Non-HDL-C/TG ratio indicates significant underestimation of calculated low-density lipoprotein cholesterol (LDL-C) better than TG level: a study on the reliability of mathematical formulas used for LDL-C estimation

Assessing Performance of Martins's and Sampson's Formulae for Calculation of LDL-C in Indian Population: A Single Center Retrospective Study

Various formulae had been derived to calculate the LDL-C from other lipid profile parameters to supplant the need for direct estimation. Martin's, Sampson's, and Cordova's formulae are recently derived formulae for calculating LDL-C. However, no study has been undertaken till now to verify the newer formulae viz. Martins's and Sampson's in Indian population. The retrospective cross-sectional study was carried out after obtaining approval from the Institutional Ethics Committee on human subject research. The lipid profile data were collected for a period of 17 months from January 2020 to May 2021. The formulae proposed by Friedewald, Cordova, Anandaraja, Martin, and Sampson were used to assess calculated LDL-C. Intraclass correlations were performed to assess the effectiveness of each formula when compared with direct estimation. In our study, we observed that LDL-C calculated using Martin was observed to be closer to that of direct estimation. The bias observed was lowest for Martin's formulae, followed by Sampson's. Intraclass correlation analysis for absolute agreement demonstrated Cordova, Martin, and Sampson to have an average ICC > 0.9, with Martin, and Sampson having a p value < 0.05. Martin fared superior to other formulae in intraclass correlation in patients with LDL > 70. In patients with TG below 200 mg/dL, Martin, and Sampson had a significant correlation with comparable average ICC. However, in patients with TG > 300 mg/dL, Cordova appears to fare better than all other formulae. Our study demonstrated a distinctly superior performance of Martin's formula over Friedewald's formula in the Indian patient population.

Evaluation of low-density lipoprotein cholesterol equations by cross-platform assessment of accuracy-based EQA data against SI-traceable reference value

OBJECTIVES

Low-density lipoprotein cholesterol (LDLC) is the primary cholesterol target for the diagnosis and treatment of cardiovascular disease (CVD). Although beta-quantitation (BQ) is the gold standard to determine LDLC levels accurately, many clinical laboratories apply the Friedewald equation to calculate LDLC. As LDLC is an important risk factor for CVD, we evaluated the accuracy of Friedewald and alternative equations (Martin/Hopkins and Sampson) for LDLC.

METHODS

We calculated LDLC based on three equations (Friedewald, Martin/Hopkins and Sampson) using the total cholesterol (TC), triglycerides (TG), and high-density lipoprotein cholesterol (HDLC) in commutable serum samples measured by clinical laboratories participating in the Health Sciences Authority (HSA) external quality assessment (EQA) programme over a 5 years period (number of datasets, n=345). LDLC calculated from the equations were comparatively evaluated against the reference values, determined from BQ-isotope dilution mass spectrometry (IDMS) with traceability to the International System of Units (SI).

RESULTS

Among the three equations, Martin/Hopkins equation derived LDLC had the best linearity against direct measured (y=1.141x - 14.403; R2=0.8626) and traceable LDLC (y=1.1692x - 22.137; R2=0.9638). Martin/Hopkins equation (R2=0.9638) had the strongest R2 in association with traceable LDLC compared with the Friedewald (R2=0.9262) and Sampson (R2=0.9447) equation. The discordance with traceable LDLC was the lowest in Martin/Hopkins (median=-0.725%, IQR=6.914%) as compared to Friedewald (median=-4.094%, IQR=10.305%) and Sampson equation (median=-1.389%, IQR=9.972%). Martin/Hopkins was found to result in the lowest number of misclassifications, whereas Friedewald had the most numbers of misclassification. Samples with high TG, low HDLC and high LDLC had no misclassification by Martin/Hopkins equation, but Friedewald equation resulted in ∼50% misclassification in these samples.

CONCLUSIONS

The Martin/Hopkins equation was found to achieve better agreement with the LDLC reference values as compared to Friedewald and Sampson equations, especially in samples with high TG and low HDLC. Martin/Hopkins derived LDLC also enabled a more accurate classification of LDLC levels.

Concordance of LDL-C Estimating Equations with Direct Enzymatic Measurement in Diabetic and Prediabetic Subjects

Low-density lipoprotein cholesterol (LDL-C) is a well-established biomarker in the management of dyslipidemia. Therefore, we aimed to evaluate the concordance of LDL-C-estimating equations with direct enzymatic measurement in diabetic and prediabetic populations. The data of 31,031 subjects included in the study were divided into prediabetic, diabetic, and control groups according to HbA1c values. LDL-C was measured by direct homogenous enzymatic assay and calculated by Martin-Hopkins, Martin-Hopkins extended, Friedewald, and Sampson equations. The concordance statistics between the direct measurements and estimations obtained by the equations were evaluated. All equations evaluated in the study had lower concordance with direct enzymatic measurement in diabetic and prediabetic groups compared to the non-diabetic group. Even so, the Martin-Hopkins extended approach demonstrated the highest concordance statistic in diabetic and prediabetic patients. Further, Martin-Hopkins extended was found to have the highest correlation with direct measurement compared with other equations. Over the 190 mg/dL LDL-C concentrations, the equation with the highest concordance was again Martin-Hopkins extended. In most scenarios, the Martin-Hopkins extended performed best in prediabetic and diabetic groups. Additionally, direct assay methods can be used at low values of the non-HDL-C/TG ratio (<2.4), as the performance of the equations in LDL-C estimation decreases as non-HDL-C/TG decreases.

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.

The accuracy of four formulas for LDL-C calculation at the fasting and postprandial states

Background

Elevated level of low-density lipoprotein cholesterol (LDL-C) is concerned as one of the main risk factors for cardiovascular disease, in both the fasting and postprandial states. This study aimed to compare the measured LDL-C with LDL-C calculated by the Friedewald, Martin–Hopkins, Vujovic, and Sampson formulas, and establish which formula could provide the most reliable LDL-C results for Chinese subjects, especially at the postprandial state.

Methods

Twenty-six subjects were enrolled in this study. The blood samples were collected from all the subjects before and after taking a daily breakfast. The calculated LDL-C results were compared with LDL-C measured by the vertical auto profile method, at both the fasting and postprandial states. The percentage difference between calculated and measured LDL-C (total error) and the number of results exceeding the total error goal of 12% were established.

Results

The calculated LDL-C_F levels showed no significant difference from LDL-C_VAP levels at the fasting state. The calculated LDL-C_S were significantly higher than LDL-C_VAP at the fasting state (P < 0.05), while the calculated LDL-C_s were very close to LDL-C_VAP levels after a daily meal. At the fasting state, the median total error of calculated LDL-C_F was 0 (quartile: −3.8 to 6.0), followed by LDL-C_S, LDL-C_MH, and LDL-C_V. At the postprandial states, the median total errors of LDL-C_S were the smallest, 1.0 (−7.5, 8.5) and −0.3 (−10.1, 10.9) at 2 and 4 h, respectively. The calculated LDL-C_F levels showed the highest correlation to LDL-C_VAP and accuracy in evaluating fasting LDL-C levels, while the Sampson formula showed the highest accuracy at the postprandial state.

Conclusion

The Friedewald formula was recommended to calculate fasting LDL-C, while the Sampson formula seemed to be a better choice to calculate postprandial LDL-C levels in Chinese subjects.

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.

Hypertriglyceridemia, a causal risk factor for atherosclerosis, and its laboratory assessment

Epidemiological and clinical studies show a causal association between serum triglyceride (TG) level, the number of triglyceride-rich lipoproteins (TRLs) and their remnants, and the increased risk of atherosclerosis and cardiovascular disease (CVD) development. In light of current guidelines for dyslipidemia management, the laboratory parameters reflecting TRL content are recommended as part of the routine lipid analysis process and used for CVD risk assessment, especially in people with hypertriglyceridemia (HTG), diabetes mellitus, obesity and low levels of low-density lipoprotein cholesterol (LDL-C), in which high residual CVD risk is observed. The basic routinely available laboratory parameters related with TRL are serum TG and non-high-density lipoprotein cholesterol (non-HDL-C) levels, but there are also other biomarkers related to TRL metabolism, the determination of which can be helpful in identifying the basis of HTG development or assessing CVD risk or can be the target of pharmacological intervention. In this review, we present the currently available laboratory parameters related to HTG. We summarise their link with TRL metabolism and HTG development, the determination methods as well as their clinical significance, the target values and interpretation of the results in relation to the current dyslipidemia guidelines.

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

Non-high-density lipoprotein cholesterol may predict the cardio-cerebrovascular risk in patients on maintenance hemodialysis

Background

Non-high-density lipoprotein cholesterol (non-HDL-C) may be an independent risk factor for cardio-cerebrovascular disease (CVD); however, the cutoff level in patients on maintenance hemodialysis (MHD) is unknown.

Methods

This was a retrospective multicenter study of MHD patients treated at 10 dialysis centers in Guangdong Province from July 1, 2016, to April 1, 2017. Laboratory test data were collected and CVD complications and outcomes recorded.

Results

In total, 1288 eligible patients were included in this study; the non-HDL-C interquartile range was 2.76 (2.24–3.45) mmol/L. Over a median follow-up time of 24 months, 141 patients developed CVD. The non-HDL-C level was a principal risk factor for such events (P < 0.05; 95% confidence interval 0.800–0.842). The maximum Youden index was 0.549 and the best cutoff > 3.39 mmol/L.

Conclusion

Higher baseline non-HDL-C levels may increase the CVD risk in MHD patients. Thus, non-HDL-C effectively predicts CVD.