Low-density lipoprotein-cholesterol (LDL-C) remains a key contributor to plaque formation and atherosclerotic cardiovascular disease (ASCVD). Measuring LDL-C by gold standard ultracentrifugation is time-intensive and expensive. As such, the Friedewald equation, an estimate of LDL-C initially intended for research purposes, has been utilized over the past 50 years as a primary method for clinically estimating LDL-C.¹ The equation subtracts high-density lipoprotein-cholesterol (HDL-C) and a fixed ratio of triglycerides/5, an estimate of very low-density lipoprotein-cholesterol (VLDL-C), from total cholesterol to provide an estimate of LDL-C.

Friedewald estimation, however, is prone to inaccuracies at high triglyceride and/or low LDL-C values where inaccuracy in VLDL-C estimation using a "one size fits all approach" constitutes a larger proportion of estimated LDL-C. This subsequently leads to underestimation of calculated LDL-C.^2-4 While this imprecision has been historically tolerated, the increased prevalence of high triglyceride states such as diabetes and obesity and novel lipid lowering medications such as PCSK9 inhibitors achieving even lower LDL-C levels provide impetus for improving precision in LDL-C estimation.

Improvements and Updates

The recent 2018 American Heart Association (AHA)/American College of Cardiology (ACC) multi-society cholesterol guidelines acknowledged the importance of accurate LDL-C estimation. The guidelines provided Class IIa recommendation in measuring direct LDL-C or using an alternative LDL-C estimation (the Martin/Hopkins equation) in patients with LDL-C values below 70 mg/dL.

However, direct LDL-C assays available commercially use proprietary chemical-based methods, not ultracentrifugation, and are not necessarily reliable. They are not standardized and, in some cases, can be even less accurate than the Friedewald equation.^4,5

In a study of seven direct methods for measuring LDL-C, Miller et al. highlighted the challenges of accurate LDL-C measurement. Total errors of LDL-C assessment ranged from 13.3-13.5% across the assays in healthy individuals, and -26.6% to 31.9% in those with known cardiovascular disease or dyslipidemias. Given the National Cholesterol Education Program's total error goal of ≤13%, this resulted in all seven assays failing standard accuracy goals.⁶

The Martin/Hopkins Equation

Several prior equations have attempted to improve upon Friedewald estimation but used a similar approach in fixing the ratio between triglycerides and VLDL-C.^7-10 In a study of over 1.3 million fasting and nonfasting patients from the Very Large Database of Lipids, Martin and colleagues derived and validated a novel equation which replaced the fixed ratio of 5 for VLDL-C estimation by using one of 180 adaptable ratios based on a patient's individual non-HDL-C and TG values. The ratios range from 3.1-11.9 and are personalized to the specific lipid panel.¹¹

This approach led to distinct improvements in accuracy as compared to Friedewald estimates. In the derivation study, overall accuracy of the Martin/Hopkins equation compared to direct ultracentrifugation was 92% in contrast to 85% accuracy for Friedewald estimation (p < 0.001).¹¹ Improved accuracy was preserved across all LDL-C guideline cutpoints, especially in lower LDL-C groups. In patients with LDL-C values of 130-159 mg/dL, 100-129 mg/dL, and 70-99 mg/dL, accuracies of Martin/Hopkins LDL-C estimation compared to Friedewald estimation were: 90.4% vs. 88.2%, 91.4% vs. 87.1%, and 92.6% vs. 84.7%, respectively.

Does Guideline Support Go Far Enough?

The 2018 AHA/ACC guidelines acknowledged the strength of the Martin/Hopkins equation specifically for those with LDL-C <70mg/dL and triglyceride levels >150 mg/dL (1.7mmol/L).¹² In the original Very Large Database of Lipids derivation study, accuracy of LDL-C estimation with the Martin/Hopkins equation was 94% compared to 77% via the Friedewald approach.¹¹ These results were even more striking when stratified by triglyceride levels. In patients with LDL-C <70 mg/dL and triglycerides of 150-199 mg/dL, LDL-C accuracy was 92% with Martin/Hopkins estimation compared to 61% with the Friedewald equation. In those with triglyceride levels of 200-399 mg/dL, accuracy of Martin/Hopkins estimation was 83% compared to only 40% with Friedewald calculation.¹¹

While the LDL-C threshold of 70 mg/dL is important in very high-risk ASCVD patients to consider additive nonstatin therapies, the inaccuracies of the Friedewald equation are not exclusively limited to secondary-prevention patients with lower LDL-C goals. It is equally important to accurately estimate LDL-C in those with values above 70 mg/dL who may benefit from initiation or intensification of lipid-lowering therapies. The 2018 guidelines highlighted several groups of primary prevention patients, such as those without diabetes and 10-year ASCVD risk of >7.5% with LDL-C values >70 mg/dL who may benefit from statins.¹² Per the guidelines, specific percent LDL-C reductions should be monitored to assess therapeutic effects of statins. However, if LDL-C is inaccurately estimated, this may have important implications with goal reductions and patient classification.

For example, a prior study by Martin et al. compared the Friedewald equation to direct ultracentrifugation in 1,340,614 Very Large Database of Lipids patients. Overall, 14.6% of participants were inappropriately classified by LDL-C guideline cutpoints when using Friedewald estimation. Notably, 11.3% of these errors were the result of LDL-C underestimation.² This directly leads to misclassification of patients into falsely lower LDL-C groups, and in particular those with LDL-C >70 mg/dL, who may benefit from intensified pharmacotherapy if treatment is aimed for secondary prevention. From a therapeutic standpoint, underestimation remains a major flaw with the Friedewald equation. However, the 2018 guidelines failed to endorse the Martin/Hopkins equation in patients with these higher LDL-C values.

The 2018 guidelines also addressed the utility of nonfasting samples. Recent work and consensus statements have highlighted benefits of removing fasting status from clinical decision-making, such as patient adherence to laboratory follow-up and more efficient use of laboratory/clinical resources which may not be burdened by the influx of fasting patients each morning.^13,14 Nonfasting samples may further benefit at-risk patient populations, such as those with diabetes mellitus where overnight fasting may require adjustments to oral medications and insulin regimens thereby placing patients at risk for hypo or hyperglycemia.

The Martin/Hopkins equation further provides an advantage in the nonfasting setting. In the postprandial state, triglyceride values may be increased but the equation is able to adapt by adjusting the estimated VLDL-C ratio.¹⁵ In a separate analysis of fasting versus nonfasting patients from the Very Large Database of Lipids study, the Martin/Hopkins equation performed significantly better than Friedewald estimation, with accuracy ranging from 87-94% with the Martin/Hopkins equation compared to 71-93% for Friedewald estimation (p ≤ 0.001).

These results were especially notable at LDL-C values less than 70mg/dL, with 19% of fasting and 30% of nonfasting patients exhibiting greater than 10mg/dL differences between Friedewald estimation and direct ultracentrifugation. In contrast, only 2.2% of fasting and 2.5% of nonfasting patients had such magnitude of error with the Martin/Hopkins equation. While the 2018 guidelines provided Class I recommendation for either fasting or nonfasting lipid profile acquisition to assess ASCVD risk and document baseline LDL-C, no specific endorsement was made for how LDL-C should be estimated.

Lastly, the 2018 guidelines listed level of evidence for the Martin/Hopkins equation as C-LD (Limited Data), and cited only two references in support of the equation which heralded from the original derivation dataset.¹² However, the equation has received further external validation.

For example, in a post-hoc analysis of FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk), in which patients with prior ASCVD were randomized to receive evolocumab or placebo in addition to standard lipid-lowering therapies, the authors examined Martin/Hopkins and Friedewald LDL-C estimates as compared to gold-standard preparative ultracentrifugation in 56,624 lab samples.¹⁶ In the overall cohort, only 2.6% of Martin/Hopkins LDL-C values had differences of more than 10 mg/dL compared to ultracentrifugation values. In contrast, nearly 13.3% of Friedewald LDL-C values exhibited similar differences. This trend was even more striking among those with triglyceride values >150 mg/dL: 10.0% of Martin/Hopkins LDL-C values compared to 50.2% of Friedewald LDL-C values differed by more than 10 mg/dL compared to preparative ultracentrifugation values. Similar improvements in LDL-C accuracies were also noted in post-hoc analysis from VOYAGER (an individual patient data meta-analysis Of statin therapY in At risk Groups: Effects of Rosuvastatin, atorvastatin, and simvastatin), in a patient cohort with familial combined hyperlipidemia and in Japanese patients with ASCVD.^17-19

Conclusion

As clinical decision-making trends and guideline management continue to push towards lower LDL-C levels, the need for updated and accurate clinical tools becomes even more important. The Martin/Hopkins equation provides the most accurate method to date of estimating LDL-C without associated costs and inaccuracies inherent to other methods of LDL-C measurement. Although direct LDL-C measurements are endorsed in the recent guidelines, commonly available chemical assays are not standardized and reliable. In contrast, the Martin/Hopkins equation is easily scalable and can be encoded within any electronic health record or laboratory system.

The Martin/Hopkins equation has a particular advantage in those with LDL-C values less than 70 mg/dL, an advantage acknowledged by the recent guidelines.²⁰ However, patients with LDL-C values above 70 mg/dL are also assessed more accurately with the Martin/Hopkins equation than with Friedewald estimation. The Martin/Hopkins method further has advantages with nonfasting samples and has received external validation from several studies. The level of evidence in support of the equation is robust.

While the 2018 guidelines provide a major step forward, there remains opportunity for future guidelines to broaden and strengthen endorsement of the most accurate LDL-C assessment to best inform patient care. Given growing support for the Martin/Hopkins equation with adoption across several healthcare systems and national laboratories, the next guidelines will likely upgrade the level of evidence in support of utilizing the equation.

References

1. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499-502.
2. Martin SS, Blaha MJ, Elshazly MB, et al. Friedewald-estimated versus directly measured low-density lipoprotein cholesterol and treatment implications. J Am Coll Cardiol 2013;62:732-9.
3. Fukuyama N, Homma K, Wakana N, et al. Validation of the Friedewald equation for evaluation of plasma ldl-cholesterol. J Clin Biochem Nutr 2008;43:1-5.
4. Nauck M, Warnick GR, Rifai N. Methods for measurement of LDL-cholesterol: a critical assessment of direct measurement by homogeneous assays versus calculation. Clin Chem 2002;48:236-54.
5. Evans SR, Fichtenbaum CJ, Aberg JA, A5087 Study Team. Comparison of direct and indirect measurement of LDL-C in HIV-infected individuals: ACTG 5087. HIV Clin Trials 2007;8:45-52.
6. Miller WG, Myers GL, Sakurabayashi I, et al. Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures. Clin Chem 2010;56:977-86.
7. Rao A, Parker AH, el-Sheroni NA, Babelly MM. Calculation of low-density lipoprotein cholesterol with use of triglyceride/cholesterol ratios in lipoproteins compared with other calculation methods. Clin Chem 1988;34:2532-4.
8. Chen Y, Zhang X, Pan B, et al. A modified formula for calculating low-density lipoprotein cholesterol values. Lipids Health Dis 2010;9:52.
9. de Cordova CM, de Cordova MM. A new accurate, simple formula for LDL-cholesterol estimation based on directly measured blood lipids from a large cohort. Ann Clin Biochem 2013;50:13-9.
10. DeLong DM, DeLong ER, Wood PD, Lippel K, Rifkind BM. A comparison of methods for the estimation of plasma low- and very low-density lipoprotein cholesterol. The Lipid Research Clinics Prevalence Study. JAMA 1986;256:2372-7.
11. Martin SS, Blaha MJ, Elshazly MB, et al. Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile. JAMA 2013;310:2061-8.
12. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. J Am Coll Cardiol 2018. [Epub ahead of print]
13. Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1—full report. J Clin Lipidol 2015;9:129-69.
14. Mora S. Nonfasting for routine lipid testing: from evidence to action. JAMA Intern Med 2016;176:1005-6.
15. Sathiyakumar V, Park J, Golozar A, et al. Fasting versus nonfasting and low-density lipoprotein cholesterol accuracy. Circulation 2018;137:10-9.
16. Martin SS, Giugliano RP, Murphy SA, et al. Comparison of low-density lipoprotein cholesterol assessment by Martin/Hopkins estimation, Friedewald estimation,a nd preparative ultracentrifugation: insights from the FOURIER trial. JAMA Cardiol 2018;3:749-53.
17. Palmer MK, Barter PJ, Lundman P, Nicholls SJ, Toth PP, Karlson BW. Comparing a novel equation for calculating low-density lipoprotein cholesterol with the Friedewald equation: a VOYAGER analysis. Clin Biochem 2019;64:24-9.
18. Mehta R, Reyes-Rodriguez E, Yaxmehen Bello-Chavolla O, et al. Performance of LDL-C calculated with Martin's formula compared to the Friedewald equation in familial combined hyperlipidemia. Atherosclerosis 2018;277:204-10.
19. Sonoda T, Takumi T, Miyata M, et al. Validity of a novel method for estimating low-density lipoprotein cholesterol levels in cardiovascular disease patients treated with statins. J Atheroscler Thromb 2018;25:643-52.
20. Quispe R, Hendrani A, Elshazly MB, et al. Accuracy of low-density lipoprotein cholesterol estimation at very low levels. BMC Med 2017;15:83.

Clinical Topics: Cardiovascular Care Team, Diabetes and Cardiometabolic Disease, Dyslipidemia, Prevention, Hypertriglyceridemia, Lipid Metabolism, Nonstatins, Novel Agents, Statins, Diet

Keywords: Cholesterol, LDL, Cholesterol, HDL, Cholesterol, VLDL, Triglycerides, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Goals, American Heart Association, Insulin, Fasting, Secondary Prevention, Consensus, Lipids, Diabetes Mellitus, Cholesterol, Dyslipidemias, Hyperglycemia, Obesity, Primary Prevention, Ultracentrifugation, Cardiovascular Diseases, Patient Compliance

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