Reliability of Calculated Low-Density Lipoprotein Cholesterol

Comparison of Sampson and extended Martin/Hopkins methods of low-density lipoprotein cholesterol calculations with direct measurement in pediatric patients with hypertriglyceridemia

OBJECTIVE

The Friedewald equation is the commonly used method of low-density lipoprotein cholesterol (LDL-C) calculation, requiring reflex to direct LDL-C measurement when triglycerides (TG) ≥ 400 mg/dL. Recently formulated Sampson and extended Martin/Hopkins methods have been validated with TG up to 800 mg/dL and thus have the potential to replace direct LDL-C measurement. Given the growing prevalence of childhood dyslipidemia, the objective of this study was to compare Sampson and extended Martin/Hopkins methods of LDL-C calculation with the direct measurement in a pediatric cohort with 400 ≤ TG ≤ 799 mg/dL.

METHODS

This study retrieved standard lipid panels and corresponding direct LDL-C measurements of 131 patients with 400 ≤ TG ≤ 799 mg/dL from a pediatric population. Following the application of Sampson and extended Martin/Hopkins calculations, calculated values were compared with direct LDL-C measurements using ordinary least squares linear regression analysis and bias plotting.

RESULTS

Both Sampson and extended Martin/Hopkins LDL-C calculations exhibited a strong correlation with the direct measurements (Pearson r = 0.89) in patients with 400 ≤ TG ≤ 800 mg/dL. Average percentages of bias of 45% and 21% were found between the direct LDL-C measurements and Sampson or extended Martin/Hopkins calculations, respectively.

CONCLUSION

Both Sampson and extended Martin/Hopkins calculations are applicable as clinical alternatives of direct LDL-C measurement in pediatric patients given 400 ≤ TG ≤ 799 mg/dL.

An improved method for estimating low LDL-C based on the enhanced Sampson-NIH equation

BACKGROUND

The accurate measurement of Low-density lipoprotein cholesterol (LDL-C) is critical in the decision to utilize the new lipid-lowering therapies like PCSK9-inhibitors (PCSK9i) for high-risk cardiovascular disease patients that do not achieve sufficiently low LDL-C on statin therapy.

OBJECTIVE

To improve the estimation of low LDL-C by developing a new equation that includes apolipoprotein B (apoB) as an independent variable, along with the standard lipid panel test results.

METHODS

Using β-quantification (BQ) as the reference method, which was performed on a large dyslipidemic population (N = 24,406), the following enhanced Sampson-NIH equation (eS LDL-C) was developed by least-square regression analysis: [Formula: see text] RESULTS: The eS LDL-C equation was the most accurate equation for a broad range of LDL-C values based on regression related parameters and the mean absolute difference (mg/dL) from the BQ reference method (eS LDL-C: 4.51, Sampson-NIH equation [S LDL-C]: 6.07; extended Martin equation [eM LDL-C]: 6.64; Friedewald equation [F LDL-C]: 8.3). It also had the best area-under-the-curve accuracy score by Regression Error Characteristic plots for LDL-C < 100 mg/dL (eS LDL-C: 0.953; S LDL-C: 0.920; eM LDL-C: 0.915; F LDL-C: 0.874) and was the best equation for categorizing patients as being below or above the 70 mg/dL LDL-C treatment threshold for adding new lipid-lowering drugs by kappa score analysis when compared to BQ LDL-C for TG < 800 mg/dL (eS LDL-C: 0.870 (0.853-0.887); S LDL-C:0.763 (0.749-0.776); eM LDL-C:0.706 (0.690-0.722); F LDL-C:0.687 (0.672-0.701). Approximately a third of patients with an F LDL-C < 70 mg/dL had falsely low test results, but about 80% were correctly reclassified as higher (≥ 70 mg/dL) by the eS LDL-C equation, making them potentially eligible for PCSK9i treatment. The M LDL-C and S LDL-C equations had less false low results below 70 mg/dL than the F LDL-C equation but reclassification by the eS LDL-C equation still also increased the net number of patients correctly classified.

CONCLUSIONS

The use of the eS LDL-C equation as a confirmatory test improves the identification of high-risk cardiovascular disease patients, who could benefit from new lipid-lowering therapies but have falsely low LDL-C, as determined by the standard LDL-C equations used in current practice.

Performance of the enhanced Sampson-NIH equation for VLDL-C and LDL-C in a population with familial combined hyperlipidemia

INTRODUCTION

Low-density cholesterol (LDL-C) has long been estimated by the Friedewald formula (F-LDL-C); however, this method underestimates LDL-C in patients with hypertriglyceridemia (HTG) or low LDL-C levels. The Martin (M-LDL-C) and Sampson (S-LDL-C) formulas partially resolve these limitations. Recently, Sampson et al. developed a new equation (eS-VLDL-C) that includes ApoB. This new equation could be particularly useful in FCHL, which is characterized by the predominance of triglyceride-rich VLDL and a discordance between LDL-C and ApoB.

METHODS

Very low-density lipoproteins (VLDL-C) was measured in 336 patients with FCHL by sequential ultracentrifugation. LDL-C was estimated by subtracting VLDL-C, estimated by the different equations, from non-HDL cholesterol. Spearman correlations, R2, mean squared error (RMSE), and bias were used to compare the accuracy of the different equations. Concordance of the estimated LDL-C values with LDL-C thresholds and ApoB was also assessed by their kappa coefficients and ROC analysis.

RESULTS

Overall population had a mean age of 47 years, and 61.5% were women. 19.5% had type 2 diabetes, hypertension was present in 20.8%, and only 12.2% were on statin treatment. Both S-LDL-C and eS-LDL-C performed similarly, and better than M-LDL-C and F-LDL-C. In Bland-Altman analysis, eS-LDL-C showed the lowest bias, better performance in HTG, and better concordance with LDL-C treatment goals compared to other formulas (e.g. ρ: 0.87, 95% CI 0.84-0.89).

CONCLUSIONS

LDL-S and LDL-eS equations estimate the concentration of LDL-C with greater accuracy than other formulas. The LDL-eS has best performance in estimating LDL-C with lower RMSE than other formulas.

Reducing Lipid Panel Error Allowances to Improve the Accuracy of Cardiovascular Risk Stratification

BACKGROUND

The standard lipid panel forms the backbone of atherosclerotic cardiovascular disease risk assessment. Suboptimal analytical performance, along with biological variability, could lead to erroneous risk assessment and management decisions. The current National Cholesterol Education Program (NCEP) performance recommendations have remained unchanged for almost 3 decades despite improvements in assay technology. We investigated the potential extent of risk misclassification when the current recommendations are met and explored the impact of improving analytical performance goals.

METHODS

We extracted lipid panel data for 8506 individuals from the NHANES database and used these to classify subjects into 4 risk groups as recommended by the 2018 US Multisociety guidelines. Analytical bias and imprecision, at the allowable limits, as well as biological variability, were introduced to the measured values to determine the impact on misclassification. Bias and imprecision were systematically reduced to determine the degree of improvement that may be achieved.

RESULTS

Using the current performance recommendations, up to 10% of individuals were misclassified into a different risk group. Improving proportional bias by 1%, and fixing imprecision to 3% across all assays reduced misclassifications by up to 10%. The effect of biological variability can be reduced by taking the average of serial sample measurements.

CONCLUSIONS

The current NCEP recommendations for analytical performance of lipid panel assays allow for an unacceptable degree of misclassification, leading to possible mismanagement of cardiovascular disease risk. Iteratively reducing allowable error can improve this.

Accuracy and Clinical Impact of Estimating Low-Density Lipoprotein-Cholesterol at High and Low Levels by Different Equations

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the β-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) < 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG > 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (<70 mg/dL) and high (>190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.

Comparison of the Friedewald Equation with Martin and Sampson Equations for Estimating LDL Cholesterol in Hypertriglyceridemic Adults

Low density lipoprotein cholesterol (LDL-C) is traditionally calculated using the Friedewald (LDL-F) equation. New equations by Martin (LDL-M) and Sampson (LDL-S) have improved accuracy relative to LDL-F for samples with high triglycerides (TG) or low LDL-C. However, most labs still rely on LDL-F and few studies have examined the accuracy and impact of contemporary LDL-C equations applied to a retrospective dataset. 934 lipid panels with a concurrent direct enzymatic LDL-C (dLDL-C) result were extracted from the laboratory information system. LDL-F, LDL-M, and LDL-S were calculated and the accuracy of each equation determined in a predominantly hypertriglyceridemic population. The impact of implementing each equation was compared by analyzing the LDL-C treatment group miscategorization rate relative to dLDL-C. The slope for the LDL-F, LDL-M and LDL-S were 0.59, 0.78, and 0.94, relative to dLDL-C. The three equations performed comparably for samples with TG <4.52 mmol/L (<400 mg/dL). The LDL-C treatment group miscategorization rate was 48.6% for LDL-F, 28.8% for LDL-M and 37.2% for LDL-S in specimens with TG ≥4.52 mmol/L (≥400 mg/dL) (n=817). LDL-S underestimated treatment group category (31.3%, 95% CI 17.2-22.4) relative to LDL-M (9.0%, 4.39-7.41, P<0.001). 5.9% of samples were overestimated for treatment group category by LDL-S vs. 19.8% for LDL-M (P=0.1883). LDL-M and LDL-S demonstrate reduced bias with a dLDL-C method compared to LDL-F in samples with TG ≥4.52 mmol/L (≥400 mg/dL). LDL-M reduces LDL-C treatment group miscategorization rate leading to fewer underestimations of risk overall compared to LDL-S; however, neither may be sufficiently accurate to report LDL-C in patients with TG ≥4.52 mmol/L (≥400 mg/dL).

Identification of Dysbetalipoproteinemia by an Enhanced Sampson-NIH Equation for Very Low-Density Lipoprotein-Cholesterol

Dysbetalipoproteinemia (hyperlipoproteinemia type III, HLP3) is a genetic disorder that results in the accumulation of cholesterol on highly atherogenic remnant particles. Traditionally, the diagnosis of HLP3 depended upon lipoprotein gel electrophoresis or density gradient ultracentrifugation. Because these two methods are not performed by most clinical laboratories, we describe here two new equations for estimating the cholesterol content of VLDL (VLDL-C), which can then be used for the diagnosis of HLP3. Using results from the beta-quantification (BQ) reference method on a large cohort of dyslipidemic patients (N = 24,713), we identified 115 patients with HLP3 based on having a VLDL-C to plasma TG ratio greater than 0.3 and plasma TG between 150 and 1,000 mg/dl. Next, we developed two new methods for identifying HLP3 and compared them to BQ and a previously described dual lipid apoB ratio method. The first method uses results from the standard lipid panel and the Sampson-NIH equation 1 for estimating VLDL-C (S-VLDL-C), which is then divided by plasma TG to calculate the VLDL-C/TG ratio. The second method is similar, but the Sampson-NIH equation 1 is modified or enhanced (eS-VLDL-C) by including apoB as an independent variable for predicting VLDL-C. At a cut-point of 0.194, the first method showed a modest ability for identifying HLP3 (sensitivity = 73.9%; specificity = 82.6%; and area under the curve (AUC) = 0.8685) but was comparable to the existing dual lipid apoB ratio method. The second method based on eS-VLDL-C showed much better sensitivity (96.5%) and specificity (94.5%) at a cut-point of 0.209. It also had an excellent AUC score of 0.9912 and was superior to the two other methods in test classification. In summary, we describe two new methods for the diagnosis of HLP3. The first one just utilizes the results of the standard lipid panel and the Sampson-NIH equation 1 for estimating (VLDL-C) (S-VLDL-C) and can potentially be used as a screening test. The second method (eS-VLDL-C), in which the Sampson-NIH equation 1 is modified to include apoB, is nearly as accurate as the BQ reference method. Because apoB is widely available at most clinical laboratories, the second method should improve both the accessibility and the accuracy of the HLP3 diagnosis.

LDL-C calculated by Friedewald, Martin-Hopkins, or NIH Equation 2 versus beta-quantification: pooled alirocumab trials

Accurate assessment of LDL-C levels is important, as they are often used for treatment recommendations. For many years, plasma LDL-C levels were calculated using the Friedewald equation, but there are limitations to this method compared with direct measurement via beta-quantification (BQ). Here we assessed differences between the Friedewald, Martin-Hopkins, and NIH Equation 2 methods of calculating LDL-C and the "gold standard" BQ method using pooled Phase 3 data with alirocumab (a PCSK9 inhibitor). All randomized patients were included irrespective of treatment arm (n = 6122). We compared pairs of LDL-C values (n=17,077) determined by each equation and BQ. We found that BQ-derived LDL-C values ranged from 1 to 397 mg/dL (mean 90.68 mg/dL). There were strong correlations between Friedewald-, Martin-Hopkins-, and NIH Equation 2-calculated LDL-C with BQ-determined LDL-C values (Pearson's correlation coefficient = 0.985, 0.981, and 0.985, respectively). Importantly, for BQ-derived LDL-C values ≥70 mg/dL, only 3.2%, 1.4%, and 1.8% of Friedewald-, Martin-Hopkins-, and NIH Equation 2-calculated values were <70 mg/dL, respectively. When TG levels were <150 mg/dL, differences between calculated and BQ-derived LDL-C values were minimal, regardless of LDL-C level (<40, <55 or <70 mg/dL). However, when TG levels were >150 mg/dL, NIH Equation 2 provided greater accuracy versus Friedewald or Martin-Hopkins. When TG were >250 mg/dL, inaccuracies were seen with all three methods, although NIH Equation 2 remained the most accurate. In conclusion, LDL-C calculated by any of the three methods can guide treatment decisions in the large majority of patients, including those treated with PCSK9 inhibitors.

Association of baseline as well as change in lipid levels with the risk of cardiovascular diseases and all-cause deaths

High baseline atherogenic lipid level has been an established risk factor for the risk of cardiovascular events. Evidence concerning the role of lipid changes in cardiovascular and death risks are inconclusive. A cohort study was conducted based on the Taiwanese Survey on Hypertension, Hyperglycemia, and Hyperlipidemia (n = 4072, mean 44.8 years, 53.5% women) assessing lipid levels of the participants repeatedly measured in 2002 and 2007. Combined baseline and changes in lipid levels were classified into four groups-stable or decreasing lipid changes and increasing lipid changes with low- and high-risk baseline lipid levels. Developing cardiovascular events (n = 225) and all-cause deaths (n = 345) were ascertained during a median follow-up of 13.3 years. Participants with increasing and higher total cholesterol level were more likely to develop cardiovascular risks. Similar patterns for cardiovascular events were observed across other lipid profile changes. However, participants with increasing total cholesterol, LDL-C, and non-high-density lipoprotein cholesterol (non-HDL-C) levels were more likely to be at a lower risk for all-cause deaths. Baseline and changes in total cholesterol, triglycerides, and LDL-C levels were positively associated with the risk of cardiovascular diseases, whereas baseline and changes in total cholesterol and LDL-C and non-HDL-C levels were inversely associated with all-cause deaths.

Association of body mass index with all-cause mortality in the elderly population of Taiwan: A prospective cohort study

BACKGROUND AND AIMS

The nutritional status of the elderly is different from that of young people. Body composition changes as people age, for example, fat mass increases, muscle mass decreases, and body fat distribution is changed. We aimed to investigate the association of body mass index (BMI) with cause-specific mortality in the elderly population.

METHODS AND RESULTS

The data of annual health examination for the older citizens (≥65 years old) from 2006 to 2011 in Taipei City Hospital were used. Information on baseline demographics, lifestyle behaviors, medical, and drug usage were collected by a self-administered questionnaire. Cause-specific mortality was ascertained from the National Registration of Death. Individuals were followed up until death or December 31, 2012, whichever was earlier. Univariable and multivariable Cox proportional hazard analyses were applied to investigate the association between BMI and all-cause mortality. Among 81,221 older people included in the analysis, 42,602 (52.45%) were men. The mean age was 73.85 ± 6.32 years. Among the 81,221 participants, 3398 (4.18%) were underweight, 36,476 (44.91%) were normal weight, 25,708 (31.65%) were overweight, and 15,639 (19.25%) were obese. Those in the BMI category 27 ≤ BMI<28 kg/m² had the lowest all-cause mortality risk. The BMI of lowest cause-specific mortality was between 27 kg/m² and 28 kg/m² in infection mortality, between 28 kg/m² and 29 kg/m² in circulation mortality, between 29 kg/m² and 30 kg/m² in respiratory mortality, and between 31 kg/m² and 32 kg/m² in cancer mortality.

CONCLUSIONS

The current study found a J-shaped relation between BMI and cause-specific mortality in the elderly population of Taiwan.

Non-HDL-C/TG ratio indicates significant underestimation of calculated low-density lipoprotein cholesterol (LDL-C) better than TG level: a study on the reliability of mathematical formulas used for LDL-C estimation

OBJECTIVES

Low-density lipoprotein cholesterol (LDL-C) is the main laboratory parameter used for the management of cardiovascular disease. The aim of this study was to compare measured LDL-C with LDL-C as calculated by the Friedewald, Martin/Hopkins, Vujovic, and Sampson formulas with regard to triglyceride (TG), LDL-C and non-high-density lipoprotein cholesterol (non-HDL-C)/TG ratio.

METHODS

The 1,209 calculated LDL-C results were compared with LDL-C measured using ultracentrifugation-precipitation (first study) and direct (second study) methods. The Passing-Bablok regression was applied to compare the methods. The percentage difference between calculated and measured LDL-C (total error) and the number of results exceeding the total error goal of 12% were established.

RESULTS

There was good correlation between the measurement and calculation methods (r 0.962-0.985). The median total error ranged from -2.7%/+1.4% (first/second study) for Vujovic formula to -6.7%/-4.3% for Friedewald formula. The numbers of underestimated results exceeding the total error goal of 12% were 67 (Vujovic), 134 (Martin/Hopkins), 157 (Samspon), and 239 (Friedewald). Less than 7% of those results were obtained for samples with TG >4.5 mmol/L. From 57% (Martin/Hopkins) to 81% (Vujovic) of underestimated results were obtained for samples with a non-HDL-C/TG ratio of <2.4.

CONCLUSIONS

The Martin/Hopkins, Vujovic and Sampson formulas appear to be more accurate than the Friedewald formula. To minimize the number of significantly underestimated LDL-C results, we propose the implementation of risk categories according to non-HDL-C/TG ratio and suggest that for samples with a non-HDL-C/TG ratio of <1.2, the LDL-C level should not be calculated but measured independently from TG level.

Association of exercise with all-cause mortality in older Taipei residents

BACKGROUND

Human life expectancy has increased rapidly in recent decades. Regular exercise can promote health, but the effect of exercise on mortality is not yet well understood.

OBJECTIVE

To investigate the association of exercise with mortality in the older people.

METHODS

We used data from annual health check-ups of the older citizens of Taipei in 2006. Participants were interviewed by trained nurses using a structured questionnaire to collect data on demographics and lifestyle behaviours. Overnight fasting blood was collected for measuring blood glucose, liver and renal function and lipid profiles. Exercise frequency was categorised into no exercise, 1-2 times in a week and more than 3-5 times in a week. All-cause mortality was ascertained from the National Registration of Death. All participants were followed up until death or December 312012, whichever came first. Kaplan-Meier curves and Cox proportional hazard analysis were used to investigate the association between exercise and all-cause mortality.

RESULTS

In total, 42,047 older people were analysed; 22,838 (54.32%) were male and with a mean (SD) age of 74.58 (6.32) years. Kaplan-Meier curves of all-cause mortality stratified by exercise frequency demonstrated significant findings (Log-rank P < 0.01). Multivariate Cox regression analysis showed that older people with higher exercise levels had a significantly decreased risk of mortality (moderate exercise HR = 0.74, 95% CI: 0.68-0.81, high exercise HR = 0.65, 95% CI: 0.59-0.70) after adjusting for potential confounders, with a significant trend (P for trend<0.01).

CONCLUSIONS

Older people with increased exercise levels had a significantly decreased risk of all-cause mortality.

Repeatability and reproducibility of lipoprotein particle profile measurements in plasma samples by ultracentrifugation

Background

Characterization of lipoprotein particle profiles (LPPs) (including main classes and subclasses) by means of ultracentrifugation (UC) is highly requested given its clinical potential. However, rapid methods are required to replace the very labor-intensive UC method and one solution is to calibrate rapid nuclear magnetic resonance (NMR)-based prediction models, but the reliability of the UC-response method required for the NMR calibration has been largely overlooked.

Methods

This study provides a comprehensive repeatability and reproducibility study of various UC-based lipid measurements (cholesterol, triglycerides [TGs], free cholesterol, phospholipids, apolipoprotein [apo]A1 and apoB) in different main classes and subclasses of 25 duplicated fresh plasma samples and of 42 quality control (QC) frozen pooled plasma samples of healthy individuals.

Results

Cholesterol, apoA1 and apoB measurements were very repeatable in all classes (intraclass correlation coefficient [ICC]: 92.93%–99.54%). Free cholesterol and phospholipid concentrations in main classes and subclasses and TG concentrations in high-density lipoproteins (HDL), HDL subclasses and low-density lipoproteins (LDL) subclasses, showed worse repeatability (ICC: 19.21%–99.08%) attributable to low concentrations, variability introduced during UC and assay limitations. On frozen QC samples, the reproducibility of cholesterol, apoA1 and apoB concentrations was found to be better than for the free cholesterol, phospholipids and TGs concentrations.

Conclusions

This study shows that for LPPs measurements near or below the limit of detection (LOD) in some of the subclasses, as well as the use of frozen samples, results in worsened repeatability and reproducibility. Furthermore, we show that the analytical assay coupled to UC for free cholesterol and phospholipids have different repeatability and reproducibility. All of this needs to be taken into account when calibrating future NMR-based models.

Non-HDL-cholesterol and apolipoprotein B compared with LDL-cholesterol in atherosclerotic cardiovascular disease risk assessment

Low density lipoprotein (LDL) is the predominant atherogenic lipoprotein particle in the circulation. Conventionally, a fasting lipid profile has been used for atherosclerotic cardiovascular disease (ASCVD) risk assessment. A non-fasting sample is now regarded as a suitable alternative to a fasting sample. In routine clinical practice, the Friedewald equation is used to estimate LDL-cholesterol, but it has limitations. Commercially available direct measures of LDL-cholesterol are not standardised. LDL-cholesterol is a well-established risk factor for ASCVD, being the primary therapeutic target in both primary and secondary prevention. Non-high-density lipoprotein (HDL)-cholesterol is a measure of the cholesterol content in the atherogenic lipoproteins, but it does not reflect the particle number. Non-HDL-cholesterol has the advantage over LDL-cholesterol of including remnant cholesterol and being independent of triglyceride variability, but it is compromised by the non-specificity bias of direct HDL-cholesterol methods used in the calculation. Apolipoprotein (apo) B, the major structural protein in very low-density lipoprotein, intermediate density lipoprotein, LDL and lipoprotein (a), is a measure of the number of atherogenic lipoproteins. ApoB methods are standardised, but the assay comes at an additional, albeit relatively low cost. Non-HDL-cholesterol and apoB are more accurate measures than LDL-cholesterol in hypertriglyceridaemic individuals, non-fasting samples, and in those with very-low LDL-cholesterol concentrations. Accumulating evidence suggests that non-HDL-cholesterol and apoB are superior to LDL-cholesterol in predicting ASCVD risk, and both have been designated as secondary targets in some treatment guidelines. We review the measurement, potential role, utility and current status of non-HDL-cholesterol and apoB when compared with LDL-cholesterol in ASCVD risk assessment.

Standardization of laboratory and lipid profile evaluation: A call for action with a special focus in 2016 ESC/EAS dyslipidaemia guidelines - Full report

Even with the improvement in lifestyle interventions, a better control of cardiovascular (CV) risk factors, and improvements in CV outcomes, cardiovascular disease (CVD) still persists as the leading cause of morbidity and mortality in Portugal and Europe. Atherogenic dyslipidaemias, namely hypercholesterolaemia, have a crucial and causal role in the development of atherosclerotic CVD. The clinical approach of a patient with dyslipidaemia involves a watchful diagnosis, sustained in lipid and lipoprotein laboratory procedures, which must be harmonized and standardized. Standardization of lipid test results and reports, incorporating the total CV risk and the respective target and goals of treatment approach, guarantees that clinical guidelines and good clinical practices are followed and respected, increasing the reliability of lipid disorders screening, producing more accurate diagnoses and CV risk stratification, and improving the CV prevention and the achievement the desirable treatment goals.

Validity of a Novel Method for Estimating Low-Density Lipoprotein Cholesterol Levels in Cardiovascular Disease Patients Treated with Statins

AIM

The Friedewald equation is the standard method for estimating low-density lipoprotein cholesterol (LDL-C) levels [LDL-C(F)] and fixes the ratio of triglyceride (TG) to very LDL-C at 5. However, this has been reported to underestimate LDL-C, particularly in patients with LDL-C ＜70 mg/dL. A novel method for LDL-C estimation [LDL-C(M)] using an adjustable factor instead of a fixed value of 5 has recently been proposed. The purpose of this study was to validate LDL-C(M) in Japanese patients with cardiovascular disease (CVD) treated with statins.

METHODS

In 385 consecutive CVD patients treated with statins, LDL-C(M) and LDL-C(F) levels were compared with directly measured LDL-C [LDL-C(D)].

RESULTS

Mean LDL-C(D), LDL-C(F), and LDL-C(M) were 81.7±25.5, 76.4±24.6, and 79.9±24.5 mg/dL, respectively. In all patients, both LDL-C(F) and LDL-C(M) were significantly correlated with LDL-C(D) [LDL-C(F) vs. LDL-C(D): R=0.974, p＜0.001; LDL-C(M) vs. LDL-C(D): R=0.987, p＜0.001]. In patients with LDL-C(D) ＜70 mg/dL, LDL-C(M) showed a better correlation with LDLC(D) compared with LDL-C(F) [LDL-C(M) vs. LDL-C(D): R=0.935, p＜0.001; LDL-C(F) vs. LDLC(D): R=0.868, p＜0.001]. In contrast, the correlation of LDL-C(D) with LDL-C(M) or LDL-C(F) was similar in patients with LDL-C(D) ≥70 mg/dL.

CONCLUSIONS

In Japanese patients with CVD treated with statins, LDL-C level estimated by this novel method might be more accurate than those estimated using the Friedewald equation for LDL-C levels ＜70 mg/dL.

Update on the laboratory investigation of dyslipidemias

The role of the clinical laboratory is evolving to provide more information to clinicians to assess cardiovascular disease (CVD) risk and target therapy more effectively. Current routine methods to measure LDL-cholesterol (LDL-C), the Friedewald calculation, ultracentrifugation, electrophoresis and homogeneous direct methods have established limitations. Studies suggest that LDL and HDL size or particle concentration are alternative methods to predict future CVD risk. At this time there is no consensus role for lipoprotein particle or subclasses in CVD risk assessment. LDL and HDL particle concentration are measured by several methods, namely gradient gel electrophoresis, ultracentrifugation-vertical auto profile, nuclear magnetic resonance and ion mobility. It has been suggested that HDL functional assays may be better predictors of CVD risk. To assess the issue of lipoprotein subclasses/particles and HDL function as potential CVD risk markers robust, simple, validated analytical methods are required. In patients with small dense LDL particles, even a perfect measure of LDL-C will not reflect LDL particle concentration. Non-HDL-C is an alternative measurement and includes VLDL and CM remnant cholesterol and LDL-C. However, apolipoprotein B measurement may more accurately reflect LDL particle numbers. Non-fasting lipid measurements have many practical advantages. Defining thresholds for treatment with new measurements of CVD risk remain a challenge. In families with genetic variants, ApoCIII and lipoprotein (a) may be additional risk factors. Recognition of familial causes of dyslipidemias and diagnosis in childhood will result in early treatment. This review discusses the limitations in current laboratory technologies to predict CVD risk and reviews the evidence for emergent approaches using newer biomarkers in clinical practice.

Lipid Biomarkers for Risk Assessment in Acute Coronary Syndromes

PURPOSE OF REVIEW

The objective of this review was to summarize evidence gathered for the prognostic value of routine and novel blood lipids and lipoproteins measured in patients with acute coronary syndromes (ACS).

RECENT FINDINGS

Data supports clear association with risk and actionable value for non-high-density lipoprotein (Non-HDL) cholesterol and plasma ceramides in a setting of ACS. The prognostic value and clinical actionability of apolipoprotein B (apoB) and lipoprotein(a) [Lp(a)] in ACS have not been thoroughly tested, while the data for omega-3 fatty acids and oxidized low-density lipoprotein (Ox-LDL) are either untested or more varied. Measuring basic lipids, which should include Non-HDL cholesterol, at the time of presentation for ACS is guideline mandated. Plasma ceramides also provide useful information to guide both treatment decisions and follow-up. Additional studies targeting ACS patients are necessary for apoB, Lp(a), omega-3 fatty acids, and Ox-LDL.

Performance of Calculated and Directly Measured Low-Density Lipoprotein Cholesterol in a Pediatric Population

OBJECTIVES

An assessment of methods for the accurate measurement of low-density lipoprotein cholesterol (LDL-C) at decreased concentrations has not yet been carried out. We evaluated the performance of the Friedewald equation, a direct enzymatic assay, and a novel equation for determining LDL-C levels in a pediatric population with elevated triglycerides and reduced LDL-C levels.

METHODS

LDL-C concentrations of 127 pediatric patients were determined by the Friedewald equation, a direct enzymatic assay, and a novel equation. The bias of each approach was assessed at selected LDL-C cutoffs and after stratifying samples by triglyceride content. The concordance of each approach, relative to the reference method, was determined at LDL-C cut-points of less than 70, 70 to 99, and 100 to 129 mg/dL.

RESULTS

The Friedewald equation substantially underestimated pediatric LDL-C concentrations below 100 mg/dL in the presence of elevated triglycerides. The Ortho Clinical Diagnostics (Raritan, NJ) direct LDL assay was positively biased at low LDL-C levels. The novel equation most effectively reduced the bias of the Friedewald equation at all LDL-C concentrations and increased the concordance of sample classification to the reference method.

CONCLUSIONS

The novel equation should be used for accurate measurement of pediatric LDL-C when the concentration is below 100 mg/dL in the presence of elevated triglycerides (150-399 mg/dL).

Accuracy of low-density lipoprotein cholesterol estimation at very low levels

BACKGROUND

As the approach to low-density lipoprotein cholesterol (LDL-C) lowering becomes increasingly intensive, accurate assessment of LDL-C at very low levels warrants closer attention in individualized clinical efficacy and safety evaluation. We aimed to assess the accuracy of LDL-C estimation at very low levels by the Friedewald equation, the de facto clinical standard, and compare its accuracy with a novel, big data-derived LDL-C estimate.

METHODS

In 191,333 individuals with Friedewald LDL-C < 70 mg/dL, we compared the accuracy of Friedewald and novel LDL-C values in relation to direct measurements by Vertical Auto Profile ultracentrifugation. We examined differences (estimate minus ultracentrifugation) and classification according to levels initiating additional safety precautions per clinical practice guidelines.

RESULTS

Friedewald values were less than ultracentrifugation measurement, with a median difference (25th to 75th percentile) of -2.4 (-7.4 to 0.6) at 50-69 mg/dL, -7.0 (-16.2 to -1.2) at 25-39 mg/dL, and -29.0 (-37.4 to -19.6) at < 15 mg/dL. The respective values by novel estimation were -0.1 (-1.5 to 1.3), -1.1 (-2.5 to 0.3), and -2.7 (-4.9 to 0.0) mg/dL. Among those with Friedewald LDL-C < 15, 15 to < 25, and 25 to < 40 mg/dL, the classification was discordantly low in 94.9%, 82.6%, and 59.9% of individuals as compared with 48.3%, 42.4%, and 22.4% by novel estimation.

CONCLUSIONS

Estimation of even lower LDL-C values (by Friedewald and novel methods) is even more inaccurate. More often than not, a Friedewald value < 40 mg/dL is underestimated, which translates into unnecessary safety alarms that could be reduced in half by estimation using our novel method.

Should apolipoprotein B replace LDL cholesterol as therapeutic targets are lowered?

PURPOSE OF REVIEW

The success of LDL cholesterol (LDL-C) as a predictor of atherosclerotic cardiovascular disease and a therapeutic target is indisputable. Apolipoprotein B (apoB) is a more contemporary and physiologically relevant measure of atherogenic lipoproteins. This report summarizes recent comparisons of apoB and LDL-C as biomarkers of cardiovascular risk.

RECENT FINDINGS

Multiple recent reports have found that LDL-C methods perform poorly at low concentrations (<70 mg/dl). Several meta-analyses from randomized controlled trials and large prospective observational studies have found that apoB and LDL-C provide equivalent information on risk of cardiovascular disease. More innovative analyses have asserted that apoB is a superior indicator of actual risk when apoB and LDL-C disagree.

SUMMARY

ApoB is more analytically robust and standardized biomarker than LDL-C. Large population studies have found that apoB is at worst clinically equivalent to LDL-C and likely superior when disagreement exists. Realistically, many obstacles prevent the wide spread adoption of apoB and for now providers and their patients must weigh the costs and benefits of apoB.

My Approach to the Patient With Familial Hypercholesterolemia

Familial hypercholesterolemia (FH), a relatively common Mendelian genetic disorder, is associated with a dramatically increased lifetime risk of premature atherosclerotic cardiovascular disease due to elevated plasma low-density lipoprotein cholesterol (LDL-C) levels. The diagnosis of FH is based on clinical presentation or genetic testing. Early identification of patients with FH is of great public health importance because preventive strategies can lower the absolute lifetime cardiovascular risk and screening can detect affected relatives. However, low awareness, detection, and control of FH pose hurdles in the prevention of FH-related cardiovascular events. Of the estimated 0.65 million to 1 million patients with FH in the United States, less than 10% carry a diagnosis of FH. Based on registry data, a substantial proportion of patients with FH are receiving no or inadequate lipid-lowering therapy. Statins remain the mainstay of treatment for patients with FH. Lipoprotein apheresis and newly approved lipid-lowering drugs are valuable adjuncts to statin therapy, particularly when the LDL-C-lowering response is suboptimal. Monoclonal antibodies targeting proprotein convertase subtilisin/kexin type 9 provide an additional approximately 60% lowering of LDL-C levels and are approved for use in patients with FH. For homozygous FH, 2 new drugs that work independent of the LDL receptor pathway are available: an apolipoprotein B antisense oligonucleotide (mipomersen) and a microsomal triglyceride transfer protein inhibitor (lomitapide). This review attempts to critically examine the available data to provide a summary of the current evidence for managing patients with FH, including screening, diagnosis, treatment, and surveillance.