Low-density lipoprotein cholesterol (LDL-C) is a central biomarker in cardiovascular risk assessment and is the primary therapeutic target in lipid-lowering therapy. Although direct measurement of LDL-C is possible, it is costly, not universally available and may lack precision at low concentrations. Therefore, most clinical laboratories estimate LDL-C using mathematical formulas but there are currently no national guidelines to provide evidence-based recommendations on lipid testing and reporting for UK laboratories.

Historically, the Friedewald equation has been the standard method since its introduction in 1972. However, growing recognition of its limitations – particularly in patients with hypertriglyceridaemia or low LDL-C – has led to the development of improved formulas. Among them, the Sampson-NIH equation, introduced by Sampson et al. (2020),¹ has been increasingly adopted because of its superior accuracy across a wider range of lipid profiles.

In 2025, a joint statement² from the Association of Laboratory Medicine recommended use of the Sampson-NIH calculation for LDL-c estimation. 2025 also saw the publication of a modified Sampson equation,³ which is said to be more accurate at lower LDL concentrations.

A UK national audit questionnaire was recently distributed to assess how many UK laboratories are using which method.

The Friedewald formula estimates LDL-C as:

LDL-C = TC – HDL-C – (TG/2.2) mmol/L

Although widely used, the Friedewald formula has several major limitations. First, it has inaccuracy at high triglyceride (TG) levels. There is significant error when TG >4.5 mmol/L, and it is not recommended for use at high TG concentrations. The equation also has poor performance at low LDL-C levels, which is increasingly important as modern lipid-lowering therapies (e.g. PCSK9 inhibitors) produce LDL-C levels <1 mmol/L.

The equation assumes a fixed VLDL-C to TG ratio. The TG:VLDL-C relationship varies between individuals and changes with metabolic states (e.g. diabetes, obesity, sepsis). There is also the inability to use non-fasting samples reliably – Friedewald accuracy drops when post-prandial TG levels rise. These issues reduce clinical reliability, particularly in the modern lipid era.

The Sampson equation was developed using a large, diverse dataset and advanced regression modelling that accounts for non-linear relationships between lipoprotein components. The equation is as follows:

LDL-C = TC/0.948 – HDL-C/0.971 – (TC/8.56 + (TG × non-HDL-C)/2140 – (TG²)/16100) – 9.44

Improved accuracy across a wide TG range

Sampson’s equation maintains acceptable accuracy even with TG up to 9 mmol/L, almost double the limit of Friedewald. This makes it much more useful in:

• metabolic syndrome
• diabetes
• obesity
• alcohol-related hypertriglyceridaemia
• acute illness where TG is often elevated.

Better estimation at low LDL-C levels

Sampson’s formula is significantly more accurate when LDL-C < 1.8 mmol/L, reducing misclassification of cardiovascular risk and ensuring appropriate treatment decisions.

More accurate VLDL-C estimation

The formula does not assume a simple TG/2.2 ratio. Instead, it models VLDL cholesterol using a more sophisticated approach that captures physiological variability.

Performs well with fasting and non-fasting samples

Modern practice increasingly uses non-fasting lipid profiles. Sampson’s method is less affected by post-prandial TG increases, making it more compatible with current clinical guidelines.

Reduced need for direct LDL assays

Direct LDL-C methods are more expensive, show significant inter-assay variability and may be unreliable in dyslipidemia or abnormal lipoprotein patterns. Sampson’s equation provides an accurate alternative, often outperforming direct assays.

Other formulas, such as the Martin–Hopkins method, also improve upon Friedewald by using adjustable TG:VLDL ratios. However, Martin–Hopkins requires large population-based lookup tables. Sampson is arguably simpler to implement mathematically and performs better in very high TG levels and in severe dyslipidemia. Clinical laboratories, therefore, may prefer the Sampson formula for automated calculation.

Using an inaccurate LDL-C formula can lead to under-treatment of high-risk patients, over-treatment and unnecessary use of expensive therapies. Inaccurate formulas can also cause misclassification in research studies, and incorrect audit or population health data

Adopting Sampson’s equation improves risk stratification and treatment decisions, especially in secondary prevention patients with aggressive LDL-C targets, inpatients with inflammatory or metabolic conditions, and populations with high rates of metabolic disease.

Sampson’s equation represents a significant advancement in LDL-C estimation. It addresses the long-recognised limitations of the Friedewald formula and provides more accurate results across diverse clinical situations. As lipid management strategies become more intensive and personalised, the use of a reliable LDL-C calculation method such as Sampson’s is essential for high-quality care, improved laboratory reporting and better cardiovascular outcomes.

References available on our website.

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