Assessment of three equations to calculate plasma LDL cholesterol concentration in fasting and non-fasting hypertriglyceridemic patients.

OBJECTIVES: Low-density lipoprotein cholesterol (LDL-C) concentration was calculated for many years using the Friedewald equation, but those from Sampson and extended-Martin-Hopkins perform differently. Their accuracy in fasting hypertriglyceridemia and non-fasting state were compared and the clinical impact of implementing these equations on risk classification and on the setting of lipid treatment goals was assessed. METHODS: Seven thousand six standard lipid profiles and LDL-C concentrations measured after ultracentrifugation (uLDL-C) were retrospectively included. uLDL-C were compared to calculated LDL-C in terms of correlation, root mean square error, residual error, mean absolute deviations and cardiovascular stratification. RESULTS: In fasting state (n=5,826), Sampson equation was the most accurate, exhibited the highest percentage of residual error lower than 0.13 mmol/L (67 vs. 57 % and 63 % using Friedewald, or extended-Martin-Hopkins equations respectively) and the lowest misclassification rate. However, the superiority of this equation was less pronounced when triglyceride concentration (TG) <4.5 mmol/L were considered. In post-prandial state (n=1,180), extended-Martin-Hopkins was the most accurate equation, exhibited the highest percentage of residual error lower than 0.13 mmol/L (73 vs. 39 % and 57 % using Friedewald and Sampson equation respectively). Overall, the negative bias with Sampson equation may lead to undertreatment. Conversely, a positive bias was observed with extended Martin-Hopkins. CONCLUSIONS: None of the equations tested are accurate when TG>4.52 mmol/L. When TG<4.52 mmol/L both Sampson and Martin-Hopkins equations performed better than Friedewald. The switch to one or the other should take in account their limitations, their ease of implementation into the lab software and the proportion of non-fasting patients.

Evaluation of biochemical algorithms to screen dysbetalipoproteinemia in ε2ε2 and rare APOE variants carriers.

OBJECTIVES: Dysbetalipoproteinemia (DBL) is a combined dyslipidemia associated with an increased risk of atherosclerotic cardiovascular diseases mostly occurring in ε2ε2 subjects and infrequently in subjects with rare APOE variants. Several algorithms have been proposed to screen DBL. In this work, we compared the diagnostic performances of nine algorithms including a new one. METHODS: Patients were divided into 3 groups according to their APOE genotype: ε2ε2 ("ε2ε2", n=49), carriers of rare variants ("APOEmut", n=20) and non-carriers of ε2ε2 nor APOE rare variant ("controls", n=115). The algorithms compared were those from Fredrickson, Sniderman, Boot, Paquette, De Graaf, Sampson, eSampson, Bea and ours, the "Hospices Civils de Lyon (HCL) algorithm". Our gold standard was the presence of a ε2ε2 genotype or of a rare variant associated with triglycerides (TG) >1.7 mmol/L. A replication in the UK Biobank and a robustness analysis were performed by considering only subjects with both TG and low-density lipoprotein-cholesterol (LDLc) >90th percentile. RESULTS: Total cholesterol (TC)/ApoB and NHDLC/ApoB are the best ratios to suspect DBL. In ε2ε2, according to their likelihood ratios (LR), the most clinically efficient algorithms were the HCL, Sniderman and De Graaf's. In APOEmut, Sniderman's algorithm exhibited the lowest negative LR (0.07) whereas the HCL's exhibited the highest positive LR (29). In both cohorts, the HCL algorithm had the best LR. CONCLUSIONS: We proposed a powerful algorithm based on ApoB concentration and the routine lipid profile, which performs remarkably well in detecting ε2ε2 or APOE variant-related DBL. Additional studies are needed to further evaluate algorithms performances in DBL carriers of infrequent APOE variants.