Assessment of estimated low-density lipoprotein-cholesterol (LDL-c) equations: a systematic review and meta-analysis

Abstract

Abstract Background Low-density lipoprotein cholesterol (LDL-c) is the major determinant of cardiovascular disease burden. This study critically reviewed the published literature and performed a meta-analysis to compare and to determine which other equations provide the best means of estimating LDL-c in clinical settings. Method English articles indexed in PubMed, Science Open, Biomed central and SpringerLink databases were searched with searches being conducted in or after 2001 up to date. According to the predefined inclusion and exclusion criteria, 22 articles out of the 17,970 retrieved were eligible for quantitative analysis. Data were pooled and meta-analysis performed using a random-effects model, and the results are described as event rates (pooled correlation coefficient). Main body of the abstract All the twelve equations showed positive correlation with the respective direct low-density lipoprotein-cholesterol measurements. The pooled estimates showed a stronger positive correlation between Martin’s low-density lipoprotein-cholesterol equation and the direct low-density lipoprotein-cholesterol measurement [0.96 (95% CI 0.94–0.98)] as compared to Friedewald’s equation and the direct method [0.94 (95% CI 0.92–0.96)]. At triglycerides levels > 400 mg/dl, Martin’s low-density lipoprotein-cholesterol equation established better performance (77.78%) than the Friedewald’s equation. In studies where triglycerides levels > 400 mg/dl were excluded Martin’s low-density lipoprotein-cholesterol equation still established better performance (83.33%) than the Friedewald’s equation. Short conclusion Our data suggest that Martin’s equation showed a better performance than Friedewald equation. Martin’s equation can serve as a more accurate method to estimate low-density lipoprotein cholesterol as compared to Friedewald’s equation especially in situations of the same racial background.