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Quest Diagnostics

LDL Cholesterol Calculations

Test code(s) 7600, 14852(X), 19543, 92061, 92145, 91716, 92052, 92053

The level of low-density lipoprotein-cholesterol (LDL-C), among other factors, correlates with the likelihood of developing atherosclerotic cardiovascular disease (ASCVD). Thus, LDL-C measurement is useful for assessing ASCVD risk, stratifying individuals into treatment benefit groups, and monitoring risk-reduction therapy.1

LDL-C is most often measured indirectly, using a calculation based on other blood lipid analytes. Historically, the Friedewald calculation2 has been the most common approach. This equation, developed in the 1970s, incorporates total cholesterol, HDL-cholesterol (HDL-C), and triglyceride concentrations:

      LDL-C (mg/dL) = total cholesterol – HDL-C – (triglycerides/5),

where “triglycerides/5” is used to represent very low-density lipoprotein-C (VLDL-C).

LDL-C concentration can also be measured directly or with newer equations. Quest Diagnostics uses the Martin-Hopkins calculation, as described below, which provides accurate quantitation even in patients with triglyceride (TG) values between 200 mg/dL and 400 mg/dL and LDL-C levels below 70 mg/dL.

Although the Friedewald equation it is still widely used and generally produces reliable results, it may underestimate LDL-C at the low LDL-C levels that modern treatment guidelines call for and therapies can achieve (eg, <70-100 mg/dL).3 PCSK-9 inhibitors can drive LDL-C levels even lower (eg, <40 mg/dL). Such low LDL-C concentrations are below the concentrations considered when the Friedewald equation was developed.2

This limitation relates to the fact that the Friedewald equation uses a fixed ratio of triglyceride to VLDL-C; it does not allow for heterogeneity in the ratio of triglycerides to VLDL-C. This becomes a problem especially at lower LDL-C and higher triglyceride concentrations, when the Friedewald calculation tends to underestimate LDL-C. In a 2013 study, Martin and colleagues compared the results of direct LDL-C and calculated LDL-C using the Friedewald equation in more than 1.3 million U.S. adults.4 Friedewald-estimated LDL-C tended to be lower than directly measured LDL-C, especially in patients with calculated LDL-C levels below 100 mg/dL. At triglyceride levels ≥150 mg/dL, calculated LDL-C was often below <70 mg/dL in patients with directly measured LDL-C in the 71-80 mg/dL range. These findings suggest that the tendency of the Friedewald equation to underestimate LDL-C at higher triglyceride and lower LDL-C levels could result in high-risk patients being undertreated.

The Martin-Hopkins calculation provides greater customization to a patient’s specific triglyceride level by using a more “personalized” factor to calculate VLDL-C from triglycerides.4 This adjustable factor, which can range from 3.1 to 11.9, was derived from an analysis of triglyceride-to-VLDL-C ratios in more than 1.3 million people.4 The factor is lowest for patients with very low levels of triglyceride and high levels of non-HDL-cholesterol (total cholesterol – HDL-C), and highest for those with very high levels of triglyceride and low levels of non-HDL-cholesterol.

Compared with the Friedewald equation, the Martin-Hopkins calculation provides better correlation with direct LDL-C measurements.3-7 Concordance with guideline-based risk classification, especially at high triglyceride and low LDL-C, is also superior using the Martin-Hopkins calculation.3-7 In the 2013 validation study mentioned above,4 the improvement was greatest for people with estimated LDL-C levels below 70 mg/dL, especially those with higher triglyceride levels (see Table). Thus, the primary advantage of the Martin-Hopkins equation is that it is applicable to low LDL-C levels even in the presence of elevated triglyceride concentrations. 

The improved accuracy at low LDL-C allows more accurate assessment of patients in the high-risk categories undergoing aggressive treatment with low LDL goals. In addition, the ability to adjust for high triglyceride levels may improve reliability of LDL-C estimation when fasting is not desired or practical.8 This can be convenient for risk assessment, especially for patients who have difficulty fasting (eg, young children and people with diabetes).8

The need for fasting varies with the indication for testing, and the method used to calculate LDL-C should not affect the decision to require fasting samples. However, as noted above, the ability of the Martin-Hopkins calculation to adjust for high triglyceride levels may also make LDL-C estimation more reliable in nonfasting patients.8

If the LDL concentration could not be calculated because the triglyceride level was too high, direct LDL-C testing may be useful. Direct LDL measurement provides a reliable result even when triglyceride levels are up to 1,000 mg/dL. It can be ordered as a stand-alone test, as a reflex if the patient’s triglyceridelevel is likely to exceed 400 mg/dL, or as part of one of several panels. The table below lists tests and panels that include direct LDL-C measurement or reflex to direct LDL-C measurement when the triglyceride level is above 400 mg/dL:

Yes. Aside from standard lipid profile tests, Quest offers several advanced lipid testing options, including measurement of LDL particle number and size. In a number of retrospective analyses, lipoprotein subfractions have been found to be associated with CVD events.9,10 Additionally, particle numbers as determined by ion mobility were found to be a significant determinant in defining residual risk.11 Quest uses ion mobility separation of subfractions for these measurements. The ion mobility method directly measures particle size and concentration, unlike other approaches that use algorithms to indirectly calculate lipid subfractions.12 And, unlike some methods, ion mobility separation of subfractions does not cause lipoprotein modification that could potentially affect the accuracy of the assay.10,13 Ion mobility has been used in multiple lipoprotein studies9,10,14 and is the method used in the Cardio IQ Lipoprotein Fractionation, Ion Mobility test (Test Code 91604).

 

References

  1. Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;129:S1-45.
  2. 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.
  3. Quispe R, Hendrani A, Elshazly MB, et al. Accuracy of low-density lipoprotein cholesterol estimation at very low levels. BMC Med. 2017;15:83.
  4. 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;310:2061-2068.
  5. Meeusen JW, Lueke AJ, Jaffe AS, et al. Validation of a proposed novel equation for estimating LDL cholesterol. Clin Chem. 2014;60:1519-1523.
  6. Lee J, Jang S, Son H. Validation of the Martin method for estimating low-density lipoprotein cholesterol levels in Korean adults: findings from the Korea National Health and Nutrition Examination Survey, 2009-2011. PLoS One. 2016;11:e0148147.
  7. Chaen H, Kinchiku S, Miyata M, et al. Validity of a novel method for estimation of low-density lipoprotein cholesterol levels in diabetic patients. J Atheroscler Thromb. 2016;23:1355-1364.
  8. Nordestgaard BG, Langsted A, Mora S, et al. Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cutpoints-a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem. 2016;62:930-946.
  9. Musunuru K, Orho-Melander M, Caulfield MP, et al. Ion mobility analysis of lipoprotein subfractions identifies three independent axes of cardiovascular risk. Arterioscler Thromb Vasc Biol. 2009;29:1975-1980.
  10. Mora S, Caulfield MP, Wohlgemuth J, et al. Atherogenic Lipoprotein Subfractions Determined by Ion Mobility and First Cardiovascular Events After Random Allocation to High-Intensity Statin or Placebo: The Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) Trial. Circulation. 2015;132:2220-2229.
  11. Melander O, Shiffman D, Caulfield MP, et al. Low-Density Lipoprotein Particle Number Is Associated With Cardiovascular Events Among Those Not Classified Into Statin Benefit Groups. J Am Coll Cardiol. 2015;65:2571-2573.
  12. Caulfield MP, Li S, Lee G, et al. Direct determination of lipoprotein particle sizes and concentrations by ion mobility analysis. Clin Chem. 2008;54:1307-1316.
  13. Krauss RM. Lipoprotein subfractions and cardiovascular disease risk. Curr Opin Lipidol. 2010;21:305-311.
  14. Krauss RM, Pinto CA, Liu Y, et al. Changes in LDL particle concentrations after treatment with the cholesteryl ester transfer protein inhibitor anacetrapib alone or in combination with atorvastatin. J Clin Lipidol. 2015;9:93-102.

 

This FAQ is provided for informational purposes only and is not intended as medical advice. A clinician’s test selection and interpretation, diagnosis, and patient management decisions should be based on his/her education, clinical expertise, and assessment of the patient.

Document FAQS.164 Version: 1
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Version 0 effective 02/13/2017 to 08/21/2017

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