A new phenotypic classification system for dyslipidemias based on the standard lipid panel

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.

Low-density lipoprotein cholesterol goal attainment in patients with clinical evidence of familial hypercholesterolemia and elevated Lp(a)

BACKGROUND

Although potent lipid-lowering therapies are available, patients commonly fall short of recommended low-density lipoprotein cholesterol (LDL-C) levels. The aim of this study was to examine the relationship between familial hypercholesterolemia (FH) and elevated lipoprotein(a) [Lp(a)] and LDL-C goal attainment, as well as the prevalence and severity of coronary artery disease (CAD). Moreover, we characterized patients failing to meet recommended LDL-C goals.

METHODS

We performed a cross-sectional analysis in a cohort of patients undergoing cardiac catheterization. Clinical FH was determined by the Dutch Clinical Lipid Network Score, and Lp(a) ≥ 50 mg/dL (≈ 107 nmol/L) was considered elevated.

RESULTS

A total of 838 participants were included. Overall, the prevalence of CAD was 72%, and 62% received lipid-lowering treatment. The prevalence of clinical FH (probable and definite FH) was 4%, and 19% had elevated Lp(a) levels. With 35%, LDL-C goal attainment was generally poor. Among the participants with clinical FH, none reached their LDL-C target. Among patients with elevated Lp(a), LDL-C target achievement was only 28%. The prevalence and severity of CAD were higher in participants with clinical FH (86% prevalence) and elevated Lp(a) (80% prevalence).

CONCLUSION

Most participants failed to meet their individual LDL-C goals according to the ESC 2016 and 2019 guidelines. In particular, high-risk patients with clinical FH or elevated Lp(a) rarely met their target for LDL-C. The identification of these patients and more intense treatment approaches are crucial for the improvement of CAD primary and secondary prevention.

Diagnosis of remnant hyperlipidaemia

PURPOSE OF REVIEW

In recent years, there has been interest for the development of simplified diagnosis algorithms of dysbetalipoproteinemia (DBL) in order to avoid the complex testing associated with the Fredrickson criteria (reference method). The purpose of this review is to present recent advances in the field of DBL with a focus on screening and diagnosis.

RECENT FINDINGS

Recently, two different multi-step algorithms for the diagnosis of DBL have been published and their performance has been compared to the Fredrickson criteria. Furthermore, a recent large study demonstrated that only a minority (38%) of DBL patients are carriers of the E2/E2 genotype and that these individuals presented a more severe phenotype.

SUMMARY

The current literature supports the fact that the DBL phenotype is more heterogeneous and complex than previously thought. Indeed, DBL patients can present with either mild or more severe phenotypes that can be distinguished as multifactorial remnant cholesterol disease and genetic apolipoprotein B deficiency. Measurement of apolipoprotein B as well as APOE gene testing are both essential elements in the diagnosis of DBL.

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.

Approach to the Patient With Moderate Hypertriglyceridemia

Hypertriglyceridemia is a common lipid disorder encountered in clinical practice. Plasma triglycerides are a marker for the concentration of triglycerides carried in chylomicrons and very low-density lipoprotein particles. A fasting triglyceride level <150 mg/dL is accepted widely as the upper limit of normal range. Guidelines for hypertriglyceridemia are variable without a global consensus on classification and goals for triglyceride levels. A general classification of hypertriglyceridemia is mild < 200 mg/dL, moderate = 200 to 500 mg/dL, moderate to severe = 500 to 1000 mg/dL, and severe > 1000 mg/dL. Because moderate hypertriglyceridemia does increase atherosclerotic cardiovascular disease risk, it is important to determine the underlying etiology to guide appropriate and timely management. This article provides stepwise recommendations on the diagnosis and management of moderate hypertriglyceridemia, based on 3 common scenarios encountered in clinical practice. Initial steps in management include evaluating for secondary contributors, especially diabetes mellitus. Based on patient characteristics, appropriate management decisions include lifestyle adjustments aimed at weight loss and decreasing alcohol consumption and use of statin and nonstatin therapies.