as Framingham Risk Score. The Framingham Risk Score provides an estimate of the 10 year risk for developing cardiac disease and is currently used in clinical care to determine the aggressiveness of risk factor intervention, such as the decision to treat hyperlipidemia with statins.

 

Many additional biomarkers, genetic factors and radiologic measures have been associated with increased risk of CVD. Over 100 emerging risk factors have been proposed as useful for refining estimates of CVD risk. Some general categories of these potential risk factors are as follows:

 

  • Lipid markers: In addition to LDL and HDL, other lipid markers that may have predictive ability, including apolipoproteins, lipoprotein (a) (Lp[a]), lipid subfractions, and/or other measures.
  • Inflammatory markers: Many measures of inflammation have been linked to the likelihood of CVD. High-sensitivity C-reactive protein (hs-CRP) is an example of an inflammatory markers; others include fibrinogen, interleukins, and tumor necrosis factor.
  • Metabolic syndrome biomarkers: Measures associated with metabolic syndrome, such as specific dyslipidemic profiles of serum insulin levels, have been associated with increased risk of CVD.
  • Genetic Markers (genomic profiling): A number of variants associated with increased thrombosis risk, such as the MTHFR variant of the prothrombin gene variants, have been associated with increased CVD risk. Also, numerous single nucleotide variants have been associated with CVD in large genome-wide studies.

 

There is a large amount of literature on the association of individual risk factors with cardiovascular disease (CVD). Most of this literature evaluates correlations between individual biomarkers and the presence of, or future development of, CVD. A framework for the evaluation of the clinical utility of risk factor assessment includes the following steps:

  1. Standardization of the measurement of the risk factor.
  2. Determination of its contribution to risk assessment. As a risk factor, it is important to determine whether the novel risk factor independently contributes to risk assessment compared with established risk factors. Also, because there are many potential novel risk factors that could be incorporated into existing CVD risk panels, it is important to understand the relation between each risk factor and other risk factors.
  3. Determination of how the novel risk assessment will be used in the management of the patient, compared with standard methods of assessing risk, and whether any subsequent changes in patient management result in an improvement in patient outcome.

 

Helfand et. al. (2009) have suggested a similar framework for evaluating the utility of risk factors that includes the concept of reclassifying patients into clinically relevant risk factors. These suggested criteria are as follows:

  • Risk factor should be easily and reliably measured.
  • Risk factor should be an independent predictor of major cardiovascular events in patients with an intermediate risk of CVD and no history of CVD.
  • Risk factor should reclassify a substantial portion of intermediate risk patients as high-risk.
  • Reclassified individuals should be managed differently than they otherwise would have been.
  • If other risk factors provide similar prognostic information, then convenience, availability, cost, and safety should be considered in choosing among them.

 

Novel Biomarkers in Risk Assessment and Management of Cardiovascular Disease

Numerous lipid and non-lipid biomarkers have been proposed as potential risk markers for cardiovascular disease (CVD). Biomarkers assessed herein are those that have the most evidence in support of their use in clinical care, including apolipoprotein B (apo B), apolipoprotein AI (apo AI), apolipoprotein E (apo E), high-density lipoprotein (HDL) subclass, low-density lipoprotein (LDL) subclass, lipoprotein (a), B-type natriuretic peptide, cystatin C, fibrinogen, and leptin. These biomarkers have been studied as alternatives or additions to standard lipid panels for risk stratification in CVD or as treatment targets for lipid lowering therapy.

 

Low Density Lipoproteins and Cardiovascular Disease

Low-density lipoproteins (LDLs) have been identified as the major atherogenic lipoproteins and have long been identified by the National Cholesterol Education Project as the primary target of cholesterol-lowering therapy. LDL particles consist of a surface coat composed of phospholipids, free cholesterol, and apolipoproteins surrounding an inner lipid core composed of cholesterol ester and triglycerides. Traditional lipid risk factors such as LDL cholesterol (LDL-C), while predictive on a population basis, are weaker markers of risk on an individual basis. Only a minority of subjects with elevated LDL and cholesterol levels will develop clinical disease, and up to 50% of cases of coronary artery disease (CAD) occur in subjects with ”normal” levels of total and LDL-C. Thus, there is considerable potential to improve the accuracy of current cardiovascular risk prediction models.

 

Other non-lipid markers have been identified as being associated with cardiovascular disease (CVD), including B-type natriuretic peptide, cystatin C, fibrinogen, and leptin. These biomarkers may have a predictive role in identifying CVD risk or in targeting for therapy.

 

A large body of literature has accumulated on the utility of novel lipid risk factors in the prediction of future cardiac events. The evidence reviewed herein consists of systematic reviews, meta-analyses, and large, prospective cohort studies that have evaluated the association between these lipid markers and cardiovascular outcomes. A smaller amount of literature is available on the utility of these markers as a marker of treatment response. Data on treatment response are taken from RCTs that use one or more novel lipid markers as a target of lipid-lowering therapy.

 

The Adult Treatment Panel III (ATP III) guidelines noted that, to determine their clinical significance, emerging risk factors should be evaluated against the following criteria:

  • Significant predictive power that is independent of other major risk factors
  • A relatively high prevalence in the population (justifying routine measurement in risk assessment)
  • Laboratory or clinical measurement must be widely available, well standardized, inexpensive, have accepted population reference values, and be relatively stable biologically
  • Preferable, but not necessarily, modification of the risk factor in clinical trials will have shown reduction in risk.

 

A 2002 BlueCross and BlueShield Association TEC Assessment summarized the steps necessary to determine the utility of a novel cardiac risk factor. Three steps were required:

  • Standardization of the measurement of the risk factor.
  • Determination of its contribution to risk assessment. As a risk factor, it is important to determine whether the novel risk factor independently contributes to risk assessment compared with established risk factors.
  • Determination of how the novel risk assessment will be used in the management of the patient, compared with standard methods of assessing risk, and whether any subsequent changes in patient management result in an improvement in patient outcome.

 

Lipid Markers

Apolipoprotein B (apo B)

Apolipoprotein B (apo B) is the major protein moiety of all lipoproteins, except for high density lipoprotein (HDL). The most abundant form of apo B, large B or B, constitutes the apo B found in LDL and very low density lipoproteins (VLDL). LDL and VLDL each contain 1 molecule of apo B, measurement of apo B reflects the total number of these atherogenic particles, 90% of which are LDL. LDL particles can vary in size and in cholesterol content, for a given concentration of LDL-C, there can be a wide variety in size and numbers of LDL particles. Therefore, apo B concentration is an indirect measurement of the number of LDL particles and it has been suggested that apo B is a better measure of the atherogenic potential of serum LDL than LDL concentration.

 

The evidence has suggested that apo B provides independent information on risk assessment for CVD and that apo B may be superior to LDL-C in predicting cardiovascular risk. Numerous large prospective cohort studies and nested case-control studies have compared these measures, and most have concluded that apo B is a better predictor of cardiac risk than LDL-C. However, some meta-analyses have concluded that apo B is not a better predictor of cardiac risk than HDL or non-HDL combined with LDL. There is also greater uncertainty about the degree of improvement in risk prediction and whether the magnitude of improvement is clinically significant. While there have been attempts to incorporate apo B into multivariate risk prediction models, at present, apo B is not included in the models most commonly used in routine clinical care, such as the Framingham risk model and the Prospective Cardiovascular Munster Study Score.

 

As a marker of response to cholesterol-lowering treatment, apo B may be more accurate than LDL-C and may provide a better measure of the adequacy of antilipid therapy than LDL-C. Post hoc analyses of RCTs of statin treatment have reported that on-treatment levels of apo B are more highly correlated with clinical outcomes than standard lipid measures. Whether the degree of improvement in assessing treatment response is clinically significant has yet to be determined.

 

Currently, it is not possible to conclude that the use of apo B levels will improve outcomes in routine clinical care. Improved ability to predict risk and/or treatment response does not by itself result in better health outcomes. To improve outcomes, clinicians must have the tools to translate this information into clinical practice. No studies have demonstrated improved health outcomes by using apo B in place of LDL-C for risk assessment and/or treatment response. The most widely used risk assessment models (eg, the Framingham prediction model) and the most widely used treatment guidelines (eg, the ATP III guidelines) do not provide the tools necessary for clinicians to incorporate apo B measurements into routine assessment and management of hyperlipidemic patients. This lack creates difficulties in interpreting and applying the results of apo B and/or apo B/apo AI measurements to routine clinical care.

 

Apolipoprotein A-I

HDL contains 2 associated apolipoproteins (i.e. AI, AII). HDL particles can also be classified by whether they contain apo AI only or whether they contain apo AI and apo AII. All lipoproteins contain apo AI, and some also contain apo AII. Because all HDL particles contain apo AI, this lipid marker can be used as an approximation for HDL number, similar to the way apo B has been proposed as an approximation of the LDL number.

 

Direct measurement of apo AI has been proposed as more accurate than the traditional use of HDL level in the evaluation of the cardioprotective, or “good” cholesterol. In addition the ration of apo B/apo AI has been proposed as a superior measure of the ratio of proatherogenic (i.e.“bad”) cholesteroal to anti-atherogenic (i.e “good”) cholesterol.

 

The current evidence has generally indicated that measurement of apo AI and the apo B/apo AI ratio are as good as or better than currently used lipid measures such as LDL and HDL. Some experts have argued that the apo B/apo AI ratio is superior to the LDL/HDL ratio as a predictor of cardiovascular risk and should supplement or replace traditional lipid measures as both a risk marker and a treatment target. However, there is substantial uncertainty regarding the degree of improvement that these measures provide. The evidence suggests that any incremental improvement in predictive ability over traditional measures is likely to be small and of uncertain clinical significance.

 

The use of apo AI and the apo B/apo AI ratio as a target of treatment response to statins may also be as good as or better than the traditional measure of LDL. However, to improve outcomes, clinicians must have the tools to translate this information into clinical practice. Such tools for linking apo AI to clinical decision making, both in risk assessment and treatment response, are currently not available. Apo AI has not been incorporated into quantitative risk assessment models or treatment guidelines that can be used in clinical practice (eg, the ATP III).1 The ATP III practice guidelines continue to tie clinical decision making to conventional lipid measures, such as TC, LDL-C, and HDL-C. Therefore, it is not yet possible to conclude that these measures improve outcomes or that they should be adopted in routine clinical care. There is continued interest in developing new therapeutic agents that raise HDL, and apo AI mimetics are currently in development for this purpose.

 

Apolipoprotein E

Apolipoprotein E (apo E) is the primary apolipoprotein found in VLDLs and chylomicrons. Apo E is the primary binding protein for LDL receptors in the liver and is thought to play an important role in lipid metabolism. The apolipoprotein E (APOE) gene is polymorphic, consisting of 3 epsilon alleles (e2, e3, e4) that code for 3 protein isoforms, known as E2, E3, E4, which differ from one another by 1 amino acid. These molecules mediate lipid metabolism through their different interactions with LDL receptors. The genotype of apo E alleles can be assessed by gene amplification techniques, or the APOE phenotype can be assessed by measuring plasma levels of apo E.

 

It has been proposed that various APOE genotypes are more atherogenic than others, and that APOE measurement may provide information on risk of CAD above traditional risk factor measurement. It has also been proposed that the APOE genotype may be useful in the selection of specific components of lipid-lowering therapy, such as drug selection. In the major lipid-lowering intervention trials, including trials of statin therapy, there is considerable variability in response to therapy that cannot be explained by factors such as compliance. APOE genotype may be a factor that determines an individual’s degree of response to interventions such as statin therapy.

 

The evidence have suggested that APOE genotype may be associated with lipid levels and CAD but is probably not useful in providing additional clinically relevant information beyond established risk factors. Apo E is considered a relatively poor predictor of CAD, especially compared with other established and emerging clinical variables, and does not explain a large percentage of the interindividual variation in TC and LDL levels. Moreover, apo E has not been incorporated into standardized cardiac risk assessment models and was not identified as an important “emerging risk factor” in the most recent ATP III recommendations.

 

The evidence on response to treatment indicates that APOE genotype may be a predictor of response to statins and may allow clinicians to better gage a patient’s chance of successful treatment, although not all studies have consistently reported this relation. At present, it is unclear how this type of information would change clinical management. Dietary modifications are a universal recommendation for those with elevated cholesterol or LDL levels, and statin drugs are the overwhelmingly preferred agents for lipid-lowering therapy. It is unlikely that a clinician would choose alternative therapies, even in the presence of an APOE phenotype that indicates diminished response.

 

None of the available evidence has provided adequate data to establish that APOE genotype or phenotype improves outcomes when used in clinical care.

 

LDL Subclasses (Small and Large Particles)

LDL particles are not uniform in size or density, and two main subclass patterns of LDL, called A and B, have been described. In subclass pattern A, particles have a diameter larger than 25 nm and are less dense, while in subclass pattern B, particles have a diameter less than 25 nm and a higher density. Subclass pattern B is a commonly inherited disorder associated with a more atherogenic lipoprotein profile, also termed “atherogenic dyslipidemia.” In addition to small, dense LDL, this pattern includes elevated levels of triglycerides, elevated levels of apo B, and low levels of HDL. This lipid profile is commonly seen in type 2 diabetes and is a component of the “metabolic syndrome,” defined by the Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III [ATP III]) to also include high normal blood pressure, insulin resistance, increased levels of inflammatory markers such as C-reactive protein, and a prothrombotic state. Presence of the metabolic syndrome is considered by ATP III to be a substantial risk-enhancing factor for CAD.

 

LDL size has also been proposed as a potentially useful measure of treatment response. Lipid-lowering treatment decreases total LDL and may also include a shift in the type of LDL, from smaller, dense particles to larger particles. It has been proposed that this shift in lipid profile may be beneficial in reducing risk for CAD independent of the total LDL level. Also, some drugs may cause a greater shift in lipid profile than others. Therefore, measurement of LDL size may potentially play a role in drug selection or may be useful in deciding whether to use a combination of drugs rather than a statin alone.

 

In addition to the size of LDL particles, interest has been shown in assessing the concentration of LDL particles as a distinct cardiac risk factor. For example, the commonly performed test for LDL-C is not a direct measure of LDL, but, chosen for its convenience, measures the amount of cholesterol incorporated into LDL particles. Because LDL particles carry much of the cholesterol in the bloodstream, the concentration of cholesterol in LDL correlates reasonably well with the number of LDL particles when examined in large populations. However, for an individual patient, the LDL-C level may not reflect the number of particles due to varying levels of cholesterol in different sized particles. It is proposed that the discrepancy between the number of LDL particles and the serum level of LDL-C represents a significant source of unrecognized atherogenic risk. The size and number of particles are interrelated. For example, all LDL particles can invade the arterial wall and initiate atherosclerosis. However, small dense particles are thought to be more atherogenic than larger particles. Therefore, for patients with elevated numbers of LDL particles, cardiac risk may be further enhanced when the particles are smaller versus larger.

 

LDL Gradient Gel Electrophoresis

LDL particle diameter can be measured using nuclear magnetic resonance or ultracentrifugation while particle density can be measured by gradient gel electrophoresis (GGE). GGE is the most commonly used lab technique.

 

LDL gradient gel electrophoresis (GGE) has been promoted as an important determinant of coronary heart disease (CHD) risk, and as a guide to drug and diet therapy in patients with established coronary artery disease (CAD). The measurement of LDL subclass patterns may be useful in elucidating possible atherogenic dyslipemia in patients who have no abnormalities in conventional measurement (total cholesterol, HDL, LDL and triglycerides). However, the therapeutic usefulness of discovering such subclass abnormalities has not been substantiated.

 

Small LDL size is a component of an atherogenic lipid profile; other components include increased triglycerides, increased apo B, and decreased HDL. Some studies have reported that LDL size is an independent risk factor for CAD, while others have reported that a shift in LDL size may be a useful marker of treatment response.

 

A relatively small number of studies have evaluated the predictive ability of LDL particle size and number as measured by NMR. These studies do not demonstrate that NMR-measured particle size and/or number offer predictive ability beyond that provided by traditional lipid measures. NMR measures have been proposed as indicators of residual cardiovascular risk in patients treated with statins who have met LDL goals, but there is no evidence that these measures improve health outcomes when used for this purpose.

 

The direct clinical application of measuring small, dense lipoprotein particles is still unclear. To improve outcomes, clinicians must have tools to translate this information into clinical practice. Such tools for linking levels of small, dense LDL to clinical decision making are currently not available. Published data are inadequate to determine how such measurements should guide treatment decisions and whether these treatment decisions result in beneficial patient outcomes.

 

Lipoprotein (a)

Lipoprotein (a) (Lp(a)) is a lipid-rich particle similar to LDL. Apo B is the major apolipoprotein associated with LDL; in Lp(a), however, there is an additional apo A covalently linked to the apo B. The apo A molecule is structurally similar to plasminogen, suggesting that Lp(a) may contribute to the thrombotic and atherogenic basis of CVD. Levels of Lp(a) are relatively stable in individuals over time but vary up to 1000-fold between individuals, presumably on a genetic basis. The similarity between Lp (a) and fibrinogen has stimulated an intense interest in Lp (a) as a link between atherosclerosis and thrombosis. In addition, approximately 20% of patients with CAD have elevated Lp(a) levels. Therefore, it has been proposed that levels of Lp(a) may be an independent risk factor for CAD.

 

A large amount of epidemiologic evidence has determined that Lp(a) is an independent risk factor for CVD. The overall degree of risk associated with Lp(a) levels appears to be modest, and the degree of risk may be mediated by other factors such as LDL levels and/or hormonal status.

 

There is considerable uncertainty regarding the clinical utility of measuring Lp(a), specifically how knowledge of Lp(a) levels can be used in clinical care of patients being evaluated for lipid disorders. There is scant evidence on the use of Lp(a) as a treatment target for patients with hyperlipidemia. The available evidence is insufficient related to impact on clinical outcomes.

 

High Density Lipoprotein (HDL) Subclass

HDL comprises several components and subclasses that also have been related to CHD risk. While HDL cholesterol is the risk indicator most often used, HDL subclasses (HDL2 and HDL3) have also been used for risk prediction. HDL particles exhibit considerable heterogeneity, and it has been proposed that various subclasses of HDL may have a greater role in protection from atherosclerosis. Particles of HDL can be characterized based on size or density and/or on apolipoprotein composition. Using size or density, HDL can be classified into HDL2, the larger, less dense particles that may have the greatest degree of cardioprotection, and HDL3, which are smaller, denser particles.

 

An alternative to measuring the concentration of subclasses of HDL is direct measurement of HDL particle size and/or number. Particle size can be measured by nuclear magnetic resonance (NMR) spectroscopy or by gradient-gel electrophoresis. HDL particle numbers can be measured by NMR spectroscopy. Several commercial labs offer these measurements by HDL particle size and number. Measurement of apo AI has used HDL particle number as a surrogate, based on the premise that each HDL particle contains 1 apo AI molecule.

 

One RCT has evaluated the association of HDL particle size and number as measured by NMR with residual CVD risk. While this study found an association with HDL particle (but not HDL size) and CVD, it is uncertain how NMR-measured HDL particle number would be used to change clinical management beyond information provided by traditional lipid measures.

 

Non-Lipid Markers

Brain Natriuretic Peptide

Brain natriuretic peptide (BNP) is an amino acid polypeptide that is secreted primarily by the ventricles of the heart when pressure to the cardiac muscles increase or there is myocardial ischemia. Elevations in BNP levels reflect deterioration in cardiac loading levels and may predict adverse events. BNP has been studied as a biomarker for managing heart failure and predicting cardiovascular and heart failure risk.

 

BNP levels appear to be associated with cardiovascular risks. However, no evidence was identified demonstrating that the use of BNP testing in clinical care improves outcomes.

 

Cystatin C

Cystatin C is a small serine protease inhibitor protein that is secreted from all functional cells in the body. It has primarily been used as a biomarker for kidney function. Cystatin C has also been studied to determine whether it may serve as a biomarker for predicting cardiovascular risk. Cystatin C is encoded by the CST3 gene.

 

Several meta-analyses have reported that higher levels of cystatin C are associated with higher cardiovascular risk and higher risk of cardiovascular death. In contrast, in a large cohort, cystatin C did not improve risk prediction of CVD. No evidence was identified demonstrating that the use of cystatin C testing in clinical care improves.

 

Thrombogenic/Hemostatic Factors

Thrombosis plays a key role in acute coronary syndromes, including myocardial infarction. Both platelets and coagulation factors are involved in the thrombotic process. Although the precise hemostatic or prothrombotic mechanisms that predisopose to myocardial infarction have not been worked out, the evidence that aspirin and other antiplatelet therapy can reduce risk is compelling and suggests a role for platelet hyperaggregability. Another hemostatic factor associated with CHD risk is fibrinogen. A high fibrinogen level associates significantly with increased risk for coronary events, independent of cholesterol level; and conversely, a low fibrinogen level indicates a reduced risk, even in the presence of high total cholesterol levels. Other hemostatic factors that have been found to be associated with increased coronary risk include activated factor VII, plasminogen activator inhibitor-1 (PAI-1), tissue plasminogen activator (tPA), von Willebrand factor, factor V Leiden, protein C, and antithrombin III. Studies have shown that some of these prothrombotic factors are elevated as a component of the metabolic syndrome.

 

Fibrinogen

Fibrinogen is a circulating clotting factor that acts at the final step in the coagulation response to vascular and tissue injury, and epidemiological data support an independent association between elevated levels of fibrinogen to be associated with future risk of cardiovascular disease. The evidence regarding fibrinogen and cardiovascular risk is based on cohort studies which has not proven that the use of fibrinogen testing in clinical care improves outcomes. Further clinical trials are necessary before it can be determined whether fibrinogen has a casual role in atherothrombosis or is merely a marker of the degree of vascular damage taking place.

 

Reports from a number of cohort studies have suggested that fibrinogen levels are associated with cardiovascular risk. However, no evidence was identified demonstrating that the use of fibrinogen testing in clinical care improves outcomes.

 

Leptin

Leptin is a protein secreted by fat cells that has been found to be elevated in heart disease. Leptin has been studied to determine if it has any relationship with the development of cardiovascular disease.

 

Two meta-analyses have suggested that leptin levels are associated with CHD and stroke, although this association may depend on BMI. Another meta-analysis suggested no significant association between leptin concentration and CHD risk. No evidence was identified demonstrating that the use of leptin testing in clinical care improves outcomes.

 

MTHFR

The MTHFR gene provides instructions for making an enzyme called methylenetetrahydrofolate reductase. This enzyme plays a role in processing amino acids, the building blocks of proteins. Methylenetetrahydrofolate reductase is important for a chemical reaction involving forms of the vitamin folate (also called vitamin B9). Specifically, this enzyme converts a molecule called 5,10-methylenetetrahydrofolate to a molecule called 5-methyltetrahydrofolate. This reaction is required for the multistep process that converts the amino acid homocysteine to another amino acid, methionine. The body uses methionine to make proteins and other important compounds. MTHFR mutation, have been associated with increased cardiovascular risk.

 

Polymorphisms in the MTHFR gene have also been studied as possible risk factors for a variety of common conditions. These include heart disease, stroke, high blood pressure (hypertension), high blood pressure during pregnancy (preeclampsia), an eye disorder called glaucoma, psychiatric disorders, and certain types of cancer. Research indicates that individuals who have the 677C>T polymorphism on both copies of the MTHFR gene have an increased risk of developing vascular disease, including heart disease and stroke. Many of the MTHFR gene polymorphisms alter or decrease the activity of methylenetetrahydrofolate reductase, leading to an increase of homocysteine in the blood. This increase in homocysteine levels may contribute to the development of many of these conditions.

 

Studies of MTHFR gene variations in people with these disorders have had mixed results, with associations found in some studies but not in others. Therefore, it remains unclear what role changes in the MTHFR gene play in these disorders. It is likely that additional factors influence the processing of homocysteine and that variations in homocysteine levels play a role in whether a person develops any of these conditions. A large number of genetic and environmental factors, most of which remain unknown, likely determine the risk of developing most common, complex conditions.

 

Measurement of Long Chain Omega-3 Fatty Acids in Red Blood Cell Membranes

Higher palmitic and lower long chain omega-3 fatty acids (e..g alpha-linolenic, eicosapentaenoic and docosahexaenoic acids) in serum are correlated with higher incidence of CHD. It has been proposed that red blood cell (RBC) fatty acids composition, which is an index of long term intake of eicosapentaenoic plus docosahexaenoic acids, can be considered a new, modifiable, and clinically relevant risk factor for death from CHD. However, there is lack of scientific evidence regarding how measurements of RBC omega-3 fatty acids composition would affect management of individuals at risk for or patients with CHD. Large randomized clinical trials are needed to ascertain the clinical value of RBC omega-3 fatty acids composition in the management of CHD.

 

Summary

For individuals who are asymptomatic with risk of cardiovascular disease (CVD) who receive novel cardiac biomarker testing (e.g., apo B, apo AI, apo E, HDL subclass, LDL subclass, Lp[a], BNP, cystatin C, fibrinogen, leptin, MTHFR, Long Chain Omega-3 fatty acids), the evidence includes systematic reviews, meta-analyses, and large, prospective cohort studies. The evidence from cohort studies and meta-analyses of these studies has suggested that some of these markers are associated with increased cardiovascular risk and may provide incremental accuracy in risk prediction. In particular, apo B and apo AI have been identified as adding some incremental predictive value. However, it has not been established whether the incremental accuracy provides clinically important information beyond that of traditional lipid measures. Furthermore, no study has provided high-quality evidence that measurement of markers leads to changes in management that improve health outcomes. The evidence is insufficient to determine the effects of the technology on health outcomes.

 

Inflammatory Markers of Coronary Artery Disease Risk

Evidence has suggested that there may be certain biomarkers of CAD that may have a pro-inflammatory role in the progression of atherosclerosis. Recognition that atherosclerosis represents, in part, an inflammatory process has created interest in measurement of pro-inflammatory factors as part of cardiovascular disease risk assessment.

 

Lipoprotein-Associated Phospholipase A2 (Lp-PLA2) and Secretory Phospholipase A2 (sPLA2-IIA):

Lipoprotein-associtaed phospholipase A2 (Lp-PLA2), also known as platelet activating factor acetylhydrolase, is an enzyme that hydrolyzes phospholipids and is primarily associated with low-density lipoproteins (LDLs). Accumulating evidence has suggested that Lp-PLA2 and secretory phospholilpase A2 (sPLA2-IIA) are biomarkers of coronary artery disease (CAD) and may have a pro-inflammatory role in the progression of atherosclerosis.

 

Recognition that atherosclerosis represents, in part, an inflammatory process has created considerable interest in the measurement of proinflammatory factors as part of cardiovascular disease risk assessment.

 

Interest in Lp-PLA2 as a possible causal risk factor for CAD has generated development and testing of Lp-PLA2 inhibitors as a new class of drugs to reduce the risk of CAD. However, clinical trials of Lp-PLA2 inhibitors have not shown significant reductions in CAD end points.

 

A large body of literature has accumulated on the utility of risk factors in the prediction of future cardiac events. The evidence assessed for this review consists of large, prospective cohort studies that have evaluated the association between lipoprotein-associated phospholipase A2 (Lp-PLA2) and cardiovascular outcomes.

 

The National Cholesterol Education Program (NCEP) ATP-III guidelines have indicated that to determine the clinical significance of Lp-PLA2, the emerging risk factors should be evaluated against the following criteria:

  • Significant predictive power that is independent of other major risk factors.
  • A relatively high prevalence in the population (justifying routine measurement in risk assessment).
  • Laboratory or clinical measurement must be widely available, well-standardized, inexpensive, have accepted population reference values, and be relatively stable biologically.
  • Preferable, but not necessarily, modification of the risk factor in clinical trials will have shown reduction in risk.

 

A 2002 BlueCross and BlueShield Association TEC Assessment summarized the steps necessary to determine the utility of a novel cardiac risk factor. The following 3 steps were required:

  • Standardize the measurement of the risk factor.
  • Determine its contribution to risk assessment. As a risk factor, it is important to determine whether the novel risk factor independently contributes to risk assessment compared with established risk factors.
  • Determine how the novel risk assessment will be used in the management of the patient, compared with standard methods of assessing risk, and whether any subsequent changes in patient management result in an improvement in patient outcome.

 

The purpose of Lp-PLA2 testing in patients who have risk of cardiovascular disease (CVD) is to inform improve patient stratification using risk prediction models that alter management decisions and improve health outcomes.

 

Clinical Validity

A large consistent body of evidence has established that Lp-PLA2 level is an independent predictor of CAD. Relatively few studies have examined the degree to which Lp-PLA2 improves on existing CAD prediction models regarding clinically important magnitudes of reclassification.

 

Levels of Lp-PLA2 decrease substantially after treatment with antilipid medications, including statins. However, in treated patients, Lp-PLA2 levels may no longer be associated with risk of CAD, and thus may not be useful as a measure of treatment response.

 

Clinical Utility

Changes in patient management that could potentially occur with a strategy using Lp-PLA2 levels are not well-established. Studies that directly evaluate patient management changes and/or health outcome improvements are needed to determine whether the use of Lp-PLA2 measurement has efficacy in CVD. Alternatively, robust decision modeling studies may demonstrate clinically important changes in health outcomes by incorporating Lp-PLA2 levels into CAD prediction models. Groups such as the American Heart Association have often incorporated results from decision models to inform their guidelines when the data underlying the models are robust. Incorporation of Lp-PLA2 into decision models is necessary to demonstrate the potential clinical utility of the biomarker.

 

Summary

For individuals who have a risk of cardiovascular disease who receive Lp-PLA2 testing, the evidence includes studies of technical reliability and studies of the association between Lp-PLA2 and various coronary artery disease outcomes. The studies have demonstrated that Lp-PLA2 levels are an independent predictor of cardiovascular disease. Although Lp-PLA2 levels are associated with cardiovascular disease risk, changes in patient management that would occur as a result of obtaining Lp-PLA2 levels in practice are not well-defined. To demonstrate clinical utility, clinicians must have the tools to incorporate Lp-PLA2 test results into existing risk prediction models that improve classification into risk categories alter treatment decisions and lead to improved health outcomes. Direct evidence for such improved health outcomes with Lp-PLA2 testing in clinical practice is lacking. The evidence is insufficient to determine the effects of the technology on health outcomes.

 

Myeloperoxidase (MPO):

Higher levels of the leukocyte enzyme myeloperoxidase (MPO), which is secreted during acute inflammation and promotes oxidation of lipoproteins, are associated with the presence of coronary disease and may be predictive of acute coronary syndrome in patients with chest pain. Although elevated plasma MPO concentration may be associated with a more advance cardiovascular disease risk profile, plasma MPO does not predict mortality independent of other cardiovascular disease risk factors in patients with stable coronary artery disease. There is a lack of scientific evidence regarding how measurements of MPO would affect management of individuals at risk for or patients with CHD. Large randomized controlled studies are needed to ascertain the clinical value of MPO in the management of CVD risk.

 

Homocysteine Testing in the Screening, Diagnosis and Management of Cardiovascular Disease

Homocysteine (Hcy) is an amino acid that has been evaluated as a potential markers of cardiovascular disease (CVD). The association between homocysteine-lowering interventions and risk of CVD has been examined.

 

Homocysteine is a sulfur-containing amino acid that is rapidly oxidized in plasma into homocysteine and cysteine-homocysteine disulfide. Measurement of total plasma homocysteine is the sum of homocysteine and its oxidized forms.

 

Plasma levels of homocysteine have been actively researched as a risk factor for cardiovascular disease (CVD), initially based on the observation that patients with hereditary homocystinuria, an inborn error of metabolism associated with high plasma levels of homocysteine, had a markedly increased risk of CVD. Subsequently, prospective epidemiologic studies were conducted to determine if an elevated plasma level of homocysteine was an independent risk factor for CVD and could be used to improve current risk prediction models.

 

Interest in homocysteine as a potentially modifiable risk factor has been stimulated by the epidemiologic finding that levels of homocysteine inversely correlate with levels of folate. This finding has raised the possibility that treatment with folic acid might lower homocysteine levels and, in turn, reduce the risk of CVD. Therefore, homocysteine has potential utility both as a risk predictor and as a target of treatment.

 

Determination of homocysteine concentration may be offered as a component of a comprehensive cardiovascular risk assessment that may include evaluation of small-density lipoproteins, subclassification of high-density lipoproteins, evaluation of lipoprotein (a), high-sensitivity C-reactive protein, and genotyping of apolipoprotein E.

 

The purpose of testing homocysteine levels in asymptomatic patients at risk of cardiovascular disease (CVD) or in patients who have CVD is to inform management decisions such as whether to lower homocysteine levels.

 

Clinical Validity

A meta-analysis of observational studies found a moderately statistically significant association between homocysteine levels and risk of CVD. One study analyzing nationally representative survey data found that adding homocysteine level to the FRS significantly improved risk prediction.

 

Studies have also found a significant correlation between homocysteine levels in patients with known CVD and subsequent coronary events. One study analyzing nationally representative survey data found that adding homocysteine level to the Framingham risk score significantly improved risk prediction. Overall, the available evidence has suggested that homocysteine levels are associated with increased risk of a variety of cardiovascular disorders and outcomes among patients with existing CVD.

 

Clinical Utility

Assessing whether the use of homocysteine in clinical practice to manage CVD has clinical utility requires demonstrating that identification of homocysteine levels leads to changes in patient management that improve patient outcomes.

 

Vitamin B and folic acid supplementation are potential interventions that could be used for patients with high homocysteine levels to improve health outcomes. However, public health measures are already in place that require all enriched grain products be fortified with folic acid to reduce the risk of neural tube defects in newborns. This fortification has been associated with a decrease in plasma homocysteine concentration in a population-representative adult sample. Trials evaluating the impact of homocysteine-lowering therapy on health outcomes should thus evaluate the utility of treatments that lower homocysteine levels beyond those achieved by these general public health measures. In addition, clear target levels for homocysteine concentration would need to be established for translating information on homocysteine lowering into clinical practice.

 

Numerous randomized controlled trials (RCTs) have provided evidence on the benefit of vitamin therapy to reduce homocysteine levels and prevent cardiovascular (CV) events. Moreover, several meta-analyses have synthesized the available RCT evidence assessing the impact of vitamin therapy on homocysteine levels and CV events.

 

Summary

For individuals who are asymptomatic with risk of CVD or individuals with CVD who receive homocysteine testing, the evidence includes observational studies and RCTs of homocysteine-lowering interventions. Observational evidence has generally supported the association between homocysteine levels and CVD risk, especially in patients with preexisting vascular disease. However, evidence from RCTs evaluating homocysteine-lower interventions does not support the hypothesis that lowering homocysteine levels with folate and/or B vitamins improves cardiovascular outcomes. Numerous large RCTs and meta-analyses of these trials have consistently reported that homocysteine-lowering treatment is ineffective in reducing major cardiovascular events. One systematic review, with a subgroup analysis of patients from 3 RCTs who were not on antiplatelet therapy at baseline, found that homocysteine-lowering treatment reduced the risk of stroke in that group. However, replication of this effect in countries with grain enriched with folic acid would be needed. Given the large amount of evidence from placebo-controlled randomized trials that homocysteine-lowering interventions do not improve health outcomes, it is unlikely that routine homocysteine testing has the potential to change management that improves health outcomes. The evidence is sufficient to determine that the technology is unlikely to improve the net health outcome.

 

Genetic Markers (Genomic Profiling) to Assess Cardiovascular Risk

Susceptibility of coronary artery disease (CAD) is claimed to be 40% to 60% inherited, but until recently genetic risk factors predisposing to CAD have been elusive. It has been suggested that an improvement in CVD risk classification (adjusting intermediate risk of CVD into high or low risk categories) might lead to management changes (e.g. earlier initiation or higher rates of medical interventions, or targeted recommendations for behavioral change) that improve CVD outcomes.

 

9p21 Genetic Variant

The evaluation of Genomic Applications in Practice and Prevention Working Group (EWG) (2010) found insufficient evidence to recommend testing for the 9p21 genetic variant or 57 other variants in 28 genes to assess risk for cardiovascular disease (CVD) in the general population, specifically heart disease and stroke. The EWG found that the magnitude of net health benefit from use of any of these tests alone or in combination are negligible. The EWG discourages clinical use unless further evidence supports improved clinical outcomes. Based on the available evidence, the overall certainty of net health benefit is deemed low.

 

KIF6 Genotyping

Genetic testing to determine KIF6 (Trp719Arg) variant status is being evaluated as a prognostic test to predict risk of future cardiovascular events and/or as a pharmacogenetic test to predict response to statin therapy, particularly high risk patients.

 

The evidence for use of KIF6 genotyping for individuals who are asymptomatic with risk of CVD is limited and it has not been determined whether knowledge of carrier status can be used to improve patient management decisions and improve net health outcomes. The evidence is insufficient to determine the effects of this.

 

LPA Genetic Variant

Patients with a positive test for the LPA genetic variant rs3798220 have a higher risk for thrombosis and therefore may derive greater benefit from the antithrombotic properties of aspirin. As a result, testing for the rs3798220 variant has been proposed as a method of stratifying benefit from aspirin treatment.

 

The LPA minor allele, rs3798220, is associated with higher levels of LPA and a higher risk of cardiovascular events. This allele is infrequent in the population and is associated with a modest increase in cardiovascular risk in the general population. Testing for this allele is commercially available, but performance characteristics are uncertain and standardization of testing has not been demonstrated. Several observational studies have reported that this genetic variant is an independent risk factor for cardiovascular disease, but some studies have not reported a significant association. It is unclear whether the information derived from genetic testing leads to changes in management. In particular, it cannot be determined from available evidence whether deviating from current guidelines on aspirin treatment based on LPA genetic testing improves outcomes. Therefore, the measurement of the LPA rs3798220 variant as a decision aid for aspirin treatment is considered investigational.

 

Cardiovascular Risk Panels

Cardiovascular risk panels refer to different combinations of cardiac markers that are intended to evaluate risk of cardiovascular disease (CVD). There are numerous commercially available risk panels that include different combinations of lipids, non-cardiac biomarkers, measures of inflammation, metabolic parameters, and/or genetic markers. Risk panels report the results of multiple individual tests, as distinguished from quantitative risk scores that combine results of multiple markers into a single score.

 

Cardiovascular risk panels (CVD) may contain measures from one or all of the following categories: lipid markers; inflammatory markers; metabolic syndrome biomarkers and genetic markers. The panels may also include other measures such as radiologic markers (carotid medial thickness, coronary artery calcium score). Some CVD panels are relatively limited, including a few markers in addition to standard lipids. Others include a wide variety of potential risk factors from a number of different categories, often including both genetic and non-genetic risk factors. Other panels are composed entirely of genetic markers.

 

Some examples of commercially available cardiovascular disease (CVD) risk panels including but not limited to the following:

  • Cardiac Risk Panel (Health Diagnostics): MTHFR gene analysis, common variants; vitamin D, 1, 25 dihydroxy; B-type natriuretic peptide (BNP); Lp-PLA2; myeloperoxidase; apolipoprotein; immune complex assay; lipoprotein, blood; electrophorectic separation and quanititation; very long chain fatty acids; total cholesterol; HDL; LDL; triglycerides; (high sensitivity CRP, hs-CRP); lipoprotein (a); insulin; total fibrinogen; apolipoprotein analysis; multiple SNPs associated with coronary artery disease (CAD).
  • Boston Heart Diagnostics: total cholesterol; triglyceride; HDL-C; APO A-1; Boston Heart Lab Mapy; LDL-C; Lp(a); Apo-B; sdLDL-C; Boston Heart Cholesterol Balance; hs-CRP; Lp-PLA2; MPO; Boston Heart Prediabetes Assessment; glucose; insulin; HbA1c; Boston Heart Statin Induced Myopathy (SLCO1B1) Genotype; Apo-E; Factor II/Factor V; NT-proBNP; vitamin D.
  • CV Health Plus Genomics Panel (Genova Diagnostics): apo E; prothrombin; factor V leiden; fibrinogen; HDL; HDL size; HDL particle number; homocysteine; LDL; LDL size; LDL particle number; lipoprotein (a); Lp-PLA2: MTHFR gene; triglycerides; very low density lipoprotein (VLDL); VLDL size; vitamin D; hs-crp
  • CV Health Plus Panel (Genova Diagnostics): fibrinogen; HDL; HDL size; HDL particle number; homocysteine; LDL, LDL size; LDL particle number; lipid panel; lipoprotein (a); LP-PLA2; triglycerides; VLDL; VLDL size; vitamin D; hs-CRP.
  • Cardiovascular Health Profile (Metametrix): homocysteine; C-reactive protein (hs-CRP); fibrinogen; red blood cell magnesium; coenzyme Q10; vitamin E; lipid peroxides; total testosterone; sex hormone binding globulin; free androgen index (calculation); insulin; ferritin; total cholesterol; HDL cholesterol; LDL cholesterol; triglycerides; lipoprotein (a).
  • CVD Inflammatory Profile (Cleveland Heartlab): hs-CRP; urinary microalbumin; myeloperoxidase; Lp-PLA2; F2-isoprostanes.
  • Applied Genetics Cardiac Panel: genetic mutations associated with CAD; cytochrome p450 mutations associated with metabolism of clopidogrel, ticagrelor, warfarin,B-blockers, rivaroxaban, and prasurgrel (2C19, 2C9/VKORC1, 2D6, 3A4/3A5); factor V leiden;, prothrombin gene; MTHFR gene; apo-E gene.
  • Genetiks Genetic Diagnosis and Research Center Cardiovascular Risk Panel: factor V leiden; factor V R2; prothrombin gene; factor XIII; fibrinogen -455; PAI-1; GPIIIs (HPA-1); MTHFR; ACE I/D; apo B; apo E.
  • 4myheart (Quest Diagnostics): lipoprotein subfractionation by ion mobility; Apo-B; Lp(a); homocysteine; Lp-PLA2; hs-CRP; fibrinogen; insulin; NT-proBNP; vitamin D; omega 3 and 6; 4q25-AF risk genotype test; 9p21 genotype; Apo-E genotype; CYP2C19 genotype; KIF6 genotype; LPA-aspirin genotype; LPA intron 25 genotype; apolipoprotein A1; hemoglobin A1c.
  • Cardiac Related Test Panels (Singulex):
    • Cardiac Dysfunction panel: SMCTM cTmNI (high sensitivity troponin); NT-proBNP
    • Vascular Information and Dysfunction panel: SMCTM IL-6; SMCTM IL-7; SMCTM TNFa; SMCTM Endothelin; Lp-PLA2; hs-CRP; homocysteine; vitamin B12; folate
    • Dyslipidemia panel: cholesterol total; LDL-C (direct); APO B; sdLDL; HDL-C; APO A-1; HDL2b; triglycerids; Lp(a)
    • Cardiometabolic: Parathyroid hormone; vitamin D; calcium;magnesium; leptin; adiponectin; ferritin; cortisol a.m.; testosterone; cystatin C; glucose; insulin; T4; T3; Free T4; Free T3; TSH; uric acid.

 

In addition to panels that are specifically focused on CVD risk, a number of commercially available panels include makers associated with cardiovascular health, along with a range of other markers that have been associated with inflammation, thyroid disorders and other hormonal deficiencies, and other disorders. Examples of these panels include:

  • Cardiometabolic Panel (Singulex): described above
  • Wellness FX Premium (WellnessFX): total cholesterol, HDL, LDL, triglycerides, apo AI, apo B, Lp(a), Lp-PLA2, omega-3 fatty acids, free fatty acids, lipid particle numbers, lipid particle sizes, blood urea nitrogen/creatinine, aspartate aminotransferase and alanine aminotransferase, total bilirubin, albumin, total protein, dehydroepiandrosterone, free testosterone, total testosterone, estradiol, sex hormone binding globulin, cortisol, insulin-like growth factor 1, insulin, glucose, hemoglobin A1c, total T4, T3 uptake, free T4 index, thyroid-stimulating hormone, total T3, free T3, reverse T3, free T4, hs-CRP, fibrinogen, homocysteine, complete blood count with differential, calcium, electrolytes, bicarbonate, ferritin, total iron binding capacity, vitamin B12, red blood cell magnesium, 25-hydroxy vitamin D, progesterone, follicle-stimulating hormone, luteinizing hormone.

 

The purpose of CVD risk panel testing in patients who have risk factors for CVD is to inform management and treatment decisions. The beneficial outcomes of interest are decreased morbidity and mortality from CVD. Development of CVD occurs over many years and manifests as coronary heart disease (CHD), CVD, or peripheral arterial disease. The timing for measuring outcomes can range from 5 to 10 years. Patient who have risk factors for CVD are initially managed in primary care. Patients who have had CV event may be followed in specialty clinics by cardiologists and neurologists.

 

While multiple risk factors have been individually associated with CVD, there is no convincing evidence that the addition of any individual risk marker, or combination of risk markers, leads to clinically meaningful changes in management that improve outcomes. In the available studies, improvements in risk prediction have generally been of a small magnitude, and/or have not been found to be associated with clinically meaningful management changes. Because of this uncertain impact on management, the clinical utility for any of the individual risk markers is either low or uncertain.

 

Moreover, the available evidence on individual risk markers is only of limited value in evaluating CVD risk panels. It is difficult to extrapolate the results of single risk factors to panels, given the variable composition of panels. Ideally, panels should be evaluated individually based on their impact on clinical decision making.

 

No published studies were identified that evaluated the use of commercially available CVD risk panels as risk prediction instruments in clinical care. Some studies have attempted to incorporate novel risk markers into an overall quantitative risk score, but these risk scores are not the same as CVD risk panels, which report the results of individual risk factors.

 

Furthermore, there are no standardized methods for combining multiple individual risk factors with each other, or with established risk prediction instruments such as the FRS. Therefore, there is a potential for both overestimation and underestimation of the true cardiac risk. This may lead to management decisions based on an inaccurate risk assessment. As a result of these deficiencies, it is not possible to assess the impact of using CVD risk panels on health outcomes reliably.

 

Summary

For individuals who have risk factors for CVD who receive CVD risk panels, the evidence includes multiple cohort and case-control studies and systematic reviews of these studies. The available evidence from cohort and case-control studies indicates that many of the individual risk factors included in CVD risk panels are associated with increased risk of CVD. However, it is not clear how the results of individual risk factors impact management changes, so it is also uncertain how the panels will impact management decisions. Given the lack of evidence for clinical utility of any individual risk factor beyond simple lipid measures, it is unlikely that the use of CVD risk panels improves outcome. Studies that have evaluated the clinical validity of panels of multiple markers have not assessed management changes that would occur as a result of testing or demonstrated improvements in outcomes. The evidence is insufficient to determine the effects of the technology on net health outcomes.

 

Practice Guideline and Position Statements

American College of Cardiology Foundation (ACCF)/American Heart Association (AHA)

In 2013, the American College of Cardiology Foundation (ACCF) and American Heart Association (AHA) issued a joint guideline for the assessment of cardiovascular risk.
These guidelines recommended that age- and sex-specific pooled cohort equations, which included total cholesterol and high-density lipoprotein to predict the 10-year risk of a first hard atherosclerotic cardiovascular disease event, be used in non-Hispanic blacks and non-Hispanic whites between 40 and 79 years of age (American Heart Association/American College of Cardiology class of recommendation I, American Heart Association/American College of Cardiology level of evidence B). Regarding newer risk markers after quantitative risk assessment, the guidelines stated the following: “If, after quantitative risk assessment, a risk-based treatment decision is uncertain, assessment of ≥1 of the following: family history, hs-CRP [high-sensitivity C-reactive protein], CAC [coronary artery calcium] score, or ABI [ankle-brachial index] may be considered to inform treatment decision-making” (class of recommendation IIb, level of evidence B). The guidelines did not recommend other novel cardiac risk factors or panels of cardiac risk factors.

 

Lipoprotein-associated phospholipase A2 (Lp-PLA2) testing was not mentioned in this guidelines.

 

U.S. Preventative Services Task Force (USPSTF)

In 2009, The USPSTF made the following recommendation about using nontradiational risk factors in coronary heart disease risk assessment:

 

The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of using the nontraditional risk factors studied to screen asymptomatic men and women with no history of CHD to prevent CHD events. (Grade: Insufficient)

 

The nontraditional risk factors included in this recommendation are high-sensitivity C-reactive protein (hs-CRP), ankle-brachial index (ABI), leukocyte count, fasting blood glucose level, periodontal disease, carotid intima-media thickness (carotid IMT), coronary artery calcification (CAC) score on electron-beam computed tomography (EBCT), homocysteine level, and lipoprotein(a) level.

 

In 2016, the USPSTF made the following recommendation about the use of primary prevention of cardiovascular disease in adults: preventative medication:

 

The USPSTF recommends that adults without a history of cardiovascular disease (CVD) (ie, symptomatic coronary artery disease or ischemic stroke) use a low- to moderate-dose statin for the prevention of CVD events and mortality when all of the following criteria are met: 1) they are aged 40 to 75 years; 2) they have 1 or more CVD risk factors (ie, dyslipidemia, diabetes, hypertension, or smoking); and 3) they have a calculated 10-year risk of a cardiovascular event of 10% or greater. (Grade B)

 

Identification of dyslipidemia and calculation of 10-year CVD event risk requires universal lipids screening in adults aged 40 to 75 years. See the “Clinical Considerations” section for more information on lipids screening and the assessment of cardiovascular risk.

 

Clinical Considerations

Periodic assessment of cardiovascular risk factors from ages 40 to 75 years, including measurement of total cholesterol, LDL-C, and HDL-C levels, is required to implement this recommendation. The optimal intervals for cardiovascular risk assessment are uncertain. Based on other guidelines and expert opinion, reasonable options include annual assessment of blood pressure and smoking status and measurement of lipid levels every 5 years. Shorter intervals may be useful for persons whose risk levels are close to those warranting therapy, and longer intervals are appropriate for persons who are not at increased risk and have repeatedly normal levels.

 

National Heart, Lung and Blood Institute

The National Heart, Lung, and Blood Institute’s National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) issued a position statement in 2001. Apolipoprotein B (apo B), apolipoprotein AI (apo AI), lipid subclass, and lipoprotein (a) (Lp[a]) were listed as “emerging risk factors” for cardiovascular risk assessment, without specific recommendations for how these measures should be used in clinical practice. A 2004 update to these guidelines discussed the result of clinical trials of statin therapy.

 

In 2013, the Institute published a systematic evidence review on managing blood cholesterol in adults. The review was used to develop joint guidelines by the American College of Cardiology (ACC) and American Heart Association (AHA) on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults (see above).

 

European Society of Cardiology et. al.

The 2012 guidelines from the European Society of Cardiology and other societies on cardiovascular disease (CVD) prevention in clinical practice indicated that apo B can be a substitute for low-density lipoprotein cholesterol (LDL-C), but its use does not improve risk assessment and apo B is not readily available. The use of Lp(a) was not justified as a treatment target or for screening the general population. LpPLA2 may be measured as part of a refined risk assessment in patients at high risk of a recurrent acute atherothrombotic event (Class IIb recommendation; Level of Evidence B; weak evidence).

 

In 2016, the Society and other societies issued guidelines on cardiovascular risk prevention in clinical practice, which included recommendations for lipid control based on LDL-C levels and targets. The guidelines indicated that ‘there is no evidence that apo B is a better predictor of CVD than LDL-C.” They also stated that while the apo B/apo AI ratio is one of the strongest predictors of CVD, there is insufficient evidence to supports its use as a treatment goal.

 

National Institute for Health and Care Excellence (NICE)

The National Institute for Health and Care Excellence updated its guidance on risk assessment and reduction, including lipid modification, of CVD in 2016. The guidance recommended measuring a full lipid profile including total cholesterol, high-density lipoprotein (HDL), non-HDL, and triglycerides before starting lipid-lowering therapy for primary prevention of CVD. The guidance also recommended measurement of total cholesterol, HDL, non-HDL, and triglycerides for primary and secondary prevention in people on high-intensity statins at 3 months of treatment, aiming for 40% reduction in non-HDL. Apo B and other nontraditional risk factors were not discussed as part of risk assessment or treatment targets.

 

Regulatory Status

Multiple assay methods for cardiac risk marker components, such as lipid panels and other biochemical assays, have been cleared for marketing by the U.S. Food and Drug Administration through the 510(k) process.

 

Other components of testing panels are laboratory-developed tests. Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

 

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments. Lipid and non‒lipid biomarker tests are available under the auspices of the Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

 

Several homocysteine test systems have been cleared for marketing by the U.S. Food and Drug Administration through the 510(k) process. Food and Drug Administration product code: LPS.

 

In December 2014, the PLAC® Test (diaDexus, San Francisco, CA), a quantitative enzyme assay, was cleared for marketing by the U.S. Food and Drug Administration through the 510(k) process for Lp-PLA2 activity. It was considered substantially equivalent to a previous version of the PLAC® Test (diaDexus), which was cleared for marketing by the Food and Drug Administration in July 2003. Food and Drug Administration product code: NOE.

 

Prior Approval:

Not applicable

 

Policy:

Novel biomarkers in Risk Assessment and Management of Cardiovascular Disease

The measurement of lipid or non-lipid biomarkers for cardiovascular disease risk assessment and/or management including but not limited to the following is considered investigational:

  • Low density lipoprotein (LDL) particles subclass
  • LDL gradient gel electrophoresis
  • Lipoprotein remnants: intermediate density lipoprotein (IDL)
  • Lipoprotein (a) enzyme immunoassay
  • High density lipoprotein subclass, HDL subspecies (HDL2 and HDL3)
  • Apolipoprotein B (apo B)
  • Apolipoprotein A-I (apo A-I)
  • Apolipoprotein E (apo E)
  • B-type natriuretic peptide (BNP) (Brain Natriuretic Peptide)
  • Cystatin C
  • Fibrinogen (may also include thrombogenic or hemostatic factors including but not limited to Fibrinogen, Prothrombin coagulation factor II and Factor V Leiden)
  • Long chain omega-3 fatty acids composition in red blood cell
  • Leptin
  • Vitamin D
  • Homocysteine

 

Numerous non-traditional lipid measurements have been proposed for use in improving risk prediction for cardiovascular disease. In general, there is evidence that some of these markers may provide some incremental accuracy in risk prediction. However, it has not been established that the incremental accuracy provides clinically important information beyond that of traditional lipid measures. Furthermore, no study has provided high-quality evidence that measurement of these markers leads to changes in management that improve health outcomes. The evidence is insufficient to determine the effects of the technology on net health outcomes.

 

Measure of Inflammatory Markers in the Assessment of Cardiovascular Risk

The measurement of inflammatory makers including but not limited to lipoprotein-associated phospholipase A2 (Lp-PLA2), other hyman A2 phospholipase such as secretory phospholipase A2 (sPLA2-IIA) or plasma myeloperoxidase (MPO) in the assessment of cardiovascular risk is considered investigational.

 

Based on review of the medical literature the evidence is insufficient to support conclusions concerning net health outcomes and benefits associated with this testing. Additional well-designed clinical trials are necessary to establish the clinical utility of this testing for cardiovascular risk assessment. The evidence is insufficient to determine the effects of the technology on net health outcomes.

 

Cardiovascular Risk Panels

Cardiovascular risk panels, consisting of multiple individual biomarkers intended to assess cardiac risk (other than simple lipid panels, see below note), including but not limited to the following, are considered investigational.

  • Cardiac Risk Panel (Health Diagnostics)
  • Boston Heart Diagnostics
  • CV Health Plus Genomics Panel (Genova Diagnostics)
  • CV Health Plus Panel (Genova Diagnostics)
  • Cardiovascular Health Profile (Metametrix)
  • CVD Inflammatory Profile (Cleveland Heartlab)
  • Applied Genetics Cardiac Panel
  • Genetiks Genetic Diagnosis and Research Center Cardiovascular Risk Panel
  • 4myheart (Quest Diagnostics)
  • Cardiac Related Test Panels (Singulex)
    • Cardiac Dysfunction Panel
    • Vascular Information and Dysfunction Panel
    • Dyslipidemia Panel
    • Cardiometabolic Panel
  • WellnessFX Premium (WellnessFX)

 

The available evidence from cohort case control studies and systematic reviews indicates that many of the individual risk factors included in the cardiovascular disease (CVD) risk panels are associated with increased risk for CVD. However, it is not clear how the results of individual risk factors impact management changes, so it is uncertain how the panels will impact management decisions. Given the lack of evidence for clinical utility of any individual risk factor beyond simple lipid measures, it is unlikely that the use of CV panels improves outcome. Studies that have evaluated the clinical validity of panels of multiple markers have not assessed management changes that would occur as a result of testing, or demonstrated improvements in outcomes. The evidence is insufficient to determine the effects of this testing on net health outcomes.

 

Note: A simple lipid panel generally includes the following lipid measures: total cholesterol, LDL cholesterol, HDL cholesterol and triglycerides.

 

Genetic Markers (Genotype Testing) for Predicting Cardiovascular Risk

Genetic Markers (genotype testing) for predicting cardiovascular disease risk and/or management is considered investigational, including but not limited to the following, as there is insufficient evidence to support that genetic markers alters the management or improves net health outcomes:

  • KIF6 genotype
  • 9p21 genotype
  • CYP2C19 genotype
  • 4q25-AF risk genotyping
  • LPA –Aspirin genotype
  • LPA intron 25 genotype
  • Apolipoprotein E genotyping (APO E genotyping)
  • MTHFR

 

Procedure Codes and Billing Guidelines:

To report provider services, use appropriate CPT* codes, Modifiers, Alpha Numeric (HCPCS level 2) codes, Revenue codes, and/or diagnosis codes.

  • 81240 Prothrombin coagulation factor II (see also medical policy 02.04.46)
  • 81241 Factor V Leiden (see also medical policy 02.04.46)
  • 81225 CYP2C19 (see also medical policy 02.04.67)
  • 81291 MTHFR (see also medical policy 02.04.46)
  • 81401 Molecular pathology procedure, Level 2 (eg, 2-10 SNPs, 1 methylated variant, or 1 somatic variant [typically using nonsequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat)
  • 81479 Unlisted molecular pathology procedure (when utilized with a description of KIF6, 9p21, 4q25-AF, LPA-Aspirin, LPA-Intron 25, this code may also be utilized for cardiovascular risk panels)
  • 81599 Unlisted multianalyte assay with algorithmic analysis (may be used for cardiovascular risk panels)
  • 82172 Apolipoprotein, each
  • 82306 Vitamin D; 25 hydroxy, includes fraction(s), if performed (see also medical policy 02.04.34)
  • 82652 Vitamin D; 1,25 dihydroxy, includes fraction(s), if performed (see also medical policy 02.04.34)
  • 82397 Chemiluminescent assay (Leptin)
  • 82610 Cystatin C
  • 82664 Electrophoretic technique, not otherwise classified
  • 83090 Homocysteine (see also medical policy 02.04.22)
  • 83695 Lipoprotein (a) enzyme immunoassay
  • 83698 Lipoprotein-associated phospholipase A2 (Lp-PLA2)
  • 83700 Lipoprotein, blood; electrophoretic separation and quantitation
  • 83701 Lipoprotein, blood; high resolution fractionation and quantitation of lipoprotein subclasses when performed (e.g., electrophoresis, ultracentrifugation)
  • 83704 Lipoprotein, blood; quantitation of lipoprotein particle number(s) (eg, by nuclear magnetic resonance spectroscopy), includes lipoprotein particle subclass(es), when performed
  • 83876 Myeloperoxidase (MPO)
  • 83880 Natriuretic peptid
  • 85384 Fibrinogen activity
  • 85385 Fibrinogen antigen
  • 0111T Long chain omega-3 fatty acids in red blood cell (RBC) membranes
  • 0423T Secretory type II phospholipase A2 (sPLA2-IIA)
  • 0038U Vitamin D, 25 hydroxy D2 and D3, by LC-MS/MS, serum microsample, quantitative (see also medical policy 02.04.34)
  • 0052U  Lipoprotein, blood, high resolution fractionation and quantitation of lipoproteins, including all five major lipoprotein classes and subclasses of HDL, LDL, and VLDL by vertical auto profile ultracentrifugation


 

Selected References:

  • St-Pierre AC, Ruel IL, Cantin B, et al. Comparison of various Electrophoretic Characteristics of LDL Particles and Their Relationship to the Risk of Ischemic Heart Disease. Circulation 2001;104:2295-2299.
  • Lamarche B, St-Pierre AC, Ruel IL, Cantin B, Dagenais GR, Despres JP. A prospective, population-based study of low density lipoprotein particle size as a risk factor of ischemic heart disease in men. The Canadian Journal of Cardiology2001;17(8):859-865.
  • Superko HR. Small, dense, low-density lipoprotein and atherosclerosis. Current Atherosclerosis Report 2000;2:226-231.
  • Festa A. Small, Dense Low Density Lipoprotein (LDL) and the Insulin Resistance Syndrome (IRS). Clinical Laboratory2001;47:111-118.
  • Williams, PT, et al. Smallest LDL Particles Are Most Strongly Related to Coronary Disease Progression in Men. Arteriodcler Thromb Vasc Biol. February 2003;(23) 314-321.
  • Mackey RH, Kuller LH, et al.  Hormone therapy, lipoprotein subclasses, and coronary calcification: the Healthy Women Study.  Arch Intern Med. 2005 Mar 14;165(5):510-5.
  • St-Pierre AC, Cantin B, et al. Low-density lipoprotein subfractions and the long-term risk of ischemic heart disease in men: 13-year follow-up data from the Quebec Cardiovascular Study.  Arterioscler Thromb Vasc Biol. 2005 Mar;25(3):553-9.
  • Executive Summary of the Third Report National Cholesterol Education Program. (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Final Report. JAMA May 16, 2001;285(19):2486-2497. PMID 11368702
  • BlueCross and BlueShield Technology Assessment. C-Reactive Protein as a Cardiac Risk Marker (Special Report). TEC Assessment 2002; Volume 17:Tab 23
  • Brunzell JD, Davidson M, et al. Lipoprotein Management in Patients With Cardiometabolic Risk. Diabetes Care, volume 31, number 4, April 2008
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  • Jellinger PS, Handelsman Y, Rosenblit PD, et al. American Association of Clinical Endocrinologists and American College of Endocrinology guidelines for management of dyslipidemia and prevention of cardiovascular disease. Endocr Pract. Apr 2017;23(Suppl 2):1-87. PMID 28437620
  • Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1 - executive summary. J Clin Lipidol. Sep-Oct 2014;8(5):473-488. PMID 25234560
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  • Stability Investigators, White HD, Held C, et al. Darapladib for preventing ischemic events in stable coronary heart disease. N Engl J Med. May 1 2014;370(18):1702-1711. PMID 24678955 
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  • Nicholls SJ, Kastelein JJ, Schwartz GG, et al. Varespladib and cardiovascular events in patients with an acute coronary syndrome: the VISTA-16 randomized clinical trial. JAMA. Jan 15 2014;311(3):252-262. PMID 24247616
  • Ridker PM, Macfadyen JG, Wolfert RL, et al. Relationship of lipoprotein-associated phospholipase A2 mass and activity with incident vascular events among primary prevention patients allocated to placebo or to statin therapy: an analysis from the JUPITER Trial. Clin Chem. May 2012;58(5):877-886. PMID 22419750
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  • Helfand M, Buckley DI, Freeman M, et al. Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U.S. Preventive Services Task Force. Ann Intern Med. Oct 6 2009;151(7):496-507. PMID 19805772 
  • Brotman DJ, Walker E, Lauer MS, et al. In search of fewer independent risk factors. Arch Intern Med. Jan 24 2005;165(2):138-145. PMID 15668358
  • Zethelius B, Berglund L, Sundstrom J, et al. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N Engl J Med. May 15 2008;358(20):2107-2116. PMID 18480203
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  • WellnessFX. 
  • UpToDate Overview of Possible Risk Factors for Cardiovascular Disease. Peter WF Wilson M.D., Topic last updated February 6, 2018. 
  • UpToDate. Overview of Cardiovascular Risk Factors in Women. Pamela S. Douglas M.D., Athena Poppas M.D. Topic last updated December 6, 2017.

 

 

Policy History:

  • April 2018 - Annual Review, Policy Revised 
  • April 2017 - Annual Review, Policy Revised 
  • April 2016 - Annual Review, Policy Revised 
  • May 2015  - Annual Review, Policy Revised 
  • June 2014 - Annual Review, Policy Revised 
  • Augugst 2013 - Annual Review, Policy Revised 
  • September 2012  - Annual Review, Policy Renewed
  • September 2011 - Annual Review, Policy Renewed

Wellmark medical policies address the complex issue of technology assessment of new and emerging treatments, devices, drugs, etc.   They are developed to assist in administering plan benefits and constitute neither offers of coverage nor medical advice. Wellmark medical policies contain only a partial, general description of plan or program benefits and do not constitute a contract. Wellmark does not provide health care services and, therefore, cannot guarantee any results or outcomes. Participating providers are independent contractors in private practice and are neither employees nor agents of Wellmark or its affiliates. Treating providers are solely responsible for medical advice and treatment of members. Our medical policies may be updated and therefore are subject to change without notice.

 

*CPT® is a registered trademark of the American Medical Association.