LDL Cholesterol Calculations

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 studies^9,10,14 and is the method used in the Cardio IQ Lipoprotein Fractionation, Ion Mobility test (Test Code 91604).