A new formula for estimation of low-density lipoprotein cholesterol in an ethnic Chinese population

Clin Chem Lab Med. 2015 Oct;53(11):1871-9. doi: 10.1515/cclm-2014-1029.

Abstract

Background: Low-density lipoprotein cholesterol (LDL-C) is an established risk factor for cardiovascular disease and is usually estimated by the Friedewald formula (FF) calculated from three parameters, namely, total cholesterol (TC), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C). We aimed to develop a new and simple formula (NF) for LDL-C estimation.

Methods: This cross-sectional study enrolled two study populations (a testing group, n=16,749, and a validation group, n=4940). Linear regression analysis was used in the testing group to investigate the association between measured LDL-C (mLDL-C) and TC concentration, and was verified in the validation group.

Results: The NF yielded an estimated LDL-C (eLDL-C) equal to 0.75 × total cholesterol-0.6465 (mmol/L). For the subjects with TC between 2.58 and 7.74 mmol/L, the difference between mLDL-C and eLDL-C using the NF was less than that from the FF (testing group: -0.04 to -0.20 vs. -0.28 to -0.38 mmol/L; validation group: 0.01 to -0.12 vs. -0.23 to -0.30 mmol/L; p<0.001, respectively). The predictability of the NF was not inferior to that of the FF in subjects with different triglyceride and HDL-C concentrations, and was not affected by diabetes diagnosis and statin use. However, the NF performed similar to or worse than the FF at TC concentrations <2.58 mmol/L and >7.74 mmol/L, respectively.

Conclusions: In the Chinese population, the accuracy of eLDL-C measurement with the NF was better than that with the FF, especially in subjects with TC levels between 2.58 and 7.74 mmol/L. The NF is simple and may be used for screening as well as for follow-up of patients on lipid lowering agents.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Asian People*
  • China / ethnology
  • Cholesterol, LDL / blood*
  • Cross-Sectional Studies
  • Ethnicity*
  • Female
  • Humans
  • Linear Models
  • Male
  • Middle Aged

Substances

  • Cholesterol, LDL