Factors Impacting the Differences Between the Martin/hopkins and Friedewald LDL-C Estimates

Research Objectives: Low-density lipoprotein-cholesterol (LDL-C) remains of utmost clinical importance as a treatment target and primary cholesterol target in the primary prevention of atherosclerotic cardiovascular disease. To address the Friedewald equation measurement inadequacy, the Martin/Hopkins equation was developed to improve the LDL-C estimates. This study aimed to (1) scrutinize the factors influencing the differences between the Martin/Hopkins and Friedewald LDL-C estimates, and (2) ascertain the significant predictive factors using multiple regression and discriminant analysis.

Design: This is an observational study.

Setting: General community.

Participants: Blood lipid measurements were taken from 4,617 noninstitutionalized participants, aged 12 to 80, with triglyceride < 400 mg/dL, as obtained from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) study.

Interventions: N/A

Main Outcome Measures: Blood lipid measurements. The differences between the Martin/Hopkins and Friedewald LDL-C estimates were calculated as the dependent variable. The independent variables included sex, age, race/ethnicity, body mass index (BMI) category, and triglyceride levels.

Results: The differences between Martin/Hopkins and Friedewald LDL-C estimates varied by sex, age, race/ethnicity, BMI, and triglyceride levels (p < 0.001). Discrepancies were more pronounced in males compared to females, increased with age, higher BMI levels, and elevated triglyceride levels (mg/dL) (p < 0.001). Furthermore, disparities were greater in Non-Hispanic Whites and Mexican Americans compared to Non-Hispanic Blacks (p < 0.001). The relationship between the differences and triglyceride concentration revealed a V-shaped distribution, with the minimum turning point occurring at approximately 40 mg/dL. In comparison to the Martin/Hopkins LDL-C estimates, the Friedewald LDL-C estimates overestimated when triglyceride levels were < 100 mg/dL and underestimated when triglyceride levels were >100 mg/dL. The magnitude of differences was -3.6 mg/dL when triglyceride levels were at 20-40 mg/dL, 0.66 mg/dL when triglyceride levels were at 100-120 mg/dL, and gradually increased to 22.6 mg/dL when triglyceride levels were at 380-400 mg/dL. Results from regression analyses identified sex, age, and triglyceride levels as significant factors, with an R squared value of 0.865. Additionally, results from discriminant analysis identified age, race/ethnicity, BMI, and triglyceride levels as significant factors, with a correct classification rate of 84.6%.

Conclusions: Future studies are warranted to redefine LDL-C estimation methods as our treatment targets evolve and novel therapeutics progress.

Author(s) Disclosures: The authors declare no conflict of interest.