Comparative assessment of LDL-C and VLDL-C estimation in familial combined hyperlipidemia using Sampson's, Martin's and Friedewald's equations

Abstract

Background: Sampson et al. developed a novel method to estimate very low-density lipoprotein cholesterol (VLDL-C) and low-density lipoprotein cholesterol (LDL-C) in the setting of hypertriglyceridemia. Familial Combined Hyperlipidemia (FCHL) is a common primary dyslipidemia in which lipoprotein composition interferes with LDL-C estimation. This study aimed to evaluate performance of LDL-C using this new method (LDL-S) compared with LDL-C estimated by Friedewald's and Martin eq. (LDL-F, LDL-M) in FCHL.

Methods: Data were collected from 340 subjects with confirmed FCHL. Concordance for VLDL-C measured by ultracentrifugation and LDL-C estimated using these measures compared to Sampson's, Martin's and Friedewald's equations was performed using correlation coefficients, root mean squared error (RMSE) and bias. Also, concordance of misclassified metrics according to LDL-C (< 70 and < 100 mg/dL) and Apo B (< 80 and < 65 mg/dL) thresholds were assessed.

Results: Sampson's equation was more accurate (RMSE 11.21 mg/dL; R² = 0.88) compared to Martin's (RMSE 13.15 mg/dL; R² = 0.875) and the Friedewald's equation (RMSE 13.7 mg/dL; R² = 0.869). When assessing performance according to LDL-C, Sampson's had highest correlation and lowest RMSE compared to other equations (RMSE 19.99 mg/dL; R² = 0.840). Comparing performance strength across triglyceride levels, Sampson's showed consistently improved correlations compared to Martin's and Friedewald's formulas for increasing triglycerides and for the FCHL phenotype of mixed dyslipidemia. Sampson's also had improved concordance with treatment goals.

Conclusions: In FCHL, VLDL-C and LDL-C estimation using Sampson's formula showed higher concordance with lipid targets assessed using VLDL-C obtained by ultracentrifugation compared with Friedewald's and Martin's equations. Implementation of Sampson's formula could improve treatment monitoring in FCHL.

Keywords: Cardiovascular risk; Familial combined hyperlipidemia; Friedewald’s equation; Low-density lipoprotein cholesterol; Martin/Hopkins’ equation; Sampson’ equation; Very low-density lipoprotein cholesterol.

Fig. 1

Performance metrics for all three formulas compared to VLDL-C measured by ultracentrifugation in the overall population, showing RMSE for the overall population (RMSE1, n = 340) and for subjects with triglycerides < 800 mg/dL (RMSE2) comparing VLDL-C measured by Martin’s (a), Sampson’s (b) and the Friedewald’s equation. The figure also shows Bland-Altman plots showing bias and limits of agreement for VLDL-C estimated using Martin’s (d), Sampson’s (e) and the Friedewald’s equation (f). Abbreviations = RMSE: Root of Mean Squared Error; 95%CI: 95% Confidence Interval; LDL-F: LDL-C estimated by the Friedewald’s equation; LDL-M: LDL-C estimated by Martin’s formula; LDL-S: LDL-C estimated by Sampson’s formula

Fig. 2

Performance metrics for all three formulas compared to LDL-C estimated using VLDL-C measured by ultracentrifugation in the overall population, showing RMSE for the overall population (RMSE1, n = 340) and for subjects with triglycerides < 800 mg/dL (RMSE2) comparing VLDL-C measured by Martin’s (a), Sampson’s (b) and the Friedewald’s equation. The figure also shows Bland-Altman plots showing bias and limits of agreement for VLDL-C estimated using Martin’s (d), Sampson’s (e) and the Friedewald’s equation (f). Abbreviations = RMSE: Root of Mean Squared Error; 95%CI: 95% Confidence Interval; LDL-F: LDL-C estimated by the Friedewald’s equation; LDL-M: LDL-C estimated by Martin’s formula; LDL-S: LDL-C estimated by Sampson’s formula