Comparative performance of equations to estimate low-density lipoprotein cholesterol levels and cardiovascular disease incidence: The ATTICA study (2002-2022).

Accurate estimation of low-density lipoprotein cholesterol (LDL-C) is important for monitoring cardiovascular disease (CVD) risk and guiding lipid-lowering therapy. This study aimed to evaluate the magnitude of discordance of LDL-C levels calculated by different equations and its effect on CVD incidence. The study sample consisted of 2354 CVD-free individuals (49% males, mean age 45 ± 14 years); 1600 were re-evaluated at 10 years and 1570 at 20 years. LDL-C was estimated using the Friedewald, Martin/Hopkins, and Sampson equations. Participants were categorized as discordant if estimated LDL-C was below the CVD-risk specific cut-off for one equation and equal/above for its comparator. The Friedewald and Martin/Hopkins equations presented a similar performance in estimating LDL-C; however, both yielded lower values compared to the Sampson. In all pairwise comparisons, differences were more pronounced at lower LDL-C levels, while the Friedewald equation significantly underestimated LDL-C in hypertriglyceridemic participants. Discordance was evident in 11% of the study population, and more specifically 6%, 22%, and 20% for Friedewald versus Martin/Hopkins, Friedewald versus Sampson and Martin/Hopkins versus Sampson equations, respectively. Among discordant participants, median (1st, 3rd quartile) difference in LDL-C was -4.35 (-10.1, 1.95), -10.6 (-12.3, -9.53) and -11.3 (-11.9, -10.6) mg/dL for Friedewald versus Martin/Hopkins, Friedewald versus Sampson and Martin/Hopkins versus Sampson equations, respectively. The 10- and 20-year CVD survival model that included LDL-C values of the Martin-Hopkins equation outperformed the predictive ability of those based on the Friedewald or Sampson equations. Significant differences in estimated LDL-C exist among equations, which may result in LDL-C underestimation and undertreatment.