Pending Policies - Medicine
Novel Biomarkers in Risk Assessment and Management of Cardiovascular Disease
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Measurement of novel lipid and nonlipid risk factors is considered experimental, investigational and/or unproven as an adjunct to low density lipoproteins (LDL) cholesterol in the risk assessment and management of cardiovascular disease, including, but not limited to the following:
• Apolipoprotein E,
• LDL subclass,
• High Density Lipoprotein (HDL) subclass, or
Low density lipoprotein (LDL) has been identified as the major atherogenic lipoprotein and has long been identified by the National Cholesterol Education Project (NCEP) 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.
Numerous lipid and nonlipid biomarkers have been proposed as potential risk markers for cardiovascular disease. This policy will focus on the above mentioned lipid markers. The biomarkers assessed here are apolipoprotein E (Apo E), high-density lipoprotein (HDL) subclass, low-density lipoprotein (LDL) subclass, and lipoprotein (a).
Apolipoprotein E (ApoE) is the primary apolipoprotein found in very low density lipoproteins (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 ApoE gene is polymorphic, consisting of 3 epsilon alleles (e2, e3, e4) that code for 3 protein isoforms, known as E2, E3, and E4, which differ from one another by 1 amino acid. These molecules mediate lipid metabolism through their different interactions with the 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 1 factor that determines an individual’s degree of response to interventions such as statin therapy.
Two main subclass patterns of LDL, called A and B, have been described. In subclass pattern A, the particles have a diameter larger than 25 nm and are less dense, while in subclass pattern B, the 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 high density lipoprotein (HDL). This lipid profile is commonly seen in type II diabetes and is 1 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 (CRP), 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 induce 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. Niacin and/or fibrates may cause a greater shift from small to large LDL size than statins. Therefore, measurement of LDL size may potentially play a role in drug selection or may be useful in deciding to use a combination of 2 or more 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, 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 compared with larger particles. Therefore, for patients with elevated numbers of LDL particles, cardiac risk may be further enhanced when the particles are smaller versus larger.
Two techniques are most commonly used for measuring LDL particle concentration, the surrogate measurement of Apo B or direct measurement of the number of particles using nuclear magnetic resonance (NMR). NMR is used based on the fact that lipoprotein subclasses of different size broadcast distinguishable NMR signals. Thus NMR can directly measure the number of LDL particles of a specific size (i.e., small dense LDL) and can provide a measurement of the total number of particles. Therefore, NMR is proposed as an additional technique to assess cardiac risk.
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/density and/or on the apolipoprotein composition. Using size/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. HDL contains 2 associated apolipoproteins, i.e., AI and AII. HDL particles can also be classified by whether they contain Apo AI only or whether they contain both Apo AI and Apo AII. There has been substantial interest in determining whether subclasses of HDL can be used to provide additional information on cardiovascular risk compared to HDL alone.
An alternative to measuring the concentration of subclasses of HDL, such as HDL2 and HDL3, is direct measurement of HDL particle size and/or number. Particle size can be measured by NMR spectroscopy or by gradient-gel electrophoresis. HDL particle numbers can be measured by NMR spectroscopy.
Several commercial labs offer these measurements of HDL particle size and number. Measurement of Apo AI has used measurement of HDL particle number as a surrogate, based on the premise that each HDL particle contains one Apo AI molecule.
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 apolipoprotein (a) molecule is structurally similar to plasminogen, suggesting that lp(a) may contribute to the thrombotic and atherogenic basis of cardiovascular disease. 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 intense interest in lp(a) as a link between atherosclerosis and thrombosis. In addition, approximately 20% of patients with CAD have elevated levels of lp(a). Therefore, it has been proposed that levels of lp(a) may be an independent risk factor for CAD.
This policy has been updated with searches of scientific literature through March 2017. The following is a summary of the key literature to date.
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 for this coverage statement consists of systematic reviews, meta- analyses and large, prospective cohort studies that have evaluated the association of these lipid markers with 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 is taken from randomized controlled trials (RCTs) that use one or more novel lipid markers as a target of lipid-lowering therapy.
The Adult Treatment Panel (ATP) III guidelines document (1) notes that to determine their clinical significance, the emerging risk factors should be evaluated against the following criteria to determine their clinical significance:
• 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 BCBSA TEC Assessment (2) summarized the steps necessary to determine 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.
Each of the individual novel lipid risk factors will be judged individually against these criteria to determine whether health outcomes are improved through measurement of the novel lipid risk factor.
A Health Technology Assessment (HTA) performed for the National Institute for Health Research on strategies for monitoring lipid levels in patients at risk or with cardiovascular disease (CVD) was published in 2015. (76) The HTA included a systematic review of predictive associations for CVD events. Studies were included if they had at least 12 months of follow-up and 1000 participants. Results were stratified by use of statins and primary versus secondary prevention. For populations not taking statins, 90 publications reporting 110 cohorts were included and for populations taking statins, and 25 publications reporting 28 cohorts were included. In populations not taking statins, the ratio of apolipoprotein B (apo B) to apolipoprotein AI (Apo AI) was mostly strongly associated with the outcome of CVD events (hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.22 to 1.5) although the hazard ratios for Apo B, total cholesterol/high-density lipoprotein (HDL), and low-density lipoprotein (LDL)/HDL all had overlapping confidence intervals with the hazard ratio for apo B/apo AI. In populations taking statins, insufficient data were available to estimate the association between apo B or apo AI with CVD events.
Thanassoulis et al. in 2014 reported on a meta-analysis of 7 placebo-controlled statin trials to evaluate the relationship of statin-induced reductions in lipid levels to reduction of coronary heart disease risk. (3) Each of the trials included -density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein-cholesterol (HDL- C), and apolipoprotein B (Apo B) values assessed at baseline and 1-year follow-up. In both frequents and Bayesian meta-analyses, reductions in Apo B were more closely related to coronary heart disease risk reduction from statins than LDL-C or non-HDL-C.
In 2013, van Holten et al. reported on a systematic review of 85 articles with 214 meta-analyses to compare serological biomarkers for risk of cardiovascular disease (CVD). (4) Predictive potential for primary CVD events was strongest with lipids with a ranking from high to low found with: C-reactive protein (CRP), fibrinogen, cholesterol, Apo B, the apolipoprotein A (Apo A)/Apo B ratio, HDL, and vitamin D. Markers associated with ischemia were more predictive of secondary cardiovascular events and included from high to low result: cardiac troponins I and T, C-reactive protein (CRP), serum creatinine, and cystatin C. A strong predictor for stroke was fibrinogen.
Tzoulaki et al., in 2013, reported on an evaluation of meta-analyses on biomarkers for CVD risk to examine potential evidence of bias and inflation of result in the literature. (5) Included in the evaluation were 56 meta-analyses with 49 reporting statistically significant results. Very large heterogeneity was seen in 9 meta-analyses, and small study effects were seen in 13 meta-analyses. Significant excess of studies with statistically significant results was found in 29 meta-analyses (52%). The authors report only 13 of the meta-analyses with statistically significant results had more than 1000 cases and no evidence of large heterogeneity, small-study effects, or excess significance.
In a 2013 systematic review, Willis et al. evaluated whether validated CVD risk scores can identify patients at risk for CVD for participation in more intensive intervention programs for primary prevention. (6) Sixteen papers on 5 studies were included in the systematic review. The authors were unable to perform a meta- analysis due to the heterogeneity of the studies. The evidence was considered not strong enough to draw definitive conclusions, but the authors note lifestyle interventions with higher intensity may have potential for lowering CVD risk.
Apo E as a Predictor of Cardiovascular Disease
A large body of research has established a correlation between lipid levels and the underlying APOE genotype. For example, in population studies, the presence of an Apo e2 allele is associated with the lowest cholesterol levels and the Apo e4 allele is associated with the highest levels. (7, 8)
Numerous studies have focused on the relationship between genotype and physiologic markers of atherosclerotic disease. A number of small- to medium-sized cross-sectional and case-control studies have correlated Apo E with surrogate outcomes such as cholesterol levels, markers of inflammation, or carotid intima-media thickness. (9-14) These studies have generally shown a relationship between Apo E and these surrogate outcomes. Other studies have suggested that carriers of Apo e4 are more likely to develop signs of atherosclerosis independent of TC and LDL-C levels. (15-18)
Some larger observational studies have correlated APOE genotype with clinical disease. The Atherosclerosis Risk in Communities (ARIC) study followed up 12,000 middle-aged subjects free of CAD at baseline for 10 years. (74) This study reported that the e3/2 genotype was associated with carotid artery atherosclerosis after controlling for other atherosclerotic risk factors. Volcik et al. reported that APOE polymorphisms were associated with LDL levels and carotid intima-media thickness but were not predictive of incident CAD. (19)
A meta-analysis published by Bennet et al. (20) summarized the evidence from 147 studies on the association of APOE genotypes with lipid levels and cardiac risk. Eighty-two studies included data on the association of Apo E with lipid levels, and 121 studies reported the association with clinical outcomes. The authors estimated that patients with the Apo e2 allele had LDL levels that were approximately 31% less compared with patients with the Apo e4 allele. When compared with patients with the Apo e3 allele, patients with Apo e2 had an approximately 20% decreased risk for coronary events (OR=0.80; 95% CI, 0.70 to 0.90). Patients with the Apo e4 had an estimated 6% higher risk of coronary events that was of marginal statistical significance (OR=1.06; 95% CI, 0.99 to 1.13).
In 2016, Sofat et al. published a meta-analysis of 3 studies of circulating apo E and CVD events. (77) The method for selecting the studies was not described. The 3 studies included 9587 participants and 1413 CVD events. In the pooled analysis, there was no association of apo E with CVD events. The unadjusted odds ratio for CVD events for a standard deviation increase in apo E concentration was 1.02 (95% CI, 0.96 to 1.09). After adjustment for other cardiovascular risk factors, the odds ratio for CVD for a standard deviation increase in apo E concentration was 0.97 (95% CI 0.82, 1.15).
Apo E as a Predictor of Response to Therapy
Apo E has been investigated as a predictor of response to therapy by examining Apo E alleles in the intervention arm(s) of lipid-lowering trials. Some data suggest that patients with an Apo e4 allele may respond better to diet-modification strategies. (21, 22) Other studies have suggested that response to statin therapy may vary with ApoE genotype and that the e2 allele indicates greater responsiveness to statins. (23)
Chiodini et al. (24) examined differential response to statin therapy according to APOE genotype, by reanalyzing data from the GISSI study according to APOE genotype. GISSI was an RCT comparing pravastatin with placebo in 3304 Italian patients with previous myocardial infarction (MI). Patients with the Apo e4 allele treated with statins had a greater response to treatment as evidenced by lower overall mortality (1.85% vs 5.28%, respectively, p=0.023), while there was no difference in mortality for patients who were not treated with statins (2.81% vs 3.67%, respectively, p=0.21). This study corroborates results reported in previous studies but does not provide evidence to suggest that changes in treatment should be made as a result of APOE genotype.
Donnelly et al. (25) reported on 1383 patients treated with statins from the Genetics of Diabetes Audit and Research in Tayside, Scotland (Go-DARTS) database. The researchers reported on the final LDL levels and percent of patients achieving target LDL according to APOE genetic status. LDL levels following treatment were lower for patients who were homozygous for Apo e2, compared with patients homozygous for Apo e4 (0.6±0.5 mmol/L vs 1.7±0.3 mmol/L, p<0.001). All patients who were homozygous for Apo e2 reached their target LDL level, compared with 68% of patients homozygous for Apo e4 (p<0.001).
Vossen et al. (26) evaluated response to diet and statin therapy by Apo E status in 981 patients with CAD who were enrolled in a cardiac rehabilitation program. These authors reported that patients with an Apo e4 allele were more responsive to both diet and statin therapy than were patients with an Apo e2 allele. The overall response to treatment was more dependent on baseline LDL levels than APOE genetic status, with 30% to 47% of the variation in response to treatment explained by baseline LDL, compared with only 1% of the variation explained by APOE status.
Section Summary: Apolipoprotein E
The evidence suggests 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 when compared with other established and emerging clinical variables and does not explain a large percent 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 one of the important “emerging risk factors” 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 gauge a patient’s chance of successful treatment, although not all studies are consistent in reporting this relationship. At present, it is unclear how this type of information will 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 will choose alternative therapies, even in the presence of an APOE phenotype that indicates diminished response.
None of the available evidence provides adequate data to establish that APOE genotype or phenotype improves outcomes when used in clinical care. Thus, given the uncertain impact on clinical outcomes, this testing is considered experimental, investigational and/or unproven.
HDL Particle Size/Concentration
In the JUPITER RCT, (28) 10,886 patients without cardiovascular disease were randomized to rosuvastatin or placebo and followed for a median of 2 years. Before randomization and 1 year after, levels of LDL-C, HDL-C, Apo AI, and nuclear magnetic resonance (NMR) measured HDL size and HDL particle (HDL-P) numbers were evaluated. Statistically significant changes in the median and 25th and 75th percentile values of HDL measures between baseline and year 1 values occurred in the rosuvastatin and placebo groups for all levels (p<0.001) except for Apo AI and HDL-P size in the placebo group, which were not significantly different (p=0.09 and 0.74, respectively). Changes in the rosuvastatin group were all statistically significant when compared with placebo for LDL-C, HDL-C, Apo AI, and HDL-P size and number (p<0.001 for all). In the placebo group, inverse associations with cardiovascular disease and HDL-C, Apo AI, and HDL-P were seen. HDL-P number in the rosuvastatin group had a greater association with cardiovascular disease (HR=0.73; 95% CI, 0.57 to 0.93; p=0.01) than HDL-C (HR=0.82; 95% CI, 0.63 to 1.08; p=0.16) or Apo AI (HR=0.86; 95% CI, 0.67 to 1.10; p=0.22). This association remained after adjusting for HDL-C (HR=0.72; 95% CI, 0.53 to 0.97; p=0.03). HDL size was not significantly associated with cardiovascular disease in risk factor?adjusted models.
Current Treatment Guidelines
No guidelines were identified that specify a role for HDL subclass for the identification or management of cardiovascular disease.
Section Summary- HDL Particle Size/Concentration
One RCT has evaluated the association of HDL particle size and number as measured by NMR with residual cardiovascular disease risk. While this study found an association with HDL-P (but not HDL size) and cardiovascular disease, this does not demonstrate how NMR-measured HDL-P number would be used to change clinical management beyond information provided by traditional lipid measures. Therefore, there is no evidence that HDL size or HDL-P number measurement improves health outcomes.
Based on the available evidence and the uncertain impact of testing on clinical outcomes, testing for HDL particle size or concentration is considered experimental, investigational and/or unproven.
LDL Subclass and LDL Particle Size/Concentration
LDL Subclass as an Independent Risk Factor for Cardiovascular Disease
A nested case-control study from the Physician’s Health Study, a prospective cohort study of approximately 15,000 men, investigated whether LDL particle size was an independent predictor of CAD risk, particularly in comparison to triglyceride levels. (29) This study concluded that while LDL particle diameter was associated with risk of myocardial infarction (MI), this association was not present after adjustment for triglyceride level. Only triglyceride level was significant independently.
The Quebec Cardiovascular Study (10,30) evaluated the ability of “nontraditional” lipid risk factors, including LDL size, to predict subsequent CAD events in a prospective cohort study of 2155 men followed up for 5 years. The presence of small LDL was associated with a 2.5 times increased risk for ischemic heart disease after adjustment for traditional lipid values, indicating a level of risk similar to total LDL. This study also suggested an interaction in atherogenic risk between LDL size and Apo B levels. In the presence of small LDL particles, elevated Apo B levels were associated with a 6-fold increased risk of CAD, whereas when small LDL particles were not present, elevated Apo B levels were associated with only a 2-fold increase in risk.
In 2005, Tzou et al. examined the clinical value of “advanced lipoprotein testing” in 311 randomly selected adults participating in the Bogalusa Heart Study. (31) Advanced lipoprotein testing consisted of subclass patterns of LDL, i.e., presence of large buoyant particles, intermediate particles, or small dense particles. These measurements were used to predict the presence of subclinical atherosclerosis, as measured ultrasonographically by carotid intimal-media thickness. In multivariate logistic regression models, substituting advanced lipoprotein testing for corresponding traditional lipoprotein values did not improve prediction of the highest quartile of carotid intimal-media thickness.
LDL Subclass as a Predictor of Treatment Response
Patients with subclass pattern B have been reported to respond more favorably to diet therapy compared with those with subclass pattern A. (32) Subclass pattern B has also been shown to respond more favorably to the drugs gemfibrozil and niacin, with a shift from small, dense LDL particles to larger LDL particles. While statin drugs lower the overall concentration of LDL-C, there is no shift to the larger LDL particles. (33)
Superko et al. (34) reported that the response to gemfibrozil differed in patients with LDL subclass A compared with those with LDL subclass B. There was a greater reduction in the small, low-density LDL levels for patients with subclass B, but this was not correlated with clinical outcomes. Another study reported that atorvastatin treatment led to an increase in mean LDL size, while pravastatin treatment led to a decrease in LDL size. (35)
These studies generally confirmed that small, dense LDL is impacted preferentially by fibrate treatment (36-38) and possibly also by statin therapy. (36-38) However, none of the studies demonstrate that preferentially targeting small, dense LDL leads to improved outcomes, compared with using the standard LDL targets that are widespread in clinical care.
Several trials with angiographic outcomes have examined the change in LDL particle size in relation to angiographic progression of CAD. The Stanford Coronary Risk Intervention Project (SCRIP) trial studied the relationship between small, dense LDL and the benefit of diet, counseling, and drug therapy in patients with CAD, as identified by initial coronary angiogram. (39) Patients with subclass pattern B showed a significantly greater reduction in CAD progression, compared with those with subclass pattern A. The Familial Atherosclerosis Treatment Study (FATS) randomized patients from families with premature CAD and elevated Apo B levels. (40) Change in LDL particle size was significantly correlated with angiographic progression of CAD in this study. Fewer studies have evaluated clinical outcomes in relation to LDL particle size. In the Cholesterol and Recurrent Events (CARE) trial, survivors of MI with normal cholesterol levels were randomly assigned to lipid-lowering therapy or placebo. A post hoc analysis from this trial failed to demonstrate a correlation between change in particle size and treatment benefit. (41)
Measurement of LDL Particle Size and Concentration by NMR
Similar to small dense lipoprotein particles, several epidemiologic studies have shown that the lipoprotein particle size and concentration measured by NMR is also associated with cardiac risk. For example, data derived from the Cardiovascular Health Study, Women’s Health Study, and PLAC-1 trial suggest that the number of LDL particles is an independent predictor of cardiac risk. (42-44) Translating these findings into clinical practice requires setting target values for lipoprotein number. Proposed target values have been derived from the same data set (i.e., Framingham study) that was used to set the ATP III target goals for LDL-C. For example, the ATP III targets for LDL-C correspond to the 20th, 50th, and 80th percentile values in the Framingham Offspring Study, depending on the number of risk factors present. Proposed target goals for lipoprotein number correspond to the same percentile values, and LDL particle concentrations corresponding to the 20th, 50th, and 80th percentile are 1100 nmol/L, 1400 nmol/L, and 1800 nmol/L, respectively. (45)
Following publication of several clinical trials indicating benefit for intensive statin therapy with lowering of LDL goals beyond those recommended in the ATP III guidelines, (?) many experts recommend a further lowering of the target LDL-C from 100 mg/dL to 70 mg/dL in high-risk patients. These new, more aggressive targets of therapy create additional questions of how either measurements of either LDL concentration or LDL size can be used to improve patient management.
Mora et al. (46) evaluated the predictive ability of LDL particle size and number measured by NMR in participants of the Women’s Health Study, a prospective cohort study of 27,673 women followed over an 11-year period. After controlling for nonlipid factors, LDL particle number was a significant predictor of incident cardiovascular disease, with an HR of 2.51 (95% CI, 1.91 to 3.30) for the highest, compared with the lowest quintile. LDL particle size was similarly predictive of cardiovascular risk, with an HR of 0.64 (95% CI, 0.52 to 0.79). When compared with standard lipid measures and apolipoproteins, LDL particle size and number showed similar predictive ability but were not superior in predicting cardiovascular events.
Rosenson and Underberg conducted a systematic review of studies on lipid-lowering pharmacotherapies in 2013 to evaluate changes in LDL particles pre- and posttreatments. (47) Reductions in mean LDL particles occurred in 34 of the 36 studies evaluated. Percentage reductions of LDL particles in several statin studies were smaller than reductions in LDL-C. LDL particles and Apo B changes were comparable in studies. The authors suggest the differences in LDL particle reductions with different lipid-lowering therapies demonstrate potential areas of residual cardiovascular risk that can be addressed with LDL particle (LDL-P) monitoring.
In 2014 Toth et al. reported on an analysis of LDL-C and LDL-P levels and cardiovascular risk using commercial insurance and Medicare claims data on 15,569 high-risk patients from the HealthCore Integrated Research Database (HIRD). (48) For each 100 nmol/L increase in LDL-P level, there was a 4% increase in risk of a coronary heart disease event (HR=1.04; 95% CI, 1.02 to1.05; p<0.000). A comparative analysis, using 1:1 propensity score matching of 2094 patients from the LDL-C target cohort (LDL-C level <100 mg/dL without a LDL-P level) and a LDL-P target cohort (LDL-P <1000 nmol/L and LDL-C of any level) found a lower risk of coronary heart disease or stroke in patients who received LDL-P measurement and were presumed to have received more intensive lipid-lowering therapy (HR=0.76; 95% CI, 0.61 to 0.96; at 12 months). A comparison of smaller LDL-P target groups at 24 (n=1242) and 36 (n=705) months showed similar reductions in coronary heart disease and stroke (HR=0.78; 95% CI, 0.62 to 0.97 and HR=0.75; 95% CI, 0.58 to 0.97, respectively).
Current Treatment Guidelines
A 2008 consensus statement commented on the use of LDL-P number in patients with cardiometabolic risk. (? BCA 30) This article comments on the limitations of the clinical utility of NMR measurement of LDL-P number or size, including lack of widespread availability. This article also comments that there is a need for more independent data confirming the accuracy of the method and whether its predictive power is consistent across various patient populations.
Section Summary- LDL Subclass and LDL Particle Size/Concentration
Small LDL size is one component of an atherogenic lipid profile that also includes increased triglycerides, increased Apo B, and decreased HDL. Some studies have reported that LDL size is an independent risk factor for CAD, and others have reported that a shift in LDL size may be a useful marker of treatment response. However, the direct clinical application of measuring small, dense lipoprotein particles is still unclear. To improve outcomes, clinicians must have the tools to translate this information into clinical practice. Such tools for linking levels of small, dense LDL to clinical decision making, both in risk assessment and treatment response, 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.
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 additional 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.
Based on the available evidence and the uncertain impact of testing on clinical outcomes, testing for LDL subclass and LDL-P size/concentration is considered experimental, investigational and/or unproven.
Lipoprotein A as a Predictor of Cardiovascular Risk
Numerous prospective RCTs, cohort studies and systematic reviews have evaluated lipoprotein (a) (lp[a]) as a cardiovascular risk factor. The following are representative prospective trials drawn from the extensive literature on this topic.
The Emerging Risk Factors Collaboration published a patient-level meta-analysis of 37 prospective cohort studies enrolling 154,544 individuals. (9) Risk prediction was examined for a variety of traditional and nontraditional lipid markers. For lp(a), evidence from 24 studies on 133,502 subjects reported that lp(a) was an independent risk factor for reduced cardiovascular risk, with an adjusted HR for cardiovascular events of 1.13 (95% CI, 1.09 to 1.18). The addition of lp (a) to traditional risk factors resulted in a small improvement in risk prediction, with an increase in the C statistic of approximately 0.002. On reclassification analysis, there was no significant improvement in the net reclassification index (0.05%; 95% CI, -0.59 to 0.70).
A systematic review by Genser et al. (49) included 67 prospective studies on 181,683 subjects that evaluated the risk of cardiovascular disease associated with lp (a). Pooled analysis was performed on 37 studies that reported the end points of cardiovascular events. When grouped by design and populations, the relative risks for these studies, comparing the uppermost and lowest strata of lp (a), ranged from 1.64 to 2.37. The risk ratio for cardiovascular events was higher in patients with previous cardiovascular disease compared with patients without previous disease. There were no significant associations found between lp (a) levels, overall mortality, or stroke.
The Lipid Research Clinics (LRC) Coronary Primary Prevention Trial, one of the first large-scale, RCTs of cholesterol-lowering therapy, measured initial lp(a) levels and reported that lp(a) was an independent risk factor for CAD when controlled for other lipid and nonlipid risk factors. (50) As part of the Framingham offspring study, lp (a) levels were measured in 2191 asymptomatic men between the ages of 20 and 54 years. (51) After a mean follow-up of 15 years, there were 129 coronary heart disease events, including MI, coronary insufficiency, angina, or sudden cardiac death. Comparing the lp(a) levels of these patients with the other participants, the authors concluded that elevated lp(a) was an independent risk factor for the development of premature coronary heart disease (i.e., before age 55 years). The ARIC study evaluated the predictive ability of lp(a) in 12,000 middle-aged subjects free of CAD at baseline who were followed up for 10 years. The lp(a) levels were significantly higher among patients who developed CAD compared with those who did not, and lp(a) levels were an independent predictor of CAD above traditional lipid measures.
Several RCTs on lipid-lowering therapies have found lp(a) is associated with residual cardiovascular risk. In a subgroup analysis of 7746 white patients from the JUPITER study, (52) median lp(a) levels did not change in either group of patients randomized to treatment with rosuvastatin or placebo during a median 2-year follow-up. Lp(a) was independently associated with a residual risk of cardiovascular disease despite statin treatment (adjusted HR=1.27; 95% CI: 1.01 to 1.59, p=0.04). The LIPID RCT (53) randomized 7863 patients to pravastatin or placebo. Patients were followed for a median 6 years. Lp(a) concentrations did not change significantly at 1 year. Baseline lp(a) concentration was associated with total coronary heart disease events (p<0.001), total cardiovascular disease events (p=0.002), and coronary events (p=0.03). The AIM-HIGH study, (54) lp(a) levels in 1440 patients at baseline and on simvastatin plus placebo or simvastatin plus extended-release niacin were significantly predictive of CV events with HRs ranging from 1.18 to 1.25.
Kamstrup et al. (55) analyzed data from the Copenhagen City Heart Study, which followed up 9330 subjects from the Copenhagen general population over a period of 10 years. This study reported a graded increase in risk of cardiac events with increasing lp(a) levels. At extreme levels of lp(a) above the 95th percentile, the adjusted HR for MI was 3.6 (95% CI, 1.7 to 7.7) for women and 3.7 (95% CI, 1.7 to 8.0) in men. Tzoulaki et al. (56) reported data from the Edinburgh Artery Study, which was a population cohort study that followed up 1592 subjects for a mean of 17 years. These authors reported that lp(a) was an independent predictor of MI, with an OR of 1.49 (95% CI, 1.0 to 2.2) for the highest one-third versus the lowest one-third.
Zakai et al. (57) evaluated 13 potential biomarkers for independent predictive ability compared with established risk factors, using data from 4510 subjects followed up for 9 years in the Cardiovascular Health Study. The lp(a) was 1 of 7 biomarkers that had incremental predictive ability above established risk factors. The adjusted HR for each SD increase in lp(a) was 1.07 (95% CI, 1.0 to 1.12).
Some studies, however, have failed to demonstrate such a relationship. In the Physicians’ Health Study, initial lp(a) levels in the 296 participants who subsequently experienced MI were compared with lp(a) levels in matched controls who remained free from CAD. (58) The authors found that the distribution of lp(a) levels between the groups was identical. The European Concerted Action on Thrombosis and Disabilities (ECAT) study, a trial of secondary prevention, evaluated lp(a) as a risk factor for coronary events in 2800 patients with known angina pectoris. (59) In this study, lp(a) levels were not significantly different among patients who did and did not have subsequent events, suggesting that lp(a) levels were not useful risk markers in this population.
Some researchers have hypothesized that there is a stronger relationship between lp(a) and stroke than for coronary heart disease. Similar to the situation with cardiac disease, most prospective studies, but not all, have indicated that lp(a) is an independent risk factor for stroke. In 1 prospective cohort study, Rigal et al. (60) reported that an elevated lp(a) level was an independent predictor of ischemic stroke in men (OR=3.55; 95% CI, 1.33 to 9.48) but not in women (OR=0.42; 95% CI, 0.12 to 1.26). In the ARIC prospective cohort study of 14,221 participants, (61) elevated lp(a) was a significant independent predictor of stroke in black women (RR=1.84; 95% CI, 1.05 to 3.07) and white women (RR=2.42; 95% CI, 1.30 to 4.53) but not in black men (RR=1.72; 95% CI, 0.86 to 3.48) or white men (RR=1.18; 95% CI, 0.47 to 2.90).
There also may be a relationship between lp(a) as a cardiovascular risk factor and hormone status in women. Suk Danik et al. (62) reported the risk of a first cardiovascular event over a 10-year period in 27,736 women enrolled in the Women’s Health Study. After controlling for standard cardiovascular risk factors, lp(a) was an independent predictor of risk in women who were not taking hormonal replacement therapy (HR=1.77; 95% CI, 1.36 to 2.30; p<0.001). However, for women who were taking hormonal replacement therapy, lp(a) levels were not a significant independent predictor of cardiovascular risk (HR=1.13; 95% CI, 0.84 to 1.53; p=0.18).
Several meta-analyses have also examined the relationship between lp(a) levels and cardiovascular risk. Bennet et al. (63) synthesized the results of 31 prospective studies with at least 1 year of follow-up and that reported data on cardiovascular death and nonfatal MI. The combined results revealed a significant positive relationship between lp(a) and cardiovascular risk, with an OR for patients with lp(a) in the top-third compared with those in the bottom-third of 1.45 (95% CI, 1.32 to 1.58). This analysis reported a moderately high degree of heterogeneity in the included studies (I2=43%), reflecting the fact that not all studies reported a significant positive association.
Smolders et al. summarized evidence from observational studies on the relationship between lp(a) and stroke. (64) Five prospective cohort studies and 23 case-control studies were included in this meta-analysis. Results from prospective cohort studies, lp(a) added a modest amount of incremental predictive information (combined RR for the highest one-third of lp(a): 1.22; 95% CI, 1.04 to 1.43). From case- control studies, an elevated lp(a) level was also associated with an increased risk of stroke (combined OR=2.39; 95% CI, 1.57 to 3.63).
A patient-level meta-analysis of 36 prospective studies published between 1970 and 2009 included 126,634 participants. (65) Overall, the independent association of lp(a) with vascular disease was consistent across studies but modest in size. The combined risk ratio, adjusted for age, sex, and traditional lipid risk factor, was 1.13 (95% CI, 1.09 to 1.18) for coronary heart disease and 1.10 (95% CI, 1.02 to 1.18) for ischemic stroke. There was no association of lp(a) levels with mortality.
Genetic studies have examined the association of various genetic loci with lp(a) levels, and Mendelian randomization studies have examined whether lp(a) is likely to be causative for CAD. In 1 such study, (66) there were 3 separate loci identified for increased lp(a) levels. Genetic variants were identified at 2 of these loci that were independently associated with coronary disease (OR=1.70; 95% CI, 1.49 to 1.95; OR=1.92; 95% CI, 1.48 to 2.49). This finding strongly implies that elevated lp(a) levels are causative of coronary disease, as opposed to simply being associated.
Lipoprotein A as Treatment Target
There is a lack of evidence to determine whether lp(a) can be used as a target of treatment. Several randomized studies of lipid-lowering therapy have included measurements of lp(a) as an intermediate outcome measurement. While these studies have demonstrated that lp(a) levels are reduced in patients receiving statin therapy, the data are inadequate to demonstrate how this laboratory test can be used to improve patient management. (67, 68)
Section Summary: Lipoprotein A
A large amount of epidemiologic evidence has determined that lp(a) is an independent risk factor for cardiovascular disease. 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 who are 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; testing for lp(a) is considered experimental, investigational and/or unproven.
Summary of Evidence
Numerous nontraditional lipid and other biomarker measurements have been proposed for use in improving risk prediction for cardiovascular disease, including apolipoprotein AI (Apo AI), the ratio of Apo B/Apo AI, apolipoprotein E (Apo E), lipoprotein A, subclasses of low-density lipoprotein (LDL) and high-density lipoprotein (HDL). 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 markers leads to changes in management that improve health outcomes.
Some markers have also been proposed as treatment targets for lipid-lowering therapy. While some evidence supports that they may be accurate in predicting residual risk for patients on lipid-lowering therapy, there is no high-quality evidence that these markers lead to health outcome improvements when used in place of traditional lipid targets, such as LDL. Because of the deficiencies in the literature around these issues, the use of these novel lipid risk markers remains experimental, investigational and/or unproven.
Practice Guidelines and Position Statements
The American College of Cardiology/American Heart Association
The American College of Cardiology/American Heart Association published guidelines in 2013 for the assessment of cardiovascular risk. (69) Pooled cohort equations for estimating arteriosclerotic cardiovascular disease (ASCVD) were developed from sex and race specific proportional hazards models that included covarieties of age, treated or untreated systolic blood pressure level, total cholesterol and HDL cholesterol levels, current smoking status, and history of diabetes. Additional risk factors that were evaluated included diastolic blood pressure, family history of ASCVD, moderate or severe chronic kidney disease, and body mass index. None of these variables significantly improved discrimination for 10-year hard ASCVD risk prediction. Further research using state of the art statistical techniques (including net reclassification improvement and integrative discrimination index are needed to examine the utility of novel biomarkers when added to these new pooled cohort equations in different populations and patient subgroups.
European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice
The 2012 guidelines on cardiovascular disease prevention from the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice indicate Apo B can be a substitute for LDL-C, but its use does not improve risk assessment and Apo B is not readily available. (70) The use of lipoprotein (a) isn’t justified as a treatment target or for screening the general population.
The National Cholesterol Education Program
The National Cholesterol Education Program Expert Panel on Detection, Evaluation, and And Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) issued a position statement in 2001. (1) Apo B, Apo AI, lipid subclass, and lipoprotein (a) were listed as “emerging risk factors” for cardiovascular risk assessment, without specific recommendations for how these measures should be used in clinical practice. There was a 2004 update to these guidelines which discussed the result of clinical trials of statin therapy. (71)
American Diabetes Association and the American College of Cardiology Foundation
A publication from a consensus conference of the American Diabetes Association and the American College of Cardiology Foundation (72) included specific recommendations for incorporating Apo B testing into clinical care for high-risk patients. They recommended that for patients with metabolic syndrome who are being treated with statins, both LDL-C and Apo B should be used as treatment targets, with an Apo B target of less than 90 mg/dL. This consensus statement also commented on the use of LDL particle number in patients with cardiometabolic risk. They commented on the limitations of the clinical utility of NMR measurement of LDL-P number or size, including lack of widespread availability. They also mentioned that there is a need for more independent data confirming the accuracy of the method and whether its predictive power is consistent across various patient populations.
National Institute for Health and Care Excellence (NICE)
National Institute for Health and Care Excellence issued guidance on risk assessment and reduction, including lipid modification, of cardiovascular disease in 2014 and most recently updated in 2016. (78) The guidelines recommend measuring a full lipid profile including total cholesterol, HDL, non-HDL, and triglycerides before starting lipid lowering therapy for primary prevention of CVD. The guidelines also recommend measurement of total cholesterol, HDL, non-HDL, and triglycerides for primary and secondary prevention in people who have been started 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.
U.S. Preventive Services Task Force Recommendations
The U.S. Preventive Services Task Force issued recommendations in 2009 (73) on the use of nontraditional risk factors for the assessment of coronary heart disease. They included lipoprotein (a) in their summary statement that stated “The evidence is insufficient to assess the balance of benefits and harms of using the nontraditional risk factors discussed in this statement to screen asymptomatic men and women with no history of CHD to prevent CHD events”.
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|11/15/2018||Reviewed. No changes.|
|6/15/2017||Document updated with literature review. Coverage unchanged.|
|4/15/2016||Reviewed. No changes.|
|1/15/2015||Document updated with literature review. Medical document revised to address coverage positions previously housed in the following medical policies: 1) MED207.121 High Density Lipoprotein Subclass Testing in the Diagnosis and Management of Cardiovascular Disease, 2) MED207.123 Lipoprotein (a) Enzyme Immunoassay in the Management of Cardiovascular Disease, and 3) MED207.124 Apolipoprotein E Genotype or Phenotype Testing in the Risk Assessment and Management of Cardiovascular Disease. Coverage remains experimental, investigational and/or unproven for all testing including measurement of: small low-density lipoprotein particles and concentration of low density lipoproteins (LDL) particles in cardiac risk assessment and management. Medical Policy title changed from Measurement of Small Low-Density Lipoprotein (LDL) Particles and Concentration of LDL Particles in Cardiac Risk Assessment and Management. Rationale and Reference sections significantly revised. CPT/HCPCS code(s) updated.|
|8/15/2012||Document updated with literature review. Coverage unchanged.|
|12/15/2009||Revised/updated entire document. No change in coverage. Coverage position remains experimental, investigational, and unproven.|
|7/15/2007||Revised/updated entire document|
|12/1/2003||Revised/updated entire document|
|11/1/2000||New medical document|
|Title:||Effective Date:||End Date:|
|Novel Biomarkers in Risk Assessment and Management of Cardiovascular Disease||06-15-2017||11-14-2018|
|Novel Biomarkers in Risk Assessment and Management of Cardiovascular Disease||04-15-2016||06-14-2017|
|Novel Biomarkers in Risk Assessment and Management of Cardiovascular Disease||01-15-2015||04-14-2016|
|Measurement of Small Low-Density Lipoprotein (LDL) Particles and Concentration of LDL Particles in Cardiac Risk Assessment and Management||08-15-2012||01-14-2015|
|Measurement of Small Low-Density Lipoprotein (LDL) Particles and Concentration of LDL Particles in Cardiac Risk Assessment and Management||12-15-2009||08-14-2012|
|Measurement of Small Low-Density Lipoprotein (LDL) Particles and Concentration of LDL Particles in Cardiac Risk Assessment and Management||07-15-2007||12-14-2009|
|Measurement of Small Low Density Lipoprotein (LDL) Particles||12-01-2003||07-14-2007|