Skip to content
Publicly Available Published by De Gruyter August 10, 2017

Reporting LDL-cholesterol levels in the era of intensive lipid management: a clarion call

  • Ishwarlal Jialal EMAIL logo and Verena Gounden

The importance of low density lipoprotein cholesterol (LDL-C) lowering in the prevention and management of cardiovascular disease (CVD) is well established. LDL-C has long been used as the lipid parameter to guide clinical decision making with regards to CVD. Despite disparity amongst current guidelines with regards to the use of LDL-C target levels or percent reduction of LDL-C there is consensus with regards to the pivotal role of LDL-C lowering to prevent CVD [1], [2].

In an era where intensive lipid lowering is the norm and several novel lipid lowering therapies such as PCSK9 inhibitors can lower LDL-C down to 0.8 mmol/L (30 mg/dL), the availability of accurate, reproducible and standardized methods for the reporting of LDL-C is paramount. The accuracy of LDL-C assessment at lower levels takes on particular importance, with guidelines recommending an LDL-C target of <1.8 mmol/L (70 mg/dL) for high risk patients or a 50% reduction in LDL-C [1], [2].

The use of the Friedewald equation for the estimation of LDL-C is widespread and has been the “benchmark” for routine LDL-C quantitation for several decades following its introduction in 1972. The Friedewald equation is based on the principle that most of the circulating triglycerides (TG) are carried by VLDL in a fasting person and assumes a constant factor for the TG:VLDL-cholesterol ratio [3]. It is a simple and cost effective method for determination for LDL-C and generally provides accurate results in patients with moderate and elevated LDL-C levels with TG levels <1.7 mmol/L (<150 mg/dL). However, there are several limitations or caveats to the use of the Friedewald equation for the estimation of LDL-C [3]. Non-fasting specimens contain chylomicrons and cannot be used to calculate LDL-C using the Friedewald equation accurately. Additionally in order to obtain reliable LDL-C estimation the equation can only be used for specimens with TGs<4.5 mmol/L (400 mg/dL). Also it is unreliable in patients with familial dysbetalipoproteinemia (Type III hyperlipoprotenemia). Furthermore the utility of the equation to estimate LDL-C in the growing number of obese and diabetic patients with hypertriglyceridemia whom are required to be evaluated for CVD poses a major problem. Underestimation of the LDL-C by the Friedewald equation is most manifest at low LDL-C levels and high TG levels [3]. In their study examining over a million patients with LDL-C estimation performed by Friedewald and ultracentrifugation, Martin et al. found that the Friedewald equation underestimates LDL-C leading to incorrect classification of risk groups [4]. They found this to occur particularly in the presence of TGs levels >2.3 mmol/L (200 mg/dL) and LDL-C<1.8 mmol/L where the concordance was only 40.3%. In a subsequent report in comparison to ultracentrifugation (beta-quantification) they confirmed the under-estimation of LDL-C by the Freidewald equation versus ultracentrifugation especially at LDL-C<1.8 mmol/L with a misclassification rate of 29% [5].

Another limitation of the Friedewald equation is that error is the sum of the errors of the three underlying measurements used to calculate the LDL-C. Modifications to the Friedewald equation has been proposed where the constant factor for the relationship of TG:VLDL was changed or made variable depending on the other lipid values. None of these modifications have been widely adopted for use for some of the following reasons: equations with adjustable factors are not easy to automate; these modified formulas are still affected by hypertriglyceridemia; they have not been validated in a large clinical trial [4], [5], [6].

Direct methods for the measurement of LDL-C have been widely adopted in routine laboratories. Introduction of the homogenous direct assays allowed for automation and improved precision. Direct methods do not require fasting samples and the assays are standardized to some extent. Issues of poor correlation between different direct methods as well as significant discordance when compared to reference method procedure (ultracentrifugation) have been reported [7]. However, more recent studies have shown good concordance with beta quantitation as well as good performance across triglyceride levels up to 11.3 mmol/L (1000 mg/dL) [3], [6]. It has been suggested that direct LDL-C be used in patients with triglyceride levels between 2.3 mmol/L and 4.5 mmol/L (200 mg/dL–399 mg/dL) and with LDL-C levels less than 2.6 mmol/L (100 mg/dL) [6]. In a recent study, the authors showed a misclassification rate for the Friedewald equation of under-reporting the LDL-C was 49% for samples with LDL-C<1.8 mmol/L compared to a direct LDL-C assay [6]. This study further underscores the issue of underestimation of LDL-C already documented by the ultracentrifugal methods [4], [5]. The direct assays are standardized, recommended by the ESC guidelines and were validated by the large Heart Protection Study [1], [6].

Beta quantification (BQ) as based on the Lipid Research Clinics method is the reference method procedure (RMP) for measurement of LDL-C although LDL-C is not directly assayed. However it is a tedious, technically demanding, labor-intensive and time-consuming method requiring a dedicated ultracentrifuge making it the least feasible option in routine clinical laboratories.

The measurement of apolipoprotein B (Apo B) allows for direct estimation of LDL as there is 1 molecule of ApoB in each molecule of LDL. Hence, it provides a measure of LDL mass/particles. The clinical utility of ApoB is similar to that of LDL-C with regards to prediction of CVD risk and it can be used in the presence of hypertriglyceridemia especially when the Friedewald equation is not valid. The EAS/ESC guidelines allow for the use of ApoB as a secondary treatment goal [1]. ApoB measurement by immunochemical methods is standardized and available on automated platforms making it a viable option for use in the routine laboratory setting. Laboratory costs of ApoB testing, however would be greater than that incurred for estimation of LDL-C using Friedewald.

The cheapest and simplest alternative to LDL-C estimation is the determination of non-HDL cholesterol calculated as total cholesterol minus HDL-C. Non-HDL-C provides an estimate of cholesterol content of all the apoB containing atherogenic lipoproteins in circulation including LDL, VLDL remnants, Lp(a) and thus can be argued to be a more inclusive measure of atherogenic risk. Various studies have demonstrated the strong diagnostic value of non-HDL-C as a marker of CVD risk. Non HDL-C has been reported to be a better risk estimator than LDL-C in patients with hypertriglyceridemia. Changes in non-HDL-C has been shown to be a better predictor of CVD events than treatment levels of LDL-C in patients receiving lipid lowering therapy [8]. The NCEP Adult Treatment Panel (ATP) III recommends non-HDLs as a treatment goal second to LDL-C in patients receiving lipid lowering therapies with TG levels >2.3 mmol/L (200 mg/dL) [9]. The treatment goal for non-HDL-C is 0.8 mmol/L (30 mg/dL) above the LDL-C treatment target. In its recently published recommendations the US National Lipid Association recognized both non-HDL-C and LDL-C as primary treatment targets [10]. Studies have described discordance between non-HDL-C and LDL-C at lower LDL-C and higher triglyceride levels. This may have implications on the treatment goals of high risk patients in particular. Finally, in a recent state of the art review on advanced lipoprotein testing (ALT) in the journal [11], the authors do a excellent job in pointing out the different assays and their pitfalls and rightly conclude that beyond automated immunoassays (immunonephelometry and immunoturbidimetry) for apolipoproteins, much work is needed before these ALT assays can be ushered into the clinical laboratories .

The determination of which estimate of LDL to use should not be based solely on evidence of its value as a risk marker or a treatment goal but also in its effectiveness to actually improve patient outcome whilst concurrently being cost effective in the background of increasing healthcare costs. Hence, whilst the Friedewald equation suffices for the majority of patients and is extremely cost-effective.In patients with diabetes, CVD and other high risk groups with TG levels >2.3mmol/L (200 mg/dL) and Friedwald reported LDL-C<1.8mmol/L (<70 mg/dL) we recommend using either non-HDL cholesterol, direct LDL-C or apoB levels in lieu of the Friedewald equation since in these patient groups who need the most optimum care the Friedewald equation under-reports LDL-C (false positives) and will lull both patient and clinician into thinking they have achieved their targets of a LDL-C<1.8 mmol/L. Laboratorians need to be proactive and disseminate this message in the spirit of optimum patient care globally.


Corresponding author: Ishwarlal Jialal, MD, PhD, FRCPath, DABCC, California North-State University, College of Medicine, Elk Grove, CA, 95757, USA

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

References

1. Catapano AL, Graham I, De Backer G, Wiklund O, Chapman MJ, Drexel H, et al. 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias The Task Force for the Management of Dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) Developed with the special contribution of the European Association for Cardiovascular Prevention and Rehabilitation (EACPR). Atherosclerosis 2016;253:281–344.10.1016/j.atherosclerosis.2016.08.018Search in Google Scholar PubMed

2. Stone NJ, Robinson J, Lichtenstein AH, Merz CNB, Lloyd-Jones D, Blum CB, 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. J Am Coll Cardiol 2013;63:2889–934.10.1161/01.cir.0000437738.63853.7aSearch in Google Scholar PubMed

3. Jialal I, Remaley A. Measurement of LDL-cholesterol in assessment and management of cardiovascular disease risk. Clin Pharmacol Ther 2014;96:20–22.10.1038/clpt.2014.69Search in Google Scholar PubMed

4. Martin SS, Blaha MJ, Elshazly MB, Toth PP, Kwiterovich PO, Blumenthal RS, et al. Comparison of a novel method versus Fridewald equation for estimating LDL-cholesterol levels from the standard lipid profile. J Am Med Assoc 2013;310:2061–8.10.1001/jama.2013.280532Search in Google Scholar PubMed PubMed Central

5. Meeusen JW, Leuke AJ, Jaffe AS, Saenger AK. Validation of a proposed novel equation for estimating LDL-cholesterol. Clin Chem 2014:60:1519–23.10.1373/clinchem.2014.227710Search in Google Scholar PubMed

6. Jialal I, Inn B, Siegel D, Devaraj S. Underestimation of low density lipoprotein-cholesterol with the Friedewald equation versus a direct homogenous low density lipoprotein-cholesterol assay. Lab Med 2017. DOI:10.1093/labmed/lmx023.Search in Google Scholar PubMed

7. Miller WG, Myers GL, Sakurabayashi I, Bachmann LM, Caudill SP, Dziekonski A, et al. Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures. Clin Chem 2010;56:977–86.10.1373/clinchem.2009.142810Search in Google Scholar PubMed PubMed Central

8. Orringer CE. Non-HDL cholesterol, ApoB and LDL particle concentration in coronary heart disease risk prediction and treatment. Clin Lipidol 2013;8:69–79.10.2217/clp.12.89Search in Google Scholar

9. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (AdultTreatment Panel III). J Am Med Assoc 2001;285:2486–97.10.1001/jama.285.19.2486Search in Google Scholar PubMed

10. Jacobson TA, Ito MK, Maki KC, Orringer CE, Bays HE, Jones PH, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1—executive summary. J Clin Lipidol 2014;8:473–88.10.1016/j.jacl.2014.07.007Search in Google Scholar PubMed

11. Clouet-Foraison N, Gaie-Levrel F, Gillery P, Delatour V. Advanced lipoprotein testing for cardiovascular diseases risk assessment: a review of the novel approaches in lipoprotein profiling. Clin Chem Lab Med 2017;55:1453–64.10.1515/cclm-2017-0091Search in Google Scholar PubMed

Published Online: 2017-8-10
Published in Print: 2017-8-28

©2017 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 29.3.2024 from https://www.degruyter.com/document/doi/10.1515/cclm-2017-0639/html
Scroll to top button