Comparative Evaluation of 24 LDL-C Estimation Equations Against Direct Assays in Two Independent Cohorts

Background: Low-density lipoprotein cholesterol (LDL-C) is essential in diagnosing and managing dyslipidemias. While direct assays are faster than the reference beta-quantification method, many labs continue using the Friedewald (FW) equation, despite its limitations. Methods: Two large datasets were analyzed: 10,174 hospital samples (Cobas/Roche) and 21,091 private lab samples (Alinity/Abbott). Various literature-based LDL-C equations were compared, focusing on FW, Sampson (SN), and Martin-Hopkins (MH). Direct LDL-C served as the reference. Evaluation metrics included bias and classification accuracy. Results: In samples with triglycerides < 400 mg/dL, several lesser-known equations showed acceptable bias (±5%), outperforming FW, SN, and MH, which had biases from -7.4% to -4.9%. Classification accuracy was higher with equations like Vujovic (up to 82.5%), compared to FW (65.8%), SN (73.1%), and MH (72.4%). The Vujovic equation showed minimal bias across triglyceride levels and the highest net gain in correct classification (3.4% and 1.57%). Conclusions: Multiple lesser-known LDL-C formulas outperformed widely used ones. The Vujovic equation yielded the best results, but the limited net clinical improvement suggests that replacing Friedewald may not be urgently necessary.