Comparison and Validation of 10 Equations Including a Novel Method for Estimation of LDL-cholesterol in a 168,212 Asian Population

Best practice for LDL-cholesterol: when and how to calculate

The lipid profile is important in the risk assessment for cardiovascular disease. The lipid profile includes total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides (TGs) and low-density lipoprotein (LDL)-cholesterol (LDL-C). LDL-C has traditionally been calculated using the Friedewald equation (invalid with TGs greater than 4.5 mmol/L and is based on the assumption that the ratio of TG to cholesterol in very- low-density lipoprotein (VLDL) is 5 when measured in mg /dL). LDL-C can be quantified with a reference method, beta-quantification involving ultracentrifugation and this is unsuitable for routine use. Direct measurement of LDL-C was expected to provide a solution with high TGs. However, this has some challenges because of a lack of standardisation between the reagents and assays from different manufacturers as well as the additional costs. Furthermore, mild hypertriglyceridaemia also distorts direct LDL-C measurements. With the limitations of the Friedewald equation, alternatives have been derived. Newer equations include the Sampson-National Institutes of Health (NIH) equation 2 and the Martin-Hopkins equation. The Sampson-NIH2 equation was derived using beta-quantification in a population with high TG and multiple least squares regression to calculate VLDL-C, using TGs and non-HDL-C as independent variables. These data were used in a second equation to calculate LDL-C. The Sampson-NIH2 equation can be used with TGs up to 9 mmol/L. The Martin-Hopkins equation uses a 180 cell stratification of TG/non-HDL-C to determine the TG:VLDL-C ratio and can be used with TGs up to 4.5 mmol/L. Recently, an extended Martin-Hopkins equation has become available for TGs up to 9.04 mmol/L.This article discusses the best practice approach to calculating LDL-C based on the available evidence.

Indirect calculation of LDL using thirteen equations in Pakistani population

BACKGROUND

Owing to the atherogenic properties, low density lipoprotein cholesterol (LDL-C) is the primary target for treatment and diagnosis of cardiovascular diseases (CVDs), hence accurate measurement of LDL-C is critical. Despite the availability of direct measurement assays for LDL-C, it is routinely calculated by Friedewald equation in clinical settings in Pakistan mostly due to financial constraints. However, the validity of this equation is impacted by several factors, therefore several other equations have been developed for the calculation of LDL-C.

MATERIALS AND METHODS

LDL-C of 39,385 individuals measured directly by homogenous assays (dLDL) was compared with LDL-C calculated by thirteen equations (cLDL-C). Stratifications based on different lipids i.e., triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL) were made to check the validity of these equations across all ranges of lipid profile. The correlation and median difference between dLDL and cLDL-C was statistically analyzed.

RESULTS

Overall Teerakanchana equation displayed a strong positive correlation (ρ = 0.967) and least median difference (-8.81) with dLDL, followed by Martin equation (ρ = 0.967). For higher TG ranges (>500 mg/dL), Teerakanchana equation had the least median difference (1.31) and a strong correlation (ρ = 0.800).

CONCLUSION

Our data suggest that Teerakanchana equation may be employed as an alternative to Friedewald equation for Pakistani population.

How should low-density lipoprotein cholesterol be calculated in 2022?

PURPOSE OF REVIEW

The reference method for low-density lipoprotein-cholesterol (LDL-C) quantitation is β-quantification, a technically demanding method that is not convenient for routine use. Indirect calculation methods to estimate LDL-C, including the Friedewald equation, have been used since 1972. This calculation has several recognized limitations, especially inaccurate results for triglycerides (TG) >4.5 mmol/l (>400 mg/dl). In view of this, several other equations were developed across the world in different datasets.The purpose of this review was to analyze the best method to calculate LDL-C in clinical practice by reviewing studies that compared equations with measured LDL-C.

RECENT FINDINGS

We identified 45 studies that compared these formulae. The Martin/Hopkins equation uses an adjustable factor for TG:very low-density lipoprotein-cholesterol ratios, validated in a large dataset and demonstrated to provide more accurate LDL-C calculation, especially when LDL <1.81 mmol/l (<70 mg/dl) and with elevated TG. However, it is not in widespread international use because of the need for further validation and the use of the adjustable factor. The Sampson equation was developed for patients with TG up to 9 mmol/l (800 mg/dl) and was based on β-quantification and performs well on high TG, postprandial and low LDL-C samples similar to direct LDL-C.

SUMMARY

The choice of equation should take into the level of triglycerides. Further validation of different equations is required in different populations.

Comparação das Novas Equações de Martin/Hopkins e Sampson para o Cálculo do Colesterol de Lipoproteína de Baixa Densidade em Pacientes Diabéticos

Fundamentos

Objetivos

Método

Resultados

Conclusão

Comparative Study of Calculated LDL-Cholesterol Levels with the Direct Assay in Patients with Hypothyroidism

Background Hypothyroidism is one among the many factors that predisposes one to coronary artery disease. As low-density lipoprotein-cholesterol (LDL-C) is associated with cardiovascular risk, calculated LDL-C should have good accuracy with minimal bias. Hypothyroidism alters the lipid composition of lipoproteins by the secretion of triglyceride-rich lipoproteins, which affects the calculation of LDL-C. The present study aimed to compare 13 different formulae for the calculation of LDL-C including the newly derived Martin's formula by direct assay in patients of hypothyroidism.

Method In this analytical cross-sectional study, a total of 105 patients with laboratory evidence of hypothyroidism, from January to June 2019, were studied, and blood samples were subjected for lipid profile analysis at central biochemistry laboratory. Calculated LDL-C was assessed by different formulae.

Result We observed that calculated LDL-C by Friedewald's, Cordova's, Anandaraja's, Hattori's, and Chen's formulae has bias less than ± 5 compared with direct LDL-C, with Anandaraja's formula having the lowest bias (2.744) and Cordova's formula having lowest bias percentage (−1.077) among them. According to the Bland–Altman plots, the bias in Friedewald's and Anandraja's were equally distributed below and above the reference line of direct LDL-C.

Conclusion This is the first study comparing different formulae for LDL-C calculation in patients with hypothyroidism. Anandaraja's formula was as equally effective as Friedewald's formula when used as an alternative cost-effective tool to evaluate LDL-C in hypothyroid patients. The recently proposed Martin's formula for calculated LDL-C had a higher bias when compared with Friedewald's and Anandaraja's formulae in patients with hypothyroidism.

Validation of a novel method for determination of low-density lipoprotein cholesterol levels in Indian patients with type 2 diabetes

BACKGROUND AND AIMS

LDL-cholesterol (LDL-C), being the primary predictor of cardiovascular disease in Type 2 diabetes (T2D), is associated with cardiovascular risk stratification and requires to be estimated with better accuracy with minimal bias. Different formulae have been devised to calculate the LDL-C from the measured lipid profile parameters.

METHODS

In this analytical cross-sectional study, a total of 150 patients with T2D were studied, and blood samples were subjected for lipid profile analysis at the Central Biochemistry laboratory. Different formulae assessed calculated LDL-C.

RESULTS

We observed that all formulae, except Ahmadi, underestimated the LDL-C compared to direct assay. A significant difference was observed between all calculated LDL-C and directly measured LDL-C. On linear regression analysis, the newer formula Martin's has a better approximation with direct assay (slope: 0.9708) than Friedewald (slope: 0.9477). Similarly, Martin's formula exhibited lesser bias (-13.56) in calculating LDL-C in patients with T2D compared with Friedewald's formula.

CONCLUSIONS

The study demonstrated that in patients with T2D, all formulae except Ahmadi significantly underestimated the LDL-C when compared with the direct assay. The newer Martin's formula appeared to more precisely calculate LDL-C in T2D when compared with the traditional Friedewald's formula.

A Tale of Two Approaches

OBJECTIVES

To summarize and assess the literature on the performances of methods beyond the Friedewald formula (FF) used in routine practice to determine low-density lipoprotein cholesterol (LDL-C).

METHODS

A literature review was performed by searching the PubMed database. Many peer-reviewed articles were assessed.

RESULTS

The examined methods included direct homogeneous LDL-C assays, the FF, mathematical equations derived from the FF, the Martin-Hopkins equation (MHE), and the Sampson equation. Direct homogeneous assays perform inconsistently across manufacturers and disease status, whereas most FF-derived methods exhibit variable levels of performance across populations. The MHE consistently outperforms the FF but cannot be applied in the setting of severe hypertriglyceridemia. The Sampson equation shows promise against both the FF and MHE, especially in severe hypertriglyceridemia, but data are still limited on its validation in various settings, including disease and therapeutic states.

CONCLUSIONS

There is still no consensus on a universal best method to estimate LDL-C in routine practice. Further studies are needed to assess the performance of the Sampson equation.

Validation of multiple equations for estimating low-density lipoprotein cholesterol levels in Korean adults

Background

Limited data are available for validation of low-density lipoprotein cholesterol (LDL) calculation (LDL_cal) in the adult Korean population. The aim of this study was to develop and validate a new equation for LDL_cal and to compare it with previous such equations in a Korean population.

Methods

A new equation for LDL_cal was developed (LDL_Choi). LDL_Choi and 11 other previously published equations were applied and compared with directly measured LDL concentration (LDL_direct) in a development cohort (population 1), an independent validation cohort in the same laboratory (population 2), and the Korea National Health and Nutrition Examination Survey 2017 cohort (population 3).

Results

Among the 12 equations, the newly-developed equation (LDL_Choi = total cholesterol – 0.87 x high-density lipoprotein cholesterol – 0.13 x triglycerides) had the highest intraclass correlation coefficient (ICC) and the lowest mean systemic difference and median absolute percentage error in populations 1 and 2 but not in population 3. Subgroup analysis showed good agreement between LDL_Choi and LDL_direct (ICC > 0.75) in population 2, whose LDL_direct < 70 mg/dL. For samples with high triglycerides (> 400 mg/dL), equation accuracy varied. Categorization concordance according to the National Cholesterol Education Program Adult Treatment Panel III criteria with the other 11 equations were less than 80%; that of LDL_Choi was 87.6 and 87.4% in populations 1 and 2, respectively.

Conclusions

Accuracy of 12 equations for LDL_cal varied by cohort and subgroup based on LDL_direct and triglycerides. A laboratory-specific equation for LDL_cal and/or LDL_direct may be needed for accurate evaluation of LDL status.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01525-6.

Comparison of three equations for estimating low-density lipoprotein-cholesterol in the rural northeastern region of Thailand

BACKGROUND

Cardiovascular disease is the most common cause of death worldwide, and the detection of LDL-C contributes to reducing risks. However, the LDL-C is rarely evaluated according to the gold standard method because it is costly and time-consuming. This study aimed to determine the agreement of LDL-C among three equations, namely Friedewald's equation, Puavilai's equation, and Dansethakul's equation.

METHODS

A cross-sectional descriptive study.

RESULTS

Using the data of lipid measurement from a specific group of people in the remote rural area, we found that the Thai equations have more superior agreement with direct measurement than the Friedewald equation (ICC = 0.870, 95% CI = 0.857-0.882) when the agreement of continuous data was used for total analysis. Although the categorical analysis that gave better agreement was from Friedewald equation (K index = 0.730, 95% CI = 0.720-0.751), the findings from this study confirmed the population-specific use of Pauvilai's equation and Dansethakul's equation for determining the LDL-C.

CONCLUSION

Pauvilai's equation showed better agreement with direct measurement for LDL-C. Thus, it could be considered as an alternative for the direct method, particularly in laboratories in rural areas in Thailand.

Clinical Validation of Eleven Formulas for Calculating LDL-C in Iran

Background & Objective:

Concentration of low-density lipoprotein (LDL) is a known risk factor for cardiovascular disease which is routinely measured or calculated as LDL-C in clinical laboratories. In order to decrease the cost, instead of its measuring, it is recommended to calculate it using multiple formulas that have been introduced up to now. The aim of this study was to assess the results of various formulas and comparison of these results with those of measuring method and to clarify the best formula for the Iranian population.

Methods:

Concentrations of total cholesterol (TC), triglyceride (TG), cholesterol of high-density lipoprotein (HDL-C) and LDL-C in serums of 471 overnight fasting individuals were measured and also LDL-Cs of these samples were calculated by eleven different formulas according to their TC, TG, and HDL-C concentrations. Subsequently, results of measured and calculated LDL-C were analyzed statistically by paired t-test, correlation coefficient, and Passing-Bablok regression. In addition, for clinical evaluation, the differences between calculated and measured mean results were calculated and compared with an allowable total error.

Results:

Paired t-test unraveled a significant difference between the results of measured and calculated LDL-C by various formulas. But for some formulas, these differences were not clinically significant. The best clinical and statistical agreement (correlation coefficient) was obtained by the Friedewald equation.

Conclusion:

By using validated methods which have correct calibration and control system for measuring TC, TG, and HDL-C, we can use the Friedewald formula for calculating LDL-C in serum samples with TG up to 400 mg/dL.

Comparison of Novel Equations for Estimating Low-Density Lipoprotein Cholesterol in Patients Undergoing Coronary Angiography

AIM

The importance of precisely quantifying low-density lipoprotein cholesterol (LDL-C) has become more pronounced over the years, with the rise of metabolic syndrome in the population and the reduction in LDL-C treatment goals. This study aims to compare two novel equations indirectly estimating LDL-C and assess their compatibility with Friedewald formula, in a population with high cardiovascular risk.

METHODS

This study is a retrospective analysis of the lipid profiles of 10,006 patients who underwent coronary angiography. LDL-C was calculated using Friedewald, Martin, and Sampson equations, and the compatibility between estimations was compared using methods of concordance and reclassification.

RESULTS

Our findings show that Martin and Sampson equations displayed high rates of upward LDL-C reclassification (10.8% and 7.5%, respectively) when compared with Friedewald equation. In comparison to the Sampson method, Martin also reclassified 3.8 % of patients to a higher LDL-C category. The magnitude of discordance between LDL-C estimates was more pronounced in hypertriglyceridemic patients, and this increased progressively with the reduction in LDL-C. The proportion of patients with LDL-C ＜70 mg/dL reclassified to a higher LDL-C category reached 44% (Sampson vs. Friedewald), 65% (Martin vs. Friedewald), and 37% (Martin vs.Sampson) in those with triglyceride levels between 200 and 399 mg/dL.

CONCLUSIONS

Both Martin and Sampson LDL-C estimates displayed significant proportion of upward discordance with reclassification to higher LDL-C categories compared to Friedewald formula, particularly in patients with elevated triglycerides and low LDL-C, a population in whom more accurate estimation of LDL-C is required. Further studies are warranted to validate the recently developed Sampson equation with comparison to Martin method that tended to more significantly overestimate LDL-C.

Validity of a Novel Method for Estimating Low-Density Lipoprotein Cholesterol Levels in Cardiovascular Disease Patients Treated with Statins

AIM

The Friedewald equation is the standard method for estimating low-density lipoprotein cholesterol (LDL-C) levels [LDL-C(F)] and fixes the ratio of triglyceride (TG) to very LDL-C at 5. However, this has been reported to underestimate LDL-C, particularly in patients with LDL-C ＜70 mg/dL. A novel method for LDL-C estimation [LDL-C(M)] using an adjustable factor instead of a fixed value of 5 has recently been proposed. The purpose of this study was to validate LDL-C(M) in Japanese patients with cardiovascular disease (CVD) treated with statins.

METHODS

In 385 consecutive CVD patients treated with statins, LDL-C(M) and LDL-C(F) levels were compared with directly measured LDL-C [LDL-C(D)].

RESULTS

Mean LDL-C(D), LDL-C(F), and LDL-C(M) were 81.7±25.5, 76.4±24.6, and 79.9±24.5 mg/dL, respectively. In all patients, both LDL-C(F) and LDL-C(M) were significantly correlated with LDL-C(D) [LDL-C(F) vs. LDL-C(D): R=0.974, p＜0.001; LDL-C(M) vs. LDL-C(D): R=0.987, p＜0.001]. In patients with LDL-C(D) ＜70 mg/dL, LDL-C(M) showed a better correlation with LDLC(D) compared with LDL-C(F) [LDL-C(M) vs. LDL-C(D): R=0.935, p＜0.001; LDL-C(F) vs. LDLC(D): R=0.868, p＜0.001]. In contrast, the correlation of LDL-C(D) with LDL-C(M) or LDL-C(F) was similar in patients with LDL-C(D) ≥70 mg/dL.

CONCLUSIONS

In Japanese patients with CVD treated with statins, LDL-C level estimated by this novel method might be more accurate than those estimated using the Friedewald equation for LDL-C levels ＜70 mg/dL.

Performance of Calculated and Directly Measured Low-Density Lipoprotein Cholesterol in a Pediatric Population

OBJECTIVES

An assessment of methods for the accurate measurement of low-density lipoprotein cholesterol (LDL-C) at decreased concentrations has not yet been carried out. We evaluated the performance of the Friedewald equation, a direct enzymatic assay, and a novel equation for determining LDL-C levels in a pediatric population with elevated triglycerides and reduced LDL-C levels.

METHODS

LDL-C concentrations of 127 pediatric patients were determined by the Friedewald equation, a direct enzymatic assay, and a novel equation. The bias of each approach was assessed at selected LDL-C cutoffs and after stratifying samples by triglyceride content. The concordance of each approach, relative to the reference method, was determined at LDL-C cut-points of less than 70, 70 to 99, and 100 to 129 mg/dL.

RESULTS

The Friedewald equation substantially underestimated pediatric LDL-C concentrations below 100 mg/dL in the presence of elevated triglycerides. The Ortho Clinical Diagnostics (Raritan, NJ) direct LDL assay was positively biased at low LDL-C levels. The novel equation most effectively reduced the bias of the Friedewald equation at all LDL-C concentrations and increased the concordance of sample classification to the reference method.

CONCLUSIONS

The novel equation should be used for accurate measurement of pediatric LDL-C when the concentration is below 100 mg/dL in the presence of elevated triglycerides (150-399 mg/dL).

Calculation of LDL-Cholesterol vs. Direct Homogenous Assay

BACKGROUND

Low-density lipoprotein cholesterol (LDLc) can be calculated or measured directly and their accordance is the subject of controversy.

OBJECTIVES

The aim of this study was to identify the independent predictors of LDLc, to formulate the best equation for calculating LDLc and to evaluate the validity of it and the published formulas, including the new method with adjustable coefficient.

METHODS

The profile of serum lipids and (apo)lipoproteins of 310 subjects was used to determine the most accurate formula for calculating serum LDLc. Serum lipids, lipoproteins and apolipoproteins were measured by enzymatic, new homogenous and immunoturbidometric methods, respectively.

RESULTS

Multiple linear regression analysis indicates that total cholesterol, apoB, HDLc and triglyceride are independent predictors of LDLc. We proposed four new formulas to calculate LDLc. As total cholesterol (TC) is the major determinant of LDLc, it can be estimated simply as 0.545 of total cholesterol. Inclusion of HDLc, triglyceride, apoB and a constant value improved the equation slightly. The equation of: LDLc (mg/dl) = 0.75 TC - 0.5 HDLc - 0.1 TG had the lowest mean and SD of difference among all the methods examined here. LDLc was also calculated by the new modified Friedewald's equation using adjustable factor from Martin's table, but it did not improve the results significantly. LDLc gap was correlated significantly and positively with triglyceride and negatively with cholesterol or its subfractions.

CONCLUSIONS

Our data suggest the simplest formula: LDLc = 0.545 TC or a more detailed: LDLc = 0.75 TC - 0.5 HDLc - 0.1 TG be used for calculating serum LDLc.

Validity of a Novel Method for Estimation of Low-Density Lipoprotein Cholesterol Levels in Diabetic Patients

Aim: Low-density lipoprotein cholesterol (LDL-C) is routinely estimated using the Friedewald equation [LDL-C(F)]. A novel method for LDL-C [LDL-C(M)] estimation recently proposed by Martin et al. was reported to be more accurate than the Friedewald formula in subjects in the United States. The validity of LDL-C(M) in different races and patients with diabetes mellitus (DM) has not been elucidated. The purpose of this study was to validate the LDL-C(M) estimates in Japanese population with type 2 DM by comparing with LDL-C(F) and directly measured LDL-C [LDL-C(D)].

Methods: Both LDL-C(M) and LDL-C(F) levels were compared against LDL-C(D) measured by selective solubilization method in 1,828 Japanese patients with type 2 DM.

Results: On linear regression analysis, LDL-C(M) showed a stronger correlation than that shown by LDL-C(F) (R = 0.979 vs. R = 0.953, respectively) with LDL-C(D). We further analyzed the effect of serum triglyceride (TG) concentrations on the accuracy of LDL-C(F) and LDL-C(M). Although LDL-C levels showed a positive correlation with TG levels, the LDL-C(F) levels tended to show a greater divergence from LDL-C(D) levels than that shown by LDL-C(M) with changes in TG levels.

Conclusion: We for the first time demonstrated a more useful measurement of LDL-C levels estimated by Martin's method than that estimated by the Friedewald equation in Japanese patients with DM.