Low-density Lipoprotein Cholesterol Estimation Research Articles

Comparison of a Novel Method vs the Friedewald Equation for Estimating Low-Density Lipoprotein Cholesterol Levels From the Standard Lipid Profile

In clinical and research settings worldwide, low-density lipoprotein cholesterol (LDL-C) is typically estimated using the Friedewald equation. This equation assumes a fixed factor of 5 for the ratio of triglycerides to very low-density lipoprotein cholesterol (TG:VLDL-C); however, the actual TG:VLDL-C ratio varies significantly across the range of triglyceride and cholesterol levels. To derive and validate a more accurate method for LDL-C estimation from the standard lipid profile using an adjustable factor for the TG:VLDL-C ratio. We used a convenience sample of consecutive clinical lipid profiles obtained from 2009 through 2011 from 1,350,908 children, adolescents, and adults in the United States. Cholesterol concentrations were directly measured after vertical spin density-gradient ultracentrifugation, and triglycerides were directly measured. Lipid distributions closely matched the population-based National Health and Nutrition Examination Survey (NHANES). Samples were randomly assigned to derivation (n = 900,605) and validation (n = 450,303) data sets. Individual patient-level concordance in clinical practice guideline LDL-C risk classification using estimated vs directly measured LDL-C (LDL-CD). In the derivation data set, the median TG:VLDL-C was 5.2 (IQR, 4.5-6.0). The triglyceride and non-high-density lipoprotein cholesterol (HDL-C) levels explained 65% of the variance in the TG:VLDL-C ratio. Based on strata of triglyceride and non-HDL-C values, a 180-cell table of median TG:VLDL-C values was derived and applied in the validation data set to estimate the novel LDL-C (LDL-CN). For patients with triglycerides lower than 400 mg/dL, overall concordance in guideline risk classification with LDL-CD was 91.7% (95% CI, 91.6%-91.8%) for LDL-CN vs 85.4% (95% CI, 85.3%-85.5%) for Friedewald LDL-C (LDL-CF) (P < .001). The greatest improvement in concordance occurred in classifying LDL-C lower than 70 mg/dL, especially in patients with high triglyceride levels. In patients with an estimated LDL-C lower than 70 mg/dL, LDL-CD was also lower than 70 mg/dL in 94.3% (95% CI, 93.9%-94.7%) for LDL-CN vs 79.9% (95% CI, 79.3%-80.4%) for LDL-CF in samples with triglyceride levels of 100 to 149 mg/dL; 92.4% (95% CI, 91.7%-93.1%) for LDL-CN vs 61.3% (95% CI, 60.3%-62.3%) for LDL-CF in samples with triglyceride levels of 150 to 199 mg/dL; and 84.0% (95% CI, 82.9%-85.1%) for LDL-CN vs 40.3% (95% CI, 39.4%-41.3%) for LDL-CF in samples with triglyceride levels of 200 to 399 mg/dL (P < .001 for each comparison). A novel method to estimate LDL-C using an adjustable factor for the TG:VLDL-C ratio provided more accurate guideline risk classification than the Friedewald equation. These findings require external validation, as well as assessment of their clinical importance. The implementation of these findings into clinical practice would be straightforward and at virtually no cost. clinicaltrials.gov Identifier: NCT01698489.

Measurement of LDL-C after treatment with the CETP inhibitor anacetrapib

Estimation of low-density lipoprotein cholesterol (LDL-C) using the Friedewald (FR) formula is often inaccurate when triglycerides are elevated or VLDL particle composition is altered. We hypothesized that LDL-C estimation by the FR formula and other measurement methods might also be inaccurate in individuals treated with a cholesteryl ester transfer protein (CETP) inhibitor. An assay comparison study was conducted using pre and posttreatment serum samples from 280 of the 811 patients treated with the CETP inhibitor anacetrapib in the DEFINE study (determining the efficacy and tolerability of CETP inhibition with anacetrapib). After 24 weeks of treatment with anacetrapib, mean LDL-C values by FR formula, Roche direct method (RDM) and Genzyme direct method (GDM) deviated from that measured by the β-quantification (BQ) reference method by -12.2 ± 7.5, -10.2 ± 6.6, -10.8 ± 8.8 mg/dl, respectively. After treatment with anacetrapib, the FR formula and detergent-based direct methods provided lower LDL-C values than those obtained by the BQ reference method. The bias by the FR formula appeared to be due to an overestimation of VLDL-C by the TG/5 component of the formula. Evaluation of the clinical significance of these findings awaits comprehensive lipid and cardiovascular outcome data from ongoing Phase III clinical studies of anacetrapib.

Does LDL-C Estimation Using Anandaraja’s Formula Give a Better Agreement with Direct LDL-C Estimation than the Friedewald’s Formula?

Estimation of low density lipoprotein cholesterol (LDL-C) is crucial in management of coronary artery disease patients. Though a number of homogenous assays are available for estimation of LDL-C, use of calculated LDL-C by Friedewald's formula (FF) is common in Indian laboratories for logistic reasons. Recently Anandaraja and colleagues have derived a new formula for calculating LDL-C. This formula needs to be evaluated before it is extensively applied in diagnosis. We measured LDL-C by homogenous method (D-LDL-C) in 515 fasting samples. Friedewald's and Anandaraja's formulas were used for calculation of LDL-C (F-LDL-C and A-LDL-C, respectively). The mean LDL-C levels were 123.3±53.2, 112.4±50.2 and 109.2±49.8mg/dl for D-LDL-C, F-LDL-C and A-LDL-C, respectively. There was a statistically significant difference between the results (P>0.001) obtained by calculation formulas compared to the measured LDL-C. There was underestimation of LDL-C by 10.8 and 14mg/dl by Friedewald's and Anandaraja's formulas respectively. The Pearson's correlation between F-LDL-C and D-LDL-C was 0.931 and that between A-LDL-C and D-LDL-C was 0.930. Bland-Altman graphs showed a definite agreement between mean and differences of the calculation formulas and direct LDL-C with 95% of values lying with in ±2 SD limits. The mean percentage difference (calculated as {(Calculated LDL-C)-(D-LDL-C)}/D-LDL-C×100) for F-LDL-C was maximum (-11.6%) at HDL-C≥60mg/dl and TG levels of 200-300mg/dl (-10.4%) compared to D-LDL-C. A-LDL-C results gave highest mean percentage difference at total cholesterol concentrations <100mg/dl (-37.3%) and HDL-C<40mg/dl (-17.1%), respectively. The results of our study showed that FF is better in agreement with D-LDL-C than Anandaraja's formula for estimation of LDL-C by calculation though both lead to its underestimation.

Do we need a fasting lipid profile to assess cardiovascular risk?

How often do our patients fail to have lipid determinations because they feel unable to come for fasting blood drawing? We do not know their lipid status, and they become frustrated at not complying with the seemingly simple directions. There is, moreover, evidence that “patients on antidiabetic medications are at risk for developing hypoglycemia while fasting for laboratory testing [with] potential serious harm”.1 We should ask: Where does the “fasting” status requirement come from? Is it justifiable? Total and low-density lipoprotein cholesterol (LDL-C) levels are only minimally increased by recent food intake. LDL-C has a very long half-life (2–4 days) in circulation.2 The issue appears to be the clinical laboratory estimation of LDL-C from the Friedewald formula: LDL-C = total cholesterol − (high-density lipoprotein cholesterol [HDL-C] + very low-density lipoprotein cholesterol [VLDL-C]), where VLDL-C is calculated by dividing the serum triglyceride (TG) level by five. Triglycerides are primarily carried in VLDL particles, and normally composed VLDL particles have a triglyceride mass five times greater than that of cholesterol, so TG/5 should be a reasonable equation to calculate VLDL-C.3 As triglyceride levels do increase in the postprandial state, when using the Friedewald formula, fasting is required. Advice from medical professionals over the years has been more than confusing. Just try your favorite web engine and search for the answers. Virtually all websites that patients can access recommend “fasting” before blood sampling for a “reliable” lipid profile (see, for example, http://www.ask.com, http://www.answers.yahoo.com, http://www.drug3k.com, http://www.wiki.answers.com, http://www.lowercholesterolcenter.com, http://www.livestrong.com). As if the term “fasting” were not vague enough, various “experts” then advise abstaining from food intake anywhere between 8 and 12 h (see, for example, http://www.webmd.com, http://www.health.harvard.com, http://www.nhs.uk, http://www.heart.org, http://www.mayoclinic.org). What is the patient to do? And, what is the principal reason one needs to obtain the “reliable” lipid profile in the first place? The answer for this is clear: first, to assess the magnitude of risk for future cardiovascular events and thus help to drive subsequent specific therapeutic choices for that particular individual; and second, for those already on a therapeutic regimen, to determine whether the goals (i.e. specific lipid particle concentration targets) are being reached. The currently accepted approach is that plasma cholesterol and triglycerides should be measured periodically in adults to assess the risk of coronary heart disease. “Total serum cholesterol and serum HDL cholesterol are relatively unaffected by eating. That is one of the reasons why the calculation of non-HDL cholesterol is a particularly useful tool …”.4 An interesting recent study asked: Among patients with type 2 diabetes, does it matter when the blood sample for lipid determination was drawn in assessing the risk of future cardiovascular events?5 The authors studied 1337 participants without known cardiovascular disease and not using statins at baseline in the European Prospective Investigation into Cancer and Nutrition (EPIC) in the Netherlands and Germany, followed for a mean 8-year period. Cardiovascular events were tracked using registries and follow-up questionnaires. Lipid concentrations were assessed across four categories of postprandial time (0–2, 2–4, 4–6, and >6 h). None of the associations between the triglyceride or HDL-C level, or the total cholesterol:HDL-C ratio, and subsequent cardiovascular events, were dependent on postprandial time, suggesting that non-fasting blood lipid concentrations are as good in the assessment of cardiovascular risk and prediction of cardiovascular events as fasting levels. Indeed, the American Heart Association now recommends initial screening with determination of non-fasting triglyceride concentrations.6 Normal levels are defined as those <200 mg/dL, with those having higher non-fasting levels potentially requiring further, fasting, triglyceride determination. Let us hope that these latest publications lessen the stress we impose on our patients and lead us to recommend the less burdensome timing of blood tests for lipid profile: any time!

Letter by Lund et al Regarding Article, “Fasting Compared With Nonfasting Lipids and Apolipoproteins for Predicting Incident Cardiovascular Events”

To the Editor: We are delighted about the report from Mora et al showing a lack of predictive value for future cardiovascular disease (CVD) of nonfasting low-density lipoprotein cholesterol (LDL-C) contrasting with the well-known predictive value of fasting LDL-C.1 In our opinion, the applied methodology has some pitfalls: 1. Measurement by a direct assay (Genzyme or Roche) in frozen samples might not produce reliable LDL-C estimates compared with fresh samples. 2. The evidence for using direct LDL-C assays in nonfasting samples (fresh or frozen) with respect to the agreement with the method recommended by the Centers for Disease Control and Prevention for measurement of LDL-C (ie, the β quantification) is sparse. 3. In daily …

Effect of HMG CoA reductase inhibitors on low-density lipoprotein cholesterol and C-reactive protein: systematic review and meta-analysis

HMG CoA reductase inhibitors (statins) have been claimed to decrease C-reactive protein (CRP), independent of their effect on low-density lipoprotein cholesterol (LDL-C). We conducted a systematic review and meta-analysis to investigate whether a relationship between the average effect of statins on LDL-C and CRP exists. The literature search of the Medline and Cochrane databases between 1980 and August 2007 yielded 65 statin intervention studies with 94 treatment arms involving 16,260 patients reporting changes in both LDL-C and CRP. DATA EXTRACTION AND STATISTICAL METHOD: From each study relative changes in LDL-C and CRP were extracted. Random effects meta-analysis was used to obtain pooled summary estimates of the average study specific LDL-C and CRP reductions, in total and stratified by dose and type of statin. Weighted correlation analysis and metaregression analysis was used to investigate the relationship between the LDL-C and CRP changes adjusted for baseline values, type of statin and dose. Pooled summary estimates of statin-induced changes in LDL-C and CRP levels were -34.7% (95% CI: -37.7% to -31.8%) and -30.8% (95% CI: -39.4% to -22.3%), respectively. We found a positive correlation between the average LDL-C and CRP reduction (r = 0.49, p = 0.010) which increased when adjusting for pre-treatment concentrations (r = 0.79, p < 0.001). The effect of statins on CRP were strongly related to the changes in LDL-C and baseline concentrations, independent of the type and dose of statin used. Our meta-analysis shows a strong correlation between statin-induced reductions in LDL-C and CRP, which has not been evident from individual studies. Measuring CRP in addition to LDL-C in the monitoring of statin treatment is currently not warranted.

LDL cholesterol estimation using the Anandaraja's and Friedewald's formulas in schizophrenic patients treated with antipsychotic drugs

Objectives The use of new antipsychotic drugs is associated with an increased risk of diabetes and metabolic syndrome, and the routine monitoring of blood lipids during treatment has been recommended. Recently, a new formula for the estimation of low-density lipoprotein (LDL) cholesterol from total cholesterol and triglycerides has been proposed by Anandaraja et al. (Int J Cardiol 2005; 102: 117), and the aim of our study was its evaluation in schizophrenic patients treated with antipsychotic drugs. Materials and methods In 487 serum samples from schizophrenic patients treated with clozapine in polytherapy, the concentrations of LDL cholesterol were determined by agar gel electrophoresis and the formula of Friedewald et al. (Clin Chem 1972; 18: 499), and compared with the results of the Anandaraja's formula. Results A higher correlation and lower error of the estimate of the electrophoresis results was found with those of Friedewald ( r = 0.940, ma68 = 0.17 mmol/L) than those of Anandaraja ( r = 0.811, ma68 = 0.31 mmol/L). Similar results were obtained on making a dichotomy of the patients with and without metabolic syndrome lipid profile. A highly significant correlation was found between the high-density lipoprotein (HDL) cholesterol levels and the Anandaraja/Electrophoresis ( r = 0.817, p < 0.001) and Anandaraja/Friedewald ( r = 0.977, p < 0.001) ratios. Conclusions According to our data, Anandaraja's formula tends towards an overestimation or underestimation of LDL cholesterol levels, depending on whether the HDL cholesterol levels are high or low, which may be clinically significant. These results do not support the proposed better accuracy of the Anandaraja's than the Friedewald's formula.

Response to: Low-density lipoprotein cholesterol estimation by a new formula — Confirmation

Gasko et al. in their study of over 10,000 patients have confirmed the utility of the new formula derived by us [ [1] Anandaraja S. Narang R. Godeswar R. Laksmy R. Talwar K.K. Low-density lipoprotein cholesterol estimation by a new formula in Indian population. Int J Cardiol. 2005; 102: 117-120 Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar ] for the indirect estimation of low-density lipoprotein cholesterol. Our formula had better correlation than the conventional Friedewald formula as compared to direct method of estimation of low-density lipoprotein cholesterol. The validation was conducted in a mix of urban and rural population of Brazil. The mean low-density lipoprotein cholesterol level calculated by direct method and that estimated by the indirect Friedewald method were similar to our population (116±22 mg/dl vs 116±41.5 mg/dl and 120±24 mg/dl vs 119±46 mg/dl, respectively). It is heartening to find that the utility of the formula derived from Indians is equally effective to a different ethnic group, indicating that the new formula is applicable for a wider range of population. The ratio of triglycerides to very low-density lipoprotein cholesterol varies with the population studied [ 2 Hata Y. Nakajima K. Application of Friedenwald LDL-cholesterol estimation formula to serum lipids in the Japanese population. Jpn Circ J. 1986; 50: 1191 Crossref PubMed Scopus (32) Google Scholar , 3 Fujimoto W.Y. Friedenwald's LDL-cholesterol estimation formula in a Japanese American population. Jpn Circ J. 1988; 52: 604-606 Crossref PubMed Scopus (11) Google Scholar ] and hence application of the Friedewald formula for low-density lipoprotein cholesterol estimation in different populations may lead to varying accuracies. Our formula is solely based on regression analysis and hence may have a wider utility as reported by Gasko et al. in their present study.

Low-density lipoprotein cholesterol estimation by a new formula — Confirmation

Our result supports the reliability of new Anandaraja's formula for low-density lipoprotein estimation in Brazil population.

LDL cholesterol estimation in patients with the metabolic syndrome

BackgroundThe Friedewald formula (LDL-F) for the estimation of low-density lipoprotein (LDL) cholesterol concentrations is the most often used formula in clinical trials and clinical practice. However, much concern has been raised as to whether this formula is applicable in all patient populations such as the presence of chylomicronaemia and/or hypertriglyceridaemia. The aim of the present study was to evaluate various LDL cholesterol calculation formulas as well as LDL cholesterol levels provided by the Lipoprint LDL System (LDL-L) in patients with the metabolic syndrome (MetSyn).ResultsLDL-F showed significant differences from other formulas in the total cohort, as well as in MetSyn individuals. This was not the case in nonMetSyn subjects, where LDL-F did not differ with other formulas, with the exception of one formula (LDL by Planella, LDL-P). The bias between LDL-F and other LDL estimation formulas were significantly higher in MetSyn subjects compared to nonMetSyn individuals, except for LDL-L which produced similar bias with LDL-F in both study groups.ConclusionLDL-F seems to exhibit some limitations as far as the calculation of LDL-C levels in patients with the MetSyn is concerned. LDL-L might be more accurate in MetSyn subjects, but so far its use is limited for the estimation of small, dense LDL (sdLDL) cholesterol levels and mean LDL particle size for research purposes only.

Low-density lipoprotein cholesterol estimation by the Anandaraja's formula – confirmation

The number of the indirect methods for LDL-C estimation is growing. Our result support the reliability of new Anandaraja's formula for low-density lipoprotein estimation from total cholesterol and triglycerides.

Influence of apolipoprotein E genotype on the reliability of the Friedewald formula in the estimation of low-density lipoprotein cholesterol concentrations

Lipoprotein data and apolipoprotein (apo) E genotype from 1302 participants, covering a wide range of total plasma cholesterol levels, were used to examine the impact of apo E genotype on the estimation of low-density lipoprotein cholesterol (LDL-C0 concentrations by the Friedewald formula using high-density lipoprotein cholesterol and triglyceride (TG) concentrations as compared with the β-quantification reference procedure. The results showed that participants with apo E2/E2 genotype had significantly higher very low-density lipoprotein cholesterol (VLDL-C) concentrations and VLDL-C/TG ratio as well as lower LDL-C concentrations than participants with other apo E genotypes. Heterozygous carriers of the ɛ2 allele had significantly higher VLDL-C than participants with apo E3/E3 and E4/E3 genotypes. The mean absolute error and the mean percentage of bias in calculated LDL-C according to all apo E genotypes, except E2/E2 genotype, were less than 0.16 mmol/L and 4.4%, respectively. Indeed, the mean error and the mean percentage of bias associated with the LDL-C calculated by the Friedewald formula in the apo E2/E2 group were 0.93 mmol/L and 40.6%, respectively. However, participants with the apo E2/E2 genotype and a type III phenotype showed a mean error and a mean percentage of bias reaching 1.53 mmol/L and 63.5%, respectively, whereas E2/E2 participants with a non–type III phenotype had a mean error and a mean precentage of bias of 0.18 mmol/L and 11.0%, respectively. Moreover, 41.9% to 57.1% of the participants had an absolute bias higher than 5% according to the apo E genotype, except for the apo E2/E2 genotypic group where 88.6% of the participants had an absolute bias higher than 5%. Stepwise multiple linear regression analyses revealed that the apo E genotype contributed to 39.0% of the VLDL-C/TG ratio variance, whereas sex, age, and high-density lipoprotein cholesterol explained between 0.5% and 3.2% of the variance. These results indicate that the apo E genotype exerts a significant influence on the estimation of LDL-C concentrations by the Friedewald formula as compared with the β-quantification.

Comparison of two methods of estimation of low density lipoprotein cholesterol, the direct versus friedewald estimation

Current recommendations of the Adult Treatment Panel and Adolescents Treatment Panel of National Cholesterol Education Program make the low-density lipoprotein cholesterol (LDL-C) levels in serum the basis of classification and management of hypercholesterolemia. A number of direct homogenous assays based on surfactant/solubility principles have evolved in the recent past. This has made LDL-C estimation less cumbersome than the earlier used methods. Here we compared one of the direct homogenous assays with the widely used Friedewald's method of estimation of LDL-C to see the differences and correlation. We used direct homogenous assay kit to estimate serum LDL-C and high-density lipoprotein cholesterol (HDL-C). Serum Triglyceride (TG) and Total Cholesterol (TC) was estimated and using Friedewald's formula LDL-C was calculated. The LDL-C level obtained by both methods in 893 fasting serum samples were compared. The statistical methods used were paired t-test and Pearson's correlation.There was significant difference in the mean LDL-C levels obtained by the two methods at the TG levels <200 mg/dl (p<0.02) and TC levels >150 mg% (p<0.001). The correlation coefficient (r) between Friedewald's and direct assay estimation was 0.88. Friedewald's method classified 23.5 % of patients as high cardiac risk whereas there were 17.58% by direct assay.Both had good correlation even though the serum triglyceride and total cholesterol levels affect the difference in LDL-C estimated by both methods. Taking into account the cost and performance, Friedewald's method is as good or even better for classifying and managing patients.

Evaluation of Methods for the Measurement of Low-Density Lipoprotein Cholesterol

A high concentration of low-density lipoprotein cholesterol (LDL-C) in plasma is one of the strongest risk factors for atherosclerotic cardiovascular disease and mortality. The most common approach to determining LDL-C in the clinical laboratory is the Friedewald calculation. There is an increased interest to improve the accuracy of LDL-C estimated by this equation. The expert panel convened by National Cholesterol Education Program has recommended the development of accurate direct methods to measure LDL-C. Several homogeneous and fully automated methods have been introduced in recent years that show improved precision and accuracy over earlier methods, especially the Friedewald calculation. Each of the atherogenic particles in plasma--very-low, intermediate-, and low- density lipoprotein--as well as lipoprotein (a), contain one molecule of apolipoprotein B (apoB) and thus, plasma total concentration of apoB reflects the number of atherogenic particles. Several studies suggested that the measurement of apoB could improve the prediction of risk of coronary artery disease. Thus, in addition to the newly developed direct assays, alternative calculation procedures have been proposed that also take into consideration total serum apoB concentration for the estimation of LDL-C and the presence of small, dense LDL particles. The new generation of homogenous methods for the measurement of LDL-C and the use of serum apoB concentration for the estimation of LDL-C can contribute to the accurate LDL-C determination.

Low-density lipoprotein cholesterol estimation by a new formula in Indian population

Background Estimation of low-density lipoprotein cholesterol is crucial in the management of ischemic heart disease patients. Low-density lipoprotein cholesterol is routinely calculated in laboratories world over by applying Friedewald formula for logistic reasons. We derived a new formula based on multiple regression approach. Methods Lipid profiles were done on blood samples of 2008 patients. In initial 1000 patients, low-density lipoprotein cholesterol was estimated by a direct method and also by Friedewald formula. By applying linear regression methods on the data of direct estimation method, a new formula was obtained and the accuracy of this new formula was validated in the next 1008 patients. Results The mean low-density lipoprotein cholesterol was 116±41.5 mg/dl (3.02±1.08 mmol/l) measured by direct low-density lipoprotein cholesterol assay and that calculated by Friedewald formula was 119±46 mg/dl (3.09±1.2 mmol/l) for the initial 1000 patients. Low-density lipoprotein cholesterol measured by direct low-density lipoprotein cholesterol assay and calculated from Friedewald formula showed good correlation ( r=0.88), however, there was minimal overestimation by the Friedewald formula. The correlation improved between direct low-density lipoprotein cholesterol and calculated low-density lipoprotein cholesterol after excluding the patients with triglycerides more than 350 mg/dl ( r=0.92). The mean low-density lipoprotein cholesterol measured by the direct assay and by new formula in the next 1008 patients was 117±40 mg/dl (3.04±1.04 mmol/l) and 113.7±37 mg/dl (2.96±0.96 mmol/l), respectively with very good correlation ( r=0.97) between them. Conclusions The new formula derived from multiple linear regression analysis appears to be more accurate than Friedewald formula in Indian population.

Evaluation of alternative calculation methods for determining low-density lipoprotein cholesterol in hemodialysis patients

Objectives: To evaluate alternative equations for the estimation of low-density lipoprotein cholesterol (LDL-C) than the Friedewald equation in hemodialysis patients. Design and methods: The equations LDL-C = 0.41TC − 0.14TG + 0.66ApoB − 10.43 and LDL-C = 0.94TC − 0.94HDL-C − 0.19TG were evaluated in 86 patients and compared with the Friedewald equation and the ultracentrifugation procedure. Results: The alternative equations yield significantly lower bias than the Friedewald equation and are less affected by increased triglycerides (TG) levels. Conclusion: The alternative equations for LDL-C yield slightly better results than the Friedewald equation especially in hypertriglyceridemia.

Evaluation of five methods for determining low-density lipoprotein cholesterol (LDL-C) in hemodialysis patients

Objectives: Current recommendations for the management of dyslipidemia are largely based on the concentration of LDL-C. Most clinical laboratories estimate the concentration of LDL-C by the recommended routine method, the equation of Friedewald, in specimens from fasting subjects and with TG concentrations < 4.52 mmol/L. Because of the limitations of the Friedewald calculation, direct methods for an accurate quantification of LDL-C are needed. Design and Methods: In the present study we evaluated the accuracy of the following 5 different procedures for LDL-C in 98 patients on hemodialysis: the Friedewald equation, where LDL-C is calculated from HDL-C, measured either by the precipitation procedure with dextran sulfate-Mg 2+ (Method 1), or by a direct HDL-C assay (Method 2), the Direct LDL™ assay (Method 3), the homogeneous N-geneous™ LDL assay (Method 4) and the calculated LDL-C values deriving from the ApoB based equation: 0.41TC - 0.32TG + 1.70ApoB - 0.27, (Clin Chem 1997;43:808–815) (Method 5). Results: All five LDL-C methods were found to be in good agreement with ultracentrifugation/dextran sulfate-Mg 2+ precipitation with the coefficients of correlation of the assays to ranging between 0.93–0.95. However, significant differences in the mean values and biases vs. the reference method were observed. The Friedewald equation and the Direct assay were less affected by high LDL-C levels, and they presented higher sensitivity and higher negative predictive value. The N-geneous assay and the ApoB derived calculation were less affected by high triglyceride levels, and they presented higher specificity and higher positive predictive value. At the diagnostic LDL-C level of 3.37 mmol/L, both Friedewald calculations correctly classified 82/92 patients; Direct assay 86/98; N-geneous assay 88/98; and ApoB derived calculation 88/98. At the diagnostic LDL-C level of 2.98 mmol/L, Friedewald calculations (Method 1 and Method 2) correctly classified 82/92 and 81/92 patients, respectively; Direct assay (LDL-3) 87/98; N-geneous assay (LDL-4) 91/98; and ApoB derived calculation (LDL-5) 91/98. Conclusions: Among hemodialysis patients, who commonly present “average” LDL-C concentrations and high TG levels, the N-geneous assay and the apoB derived calculation seem to yield more acceptable results for the estimation of LDL-C.

Evaluation of Lp[a] and other independent risk factors for CHD in Asian Indians and their USA counterparts

Conventional risk factors for coronary heart disease (CHD) do not completely account for the observed increase in premature CHD in people from the Indian subcontinent or for Asian Indians who have immigrated to the USA. The objective of this study was to determine the effect of immigration to the USA on plasma levels of lipoprotein [a] (Lp[a]) and other independent risk factors for CHD in Asian Indians. Three subject groups were studied: group 1, 57 subjects living in India and diagnosed with CHD (CHD patients); group 2, 46 subjects living in India and showing no symptoms of CHD (control subjects); group 3, 206 Asian Indians living in the USA. Fasting blood samples were drawn to determine plasma levels of triglyceride (TG), total cholesterol (TC), low density lipoprotein [LDL cholesterol (LDL-Chol)], high density lipoprotein [HDL cholesterol (HDL-Chol)], apolipoprotein B-100 (apoB-100), and Lp[a]. Apolipoprotein [a] (apo[a]) size polymorphism was determined by immunoblotting. Plasma TG, apoB-100, and Lp[a] concentrations were higher in CHD patients than in control and USA groups. CHD patients had higher levels of TC and LDL-Chol and lower HDL-Chol than control subjects. However, the USA population had higher levels of TC, LDL-Chol, and apoB-100 and lower HDL-Chol than control subjects. Plasma Lp[a] levels were inversely correlated with the relative molecular weight of the more abundant of each subject's two apo[a] isoforms (MAI), and CHD patients showed higher frequencies of lower relative molecular weights among MAI. Our observed changes in lipid profiles suggest that immigrating to the USA may place Asian Indians at increased risk for CHD. This study suggests that elevated plasma Lp[a] confers genetic predisposition to CHD in Asian Indians, and nutritional and environmental factors further increase the risk of CHD. This is the first report implicating MAI size as a predictor for development of premature CHD in Asian Indians. Including plasma Lp[a] concentration and apo[a] phenotype in screening procedures may permit early detection and preventive treatment of CHD in this population.

Biological variation of serum lipids and lipoproteins in patients with clinically well controlled non insulin dependent diabetes mellitus.

To investigate how the visit-to-visit variation in serum lipids measurements affects the decision making concerning treatment according to the National Cholesterol Education Program (NCEP) guidelines in patients with clinically well controlled non-insulin-dependent diabetes mellitus (NIDDM) we have measured the biological variation (CVb) in serum total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) in 26 patients with NIDDM. We found the CVb as follows: TC, 5.1%; TG, 17.0%; HDL-C 4.4% and LDL-C, 8.3%. Confidence intervals (95%) were determined with total intra-individual variance values around the NCEP cut-off points to evaluate how well one, two and three lipid measurements provided reliable risk classification. A single TC measurements < 177 mg/dL or > 263 mg/dL allowed confident classification as "desirable" or "high risk" respectively. For LDL-C, one measurement was accurate only at below 106.3 mg/dL or above 183.7 mg/dL. The average of three measurements contracted these limits to < 186.7 mg/dL and > 253.3 mg/dL for TC, and < 116.3 mg/dL and > 173.7 mg/dL for LDL-C. For HDL-C also, multiple measurements improved risk assignment in a similar fashion. There were no values which allowed assignment to the "borderline high" category with one TC measurement and with one and two LDL-C measurements. The mean of three TC and three LDL-C measurements allowed assignment to the "borderline high" category, if between 213.3 and 226.7 mg/dL for TC, 143.7 and 146.3 mg/dL for LDL-C. Seven patients (26.9%) in this risk group based on the mean of two LDL-C estimates could be placed into a different category when the mean of three estimates was taken, even though the first two LDL-C test results did not differ by more than 30 mg/dL. Our results suggest that repeated lipid measurement is important especially for the "borderline-high" risk group because big variations existed in some patients, and further that TC is the most reliable quantity.

Effect of serum lipoprotein(a) on estimation of low-density lipoprotein cholesterol by the Friedewald formula

The calculation of serum low-density lipoprotein cholesterol (LDL-C) by the Friedewald formula does not account for the cholesterol associated with lipoprotein(a) [Lp(a)]. To quantify the contribution of Lp(a) cholesterol to total serum cholesterol, we measured concentrations of serum Lp(a) by an ELISA and concentrations of other serum lipids and lipoproteins by standard assays in 23 normolipemic women, ages 50-60 years. In measuring serum high-density lipoprotein we found that polyethylene glycol 6000 precipitated > 99.8% of all Lp(a). When serum Lp(a) concentrations were < or = 300 mg/L, 301-600 mg/L, and > 600 mg/L, the uncorrected serum LDL-C was overestimated, respectively, by a mean of 4.1% (n = 7), 8.5% (n = 8), and 21.4% (n = 8). Serum Lp(a) concentrations were positively correlated with percentage overestimation (P < 0.001), but were not correlated with either corrected or uncorrected serum LDL-C. We conclude that the Friedewald formula should be modified to take into account the contribution of Lp(a) cholesterol to total serum cholesterol.