Liver production of lipoproteins and its lipid content, particularly in the case of VLD-C, is markedly altered in patients with FCHL [5]. Recently, our group performed an external validation of Martin’s formula in FCHL demonstrating an improved performance for this method compared to apolipoprotein B and non-HDL cholesterol in concordance and misclassification of treatment goals [14]. Despite the utility of Martin’s formula, the pathophysiology of FCHL with a concurrent insulin resistant state, increased lipolysis and variable expression of triglyceride-variants in this condition offers variable increases in triglyceride concentration, diminishing the utility of this formula as LDL-C is modified by treatment in the setting of hypertriglyceridemia and mixed dyslipidaemia. Furthermore, FCHL patients tend to have more dysfunctional atherogenic lipoproteins and thus a higher incidence of cardiovascular disease, which might require higher intensity treatment and would benefit from improved LDL-C estimation [7, 15].
The novel method proposed by Sampson et al. offers an attractive alternative to estimate VLDL-C and LDL-C in the setting of lipid profile fluctuations, particularly in cases of hypertriglyceridemia and lowering LDL-C for treatment reassessment. This allows for more precise assessment of cardiovascular risk management in FCHL by improving prediction of VLDL-C, the most variable component in LDL-C estimation, whilst also potentially allowing for more accurate estimation of remnant cholesterol [16]. As an illustrative example of the utility of the different LDL-C formulas, consider the case of a patient with lipid profile within our study, who had triglycerides at 1986 mg/dL, total cholesterol 299 mg/dL and HDL-C 21 mg/dL. LDL-C calculated using VLDL-C measurement was 41.46 mg/dL, whereas LDL-C estimated with the 3 formulas were LDL-F − 119.2 mg/dL, LDL-M − 18.418 mg/dL and LDL-S 39.311 mg/dL. In this context, LDL-C estimation with Friedewald’s and Martin’s formulas result in a negative value that it is not plausible, whilst Sampson’s equation performed a value closer to the LDL-C estimated with VLDL-C measurement by ultracentrifugation method.
This result demonstrates that VLDL-C and LDL-C estimated using Sampson’s equation is a better estimator over the traditional Friedewald’s and Martin’s formulas, showing a significantly higher correlation and agreement with VLDL-C measured by ultracentrifugation and LDL-C estimated using these VLDL-C measures in subjects with FCHL. Even in the setting of hypertriglyceridemia, which is frequent in FCHL and might significantly fluctuate through the course of the disease, Sampson’s equation is still significantly better than other formulas. When analysing FCHL phenotypes, LDL-C estimated using Sampson’s and Friedewald’s equations perform similarly in the setting of isolated hypercholesterolemia; however, Sampson’s formula had a better performance in the setting of mixed dyslipidaemia. Population-based research in the US and Korea has shown that improved LDL-C estimation might offer more precise assessment of treatment goals and allow for better informed treatment intensification which might be particularly helpful in FCHL [17, 18]. Even though Sampson’s method might underperform with triglyceride levels > 800 mg/dL, our data shows that it still holds adequate performance and is superior to Martin’s and Friedewald’s methods, indicating a use in phenotypes of isolated hypertriglyceridemia with low LDL-C values.
Therefore, improving the LDL-C estimation in a setting of hypertriglyceridemia or mixed dyslipidaemia might improve the identification of subjects under lipid-lowering treatment who would benefit to add a second drug to achieve the LDL-C goal. Indeed, achieving lower LDL-C levels is associated with a higher rate of atherosclerotic plaque regression compared to patients with more elevated LDL-C [19]. Then, the combination of lipid-lowering drugs in patients with insufficient LDL-C reduction or with high residual risk reduces the progression of coronary atherosclerosis and the risk of coronary events [19].
Apo B is highly correlated with LDL-C and non-HDL-C levels; however, Apo B is more accurate as a marker of cardiovascular risk over cholesterol and triglyceride measures, with several studies confirming these findings [20,21,22,23]. Therefore, by evaluating the correlation between Apo B levels and LDL-C estimated by these three methods, LDL-C estimated by Sampson’s equation showed the highest correlation in mixed dyslipidaemia, even for triglycerides > 800 mg/dL compared to Martin’s formula, which had shown an adequate correlation in patients with mixed dyslipidaemia and hypertriglyceridemia in a previous study [9]. Also, the performance for assessing concordance in lipid target goals (Apo B < 80 mg/dL and < 65 mg/dL) and Martin’s equation showed consistently improved concordances and AUROC compared to the other methods. However, for a given value of Apo B < 50th percentile, levels of LDL-C and non-HDL-C may range from the 25th to 75th percentile and the values will be discordant and, therefore will predict cardiovascular risk differently [24, 25]. Also, the limited number of patients under statin treatment conferred a limited number of patients with low levels of Apo B and, in this case the concordance observed between lipid target goals (Apo B < 65 and < 80 mg/dL) and LDL-C should be evaluated with reservation.
Strengths and limitations
The study had some strengths and limitations. First, this study used VLDL-C estimation assessed using the gold standard, VLDL-C measured by Ultracentrifugation, and evaluated the performance of these equations compared to VLDL-C and LDL-C in a population with high variability in the lipid profile. Potential limitations of this approach include the non-direct method to measure LDL-C or remnant lipoproteins; to overcome this, LDL-C was calculated using VLDL-C measures by ultracentrifugation to approximate a gold-standard for comparative assessments. Similarly, the limited number of subjects with low LDL-C which is an area specifically designed for Sampson’s formula and might improve its performance compared to other methods; this may be particularly helpful whilst following up treatment efficacy and should be evaluated for FCHL and other conditions with concomitant hypertriglyceridemia. However, LDL-C estimation using Sampson’s formula is markedly more useful than traditional methods in mixed dyslipidaemia, highlighting a potential application of this formula along with Apo B assessment for cardiovascular risk management.