Gcingca, Thando A

Abstract Background β-Quantification (BQ) is the reference method for low-density lipoprotein cholesterol (LDL-C) determination. It is not widely available, making it challenging for laboratories to assess the accuracy of LDL-C methods. Our goal was to develop an indirect graphical approach for comparing LDL-C test results to the BQ reference method. Methods BQ results from Mayo Medical Laboratories (n = 39 969) and the National Institutes of Health (n = 17 825) were used to investigate the interrelationships between lipid panel tests. A plot of LDL-C/non high-density lipoprotein cholesterol (nonHDL-C) vs (triglyceride (TG)/nonHDL-C)0.5 (lipid ratio plot) resulted in a negative linear regression line (y = −34.2x + 115). Based on simulation analysis, the minimum sample size for calculating its slope and intercept with a coefficient of variation of about 7.5% was 80. Results The regression lines for the lipid ratio plot of LDL-C calculated by the Sampson–NIH (y = −37.6x + 118) and enhanced Sampson–NIH (y = −33.1x + 116) equations closely overlapped with the BQ method. In contrast, the Martin–Hopkins equation showed a positive bias with an increasing TG/nonHDL-C ratio and exceeded the recommended bias limit of 4% on hypertriglyceridemic samples (y = −25.5x + 107). The Friedewald equation showed an even larger negative bias with hypertriglyceridemia (y = −47.5x + 126). Lipid ratio plots of the Roche direct assay revealed a fixed positive bias of approximately 4% (y = −33.9x + 120), whereas a much larger proportional positive bias was observed with increasing triglycerides for the Beckman direct assay (y = −14.6x + 97.8). Conclusions The lipid ratio plot is a simple graphical approach that can be readily performed by clinical laboratories for investigating the accuracy of LDL-C assays by calculation methods or direct assays.

Abstract Background Beta-quantification (BQ) is the reference method for LDL-C but is not widely available. It is difficult, therefore, for clinical laboratories to independently assess the accuracy of their methods for either calculating or directly measuring LDL-C. Our goal was to investigate if an interrelationship between the tests in the standard lipid panel could be used to compare the performance of different LDL-C methods against BQ, specifically in samples with hypertriglyceridemia, a major cause of bias for LDL-C testing. Methods BQ results from Mayo Medical Labs (n=39,667) and the NIH (n=18,338) were used to identify a linear relationship by least-squares regression analysis between lipid panel test results and LDL-C to facilitate a statistical comparison between different LDL-C methods. Results It is well established that the number of VLDL particles increases as TG increases, because VLDL is the main carrier of TG. As a consequence, the ratio of LDL-C to non-HDL-C is inversely related to TG, which can be made linear by taking the square root of TG (Figure). Nearly identical regression equations were found for this relationship, using two different BQ datasets. When LDL-C was calculated by either Sampson equation, the LDL-C/non-HDL-C regression lines nearly overlapped with the one for BQ. In contrast, the Martin equation showed a positive bias with increasing TG, whereas the Friedewald equation showed a negative bias, consistent with past reports on their LDL-C biases with hypertriglyceridemia. In the UKBiobank, the Beckman direct LDL-C showed a positive bias for TG, which was confirmed in CAP proficiency test surveys. By simulation analysis, approximately 80 samples with high (>200 mg/dL) and low (<100 mg/dL) TG is statistically sufficient to assess if the LDL-C/non-HDL-C regressions lines of LDL-C methods differ from BQ. Conclusions The LDL-C/non-HDL-C ratio method is a simple way to examine LDL-C methods for bias on hypertriglyceridemic samples.