Project description:Background/Objectives: The currently established equations for calculating low-density lipoprotein cholesterol (LDLc) do not reflect the sex-specific differences in lipid metabolism. We aimed to develop a sex-specific LDLc equation (SSLE) and validate it with three established equations (Friedewald, Sampson-NIH, and ext-Martin-Hopkins) against direct LDLc measurement in Korean adults. Methods: This study included 23,757 subjects (51% male; median age, 51 years) from the 2009-2022 Korean National Health and Nutrition Examination Survey. We developed the SSLE through multiple linear regression incorporating total cholesterol (TC), high-density lipoprotein cholesterol (HDLc), triglycerides (TG), and sex. The validation metrics included Bland-Altman analysis for mean absolute percentage error (MAPE) and agreement of the categorization based on the NCEP ATP-III guidelines, assessed by sex and lipid subgroups. Results: The derived SSLE equation was as follows: for TG < 200 mg/dL, LDLc = 0.963 × TC - 0.881 × HDLc - 0.111 × TG + 0.982 × Sex - 6.958; for TG ≥ 200 mg/dL, LDLc = 0.884 × TC - 0.646 × HDLc - 0.126 × TG + 3.742 × Sex - 3.214 (male = 1, female = 0). The MAPE was similar between males and females for the SSLE (4.6% for both) and ext-Martin-Hopkins (5.0% vs. 4.9%) but higher in males for the Sampson-NIH (5.4% vs. 4.9%) and Friedewald (7.6% vs. 5.7%). In the TG ≥ 400 mg/dL group, the MAPE increased progressively: SSLE (10.2%), ext-Martin-Hopkins (12.0%), Sampson-NIH (12.7%), and Friedewald (27.4%). In the LDLc < 70 mg/dL group, the MAPE was as follows: SSLE (8.0%), Sampson-NIH (8.6%), ext-Martin-Hopkins (9.7%), and Friedewald (12.8%). At TG 200-400 mg/dL, the SSLE revealed very good agreement (κ = 0.801) versus good agreement for other equations (ext-Martin-Hopkins κ = 0.794, Sampson-NIH κ = 0.782, Friedewald κ = 0.696). Conclusions: The novel SSLE demonstrated superior accuracy and agreement in Korean adults. Further validation studies across different ethnic populations are warranted.

Project description:BackgroundLow-density lipoprotein cholesterol (LDL-C) is an important biomarker for determining cardiovascular risk and regulating lipid lowering therapy. Therefore, the accurate estimation of LDL-C concentration is essential in cardiovascular disease diagnosis and prognosis. Sampson recently proposed a new formula for the estimation of LDL-C. However, little is known regarding the validation of this formula.ObjectivesThis study aimed to validate this new formula with other well-known formulas in Turkish population, composed of adults.MethodsA total of 88,943 participants above 18 years old at Sivas Cumhuriyet University Hospital (Sivas, Turkey) were included to this study. LDL-C was directly measured by homogeneous assays, i.e., Roche, Beckman and Siemens and estimated by Friedewald's, Martin-Hopkins', extended Martin-Hopkins' and Sampson's formulas. The concordances between the estimations obtained by the formulas and the direct measurements were evaluated both in general and separately for the LDL-C, TG and non-HDL-C sublevels. Linear regression analysis was applied and residual error plots were generated between each estimation and direct measurement method. Coefficient of determination (R2) and mean absolute deviations were also calculated.ResultsThe results showed that the extended Martin-Hopkins approach provided the most concordant results with the direct assays for LDL-C estimation. The results also showed that the highest concordances were obtained between the direct assays with the extended Martin-Hopkins formula calculated with the median statistics obtained from our own population. On the other hand, it was observed that the results of the methods may differ in different assays. The extended Martin-Hopkins approach, calculated from the median statistics of our population, gave the most concordant results in patients with "low LDL-C level (LDL-C levels < 70 mg/dL) or hypertriglyceridemia (TG levels ≥ 400 mg/dL)".ConclusionsAlthough the results of the formulas in different assays may vary, the extended Martin-Hopkins approach was the best one with the highest overall concordances. The validity of the Martin Hopkins' and Sampson's formulas has to be further investigated in different populations.

Project description:ImportanceRecent studies have shown that Friedewald underestimates low-density lipoprotein cholesterol (LDL-C) at lower levels, which could result in undertreatment of high-risk patients. A novel method (Martin/Hopkins) using a patient-specific conversion factor provides more accurate LDL-C levels. However, this method has not been tested in proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor-treated patients.ObjectiveTo investigate accuracy of 2 different methods for estimating LDL-C levels (Martin/Hopkins and Friedewald) compared with gold standard preparative ultracentrifugation (PUC) in patients with low LDL-C levels in the Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk (FOURIER) trial.Design, setting, and participantsThe FOURIER trial was a randomized clinical trial of evolocumab vs placebo added to statin therapy in 27 564 patients with stable atherosclerotic cardiovascular disease. The patients' LDL-C levels were assessed at baseline, 4 weeks, 12 weeks, 24 weeks, and every 24 weeks thereafter, and measured directly by PUC when the level was less than 40 mg/dL per the Friedewald method (calculated as non-HDL-C level - triglycerides/5). In the Martin/Hopkins method, patient-specific ratios of triglycerides to very low-density lipoprotein cholesterol (VLDL-C) ratios were determined and used to estimate VLDL-C, which was subtracted from the non-HDL-C level to obtain the LDL-C level.Main outcomes and measuresLow-density lipoprotein cholesterol calculated by the Friedewald and Martin/Hopkins methods, with PUC as the reference method.ResultsFor this analysis, the mean (SD) age was 62.7 (9.0) years; 2885 of the 12 742 patients were women (22.6%). A total of 56 624 observations from 12 742 patients had Friedewald, Martin/Hopkins, and PUC LDL-C measurements. The median difference from PUC LDL-C levels for Martin/Hopkins LDL-C levels was -2 mg/dL (interquartile range [IQR], -4 to 1 mg/dL) and for Friedewald LDL-C levels was -4 mg/dL (IQR, -8 to -1 mg/dL; P < .001). Overall, 22.9% of Martin/Hopkins LDL-C values were more than 5 mg/dL different than PUC values, and 2.6% were more than 10 mg/dL different than PUC levels. These were significantly less than respective proportions with Friedewald estimation (40.1% and 13.3%; P < .001), mainly because of underestimation by the Friedewald method. The correlation with PUC LDL-C was significantly higher for Martin/Hopkins vs Friedewald (ρ, 0.918 [95% CI 0.916-0.919] vs ρ, 0.867 [0.865-0.869], P < .001).Conclusions and relevanceIn patients achieving low LDL-C with PCSK9 inhibition, the Martin/Hopkins method for LDL-C estimation more closely approximates gold standard PUC than Friedewald estimation does. The Martin/Hopkins method may prevent undertreatment because of LDL-C underestimation by the Friedewald method.Trial registrationClinicalTrials.gov Identifier: NCT01764633.

Project description:BackgroundThe 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.ObjectiveTo 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.MethodsUsing 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.ConclusionsThe 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.

Project description:Low-density lipoprotein (LDL-C) concentrations are a standard of care in the prevention of cardiovascular disease and are influenced by different factors. This study compared the LDL-C concentrations estimated by two different equations and determined their associations with inflammatory status, oxidative stress, anthropometric variables, food intake and DNA methylation levels in the LPL, ADRB3 and MTHFR genes. A cross-sectional population-based study was conducted with 236 adults (median age 37.5 years) of both sexes from the municipality of João Pessoa, Paraíba, Brazil. The LDL-C concentrations were estimated according to the Friedewald and Martin equations. LPL, ADRB3 and MTHFR gene methylation levels; malondialdehyde levels; total antioxidant capacity; ultra-sensitive C-reactive protein, alpha-1-acid glycoprotein, homocysteine, cobalamin, and folic acid levels; usual dietary intake; and epidemiological variables were also determined. For each unit increase in malondialdehyde concentration there was an increase in the LDL-C concentration from 6.25 to 10.29 mg/dL (p <0.000). Based on the Martin equation (≥70 mg/dL), there was a decrease in the DNA methylation levels in the ADRB3 gene and an increase in the DNA methylation levels in the MTHFR gene (p <0.05). There was a positive relation of homocysteine and cholesterol intake on LDL-C concentrations estimated according to the Friedewald equation and of waist circumference and age based on the two estimates. It is concluded the LDL-C concentrations estimated by the Friedewald and Martin equations were different, and the Friedewald equation values were significantly lower than those obtained by the Martin equation. MDA was the variable that was most positively associated with the estimated LDL-C levels in all multivariate models. Significant relationships were observed based on the two estimates and occurred for most variables. The methylation levels of the ADRB3 and MTHFR genes were different according to the Martin equation at low LDL-C concentrations (70 mg/dL).

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Assessing the Practical Differences in LDL-C Estimates Calculated by Friedewald, Martin/Hopkins, or NIH Equation 2: An Observation Cross-Sectional Study

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