What does this research mean for the field?

The Martin-Hopkins method provides more accurate and reliable LDL-C estimation than the Friedewald and NIH2 equations, particularly at low LDL-C levels and in the presence of hypertriglyceridemia. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To evaluate the diagnostic accuracy of the Friedewald, Martin–Hopkins, and National Institutes of Health Equation 2 methods compared against direct enzymatic LDL-C measurement across various lipid profiles.

September 8, 2026Turkish Journal of BiochemistryOpen Access

A comparative analysis of different methods for LDL cholesterol calculation

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Authors

MAMehmet Ağıllı ACAlpaslan Coşar EKEda Karaismailoğlu

Discussion

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Overview

Cross-sectional comparative study demonstrates superior accuracy of the Martin–Hopkins equation over Friedewald and NIH2 in 618 individuals, suggesting improved clinical risk assessment.

Key Points

To evaluate the diagnostic accuracy of the Friedewald, Martin–Hopkins, and National Institutes of Health Equation 2 methods compared against direct enzymatic LDL-C measurement across various lipid profiles.
Fasting blood samples from 618 participants were analyzed on the Roche Cobas c701 platform for total cholesterol, triglycerides, HDL-C, and direct LDL-C, alongside LDL-C estimations via Friedewald, Martin–Hopkins, and NIH2 equations.
Participants were stratified across clinical LDL-C cutoffs and triglyceride concentrations (<400 and ≥400 mg/dL), with performance evaluated using Passing–Bablok regression, Lin’s concordance correlation coefficient, Bland–Altman analysis, and misclassification rates.
All mathematical equations systematically underestimated LDL-C relative to direct enzymatic measurement, with the Martin–Hopkins method demonstrating the lowest bias and closest agreement across thresholds, while Friedewald and NIH2 produced significantly lower values (p<0.05).
In the hypertriglyceridemia subgroup (triglycerides ≥400 mg/dL), concordance declined markedly for Friedewald (CCC=0.824) and NIH2 (CCC=0.878), whereas the Martin–Hopkins method retained high concordance (CCC=0.985) and lower misclassification rates.

Cite This Study

Ağıllı et al. (2026) studied this question.

synapsesocial.com/papers/6a9fd83b58e84d0ff5b47998 https://doi.org/10.1515/tjb-2025-0419

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September 8, 2026Turkish Journal of BiochemistryOpen Access

A comparative analysis of different methods for LDL cholesterol calculation

View Full Paper

Ask AI

Bookmark

Authors

MAMehmet Ağıllı ACAlpaslan Coşar EKEda Karaismailoğlu

Discussion

Member takes

Overview

Cross-sectional comparative study demonstrates superior accuracy of the Martin–Hopkins equation over Friedewald and NIH2 in 618 individuals, suggesting improved clinical risk assessment.

Key Points

To evaluate the diagnostic accuracy of the Friedewald, Martin–Hopkins, and National Institutes of Health Equation 2 methods compared against direct enzymatic LDL-C measurement across various lipid profiles.
Fasting blood samples from 618 participants were analyzed on the Roche Cobas c701 platform for total cholesterol, triglycerides, HDL-C, and direct LDL-C, alongside LDL-C estimations via Friedewald, Martin–Hopkins, and NIH2 equations.
Participants were stratified across clinical LDL-C cutoffs and triglyceride concentrations (<400 and ≥400 mg/dL), with performance evaluated using Passing–Bablok regression, Lin’s concordance correlation coefficient, Bland–Altman analysis, and misclassification rates.
All mathematical equations systematically underestimated LDL-C relative to direct enzymatic measurement, with the Martin–Hopkins method demonstrating the lowest bias and closest agreement across thresholds, while Friedewald and NIH2 produced significantly lower values (p<0.05).
In the hypertriglyceridemia subgroup (triglycerides ≥400 mg/dL), concordance declined markedly for Friedewald (CCC=0.824) and NIH2 (CCC=0.878), whereas the Martin–Hopkins method retained high concordance (CCC=0.985) and lower misclassification rates.

Cite This Study

Ağıllı et al. (2026) studied this question.

synapsesocial.com/papers/6a9fd83b58e84d0ff5b47998 https://doi.org/10.1515/tjb-2025-0419

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