RESUMO
AIMS: The reference method for low-density lipoprotein-cholesterol (LDL-C) is ultracentrifugation. However, this is unsuitable for routine use and therefore direct LDL-C assays and predictive equations are used. In this study, we compared the Friedewald, extended Martin/Hopkins, Sampson/NIH and four other equations to a direct assay. METHODS: We analysed 44 194 lipid profiles from a mixed South African population. The LDL-C predictive equations were compared with direct LDL-C assay and analysed using non-parametric statistics and error grid analysis. RESULTS: Both the extended Martin/Hopkins and Sampson/NIH equations displayed the best correlation with direct LDL-C in terms of desirable bias and total allowable error. The direct LDL-C assay classified 13.9% of patients in the low LDL-C (1.0-1.8 mmol/L) category, in comparison to the extended Martin/Hopkins equation (13.4%), the Sampson equation (14.6%) and the Friedewald equation (16.0%). The Sampson/NIH was least biased in the low LDL-C category (<1.8 mmol/L) and produced the least overall clinically relevant errors compared with the extended Martin/Hopkins and Friedewald equations in the low-LDL-C category. CONCLUSIONS: Our findings suggest only a marginal difference between the extended Martin/Hopkins equation and the Sampson/NIH equation with the use of the Beckman Coulter DxC800 analyser in this population. The results favour the implementation of the Sampson/NIH equation when the Beckman Coulter DxC analyser is used, but the extended Martin/Hopkins may also be safely implemented. Both of these equations performed significantly better than the Friedewald equation. We recommend that patients be monitored using one of these methods and that each laboratory perform its own validation of either equation to ensure continuation and accuracy, and to prevent between-method variation.
RESUMO
OBJECTIVES: Low-density lipoprotein cholesterol (LDL-C) estimation is critical for risk classification, prevention and treatment of atherosclerotic cardiovascular disease (ASCVD). Predictive equations and direct LDL-C are used. We investigated the comparability between the Martin/Hopkins, Sampson, Friedewald and eight other predictive equations on two analysers, to determine whether the equation or analyser influences predicted LDL-C result. METHODS: In two unpaired datasets, 9,995 lipid profiles were analysed by the Abbott Architect and 4,782 by the Roche Cobas analysers. Non-parametric statistics and Bland Altman plots were used to compare LDL-C. RESULTS: On the Abbott analyser; the Martin/Hopkins, Sampson and Friedewald LDL-C were comparable (median bias ≤1.8%) over a range of 1-4.9 mmol/L. On the Roche platform, Martin/Hopkins LDL-C was comparable to Friedewald (median bias 0.3%) but not to Sampson LDL-C (median bias 25%). In patients with LDL-C <1.8 mmol/L and triglycerides (TG) ≤1.7 mmol/L, predicted LDL-C using Abbott reagents was similar between Martin/Hopkins, Sampson and Friedewald equations but not comparable using Roche reagents. Abbott reagents classified 10-20% of patients in the 1.0-1.8 mmol/L range (Martin/Hopkins 13.4%; Sampson 14.5%; Friedewald 16%; direct LDL-C 13.2%). Roche reagents classified 11-30% in the 1.0-1.8 mmol/L range (Martin/Hopkins 23%; Sampson 11%; Friedewald 25%; direct LDL-C 17%). CONCLUSIONS: Performance of predictive equations is influenced by the choice of analyser for total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and TG. Replacement of the Friedewald equation with Martin/Hopkins estimation to improve quality of LDL-C results can be safely implemented across analysers, whereas caution is advised regarding the Sampson equation.