LDL-C calculated by Friedewald, Martin-Hopkins, or NIH equation 2 versus beta-quantification: pooled alirocumab trials

Accurate assessment of LDL-C levels is important, as they are often used for treatment recommendations. For many years, plasma LDL-C levels were calculated using the Friedewald equation, but there are limitations to this method compared with direct measurement via beta-quantification (BQ). Here, we assessed differences between the Friedewald, Martin-Hopkins, and NIH equation 2 methods of calculating LDL-C and the “gold standard” BQ method using pooled phase 3 data with alirocumab. All randomized patients were included irrespective of the treatment arm (n = 6,122). We compared pairs of LDL-C values (n = 17,077) determined by each equation and BQ. We found that BQ-derived LDL-C values ranged from 1 to 397 mg/dl (mean 90.68 mg/dl). There were strong correlations between Friedewald-calculated, Martin-Hopkins–calculated, and NIH equation 2–calculated LDL-C with BQ-determined LDL-C values (Pearson's correlation coefficient = 0.985, 0.981, and 0.985, respectively). Importantly, for BQ-derived LDL-C values ≥70 mg/dl, only 3.2%, 1.4%, and 1.8% of Friedewald-calculated, Martin-Hopkins–calculated, and NIH equation 2–calculated values were <70 mg/dl, respectively. When triglyceride (TG) levels were <150 mg/dl, differences between calculated and BQ-derived LDL-C values were minimal, regardless of the LDL-C level (<40, <55, or <70 mg/dl). However, when TG levels were >150 mg/dl, NIH equation 2 provided greater accuracy than Friedewald or Martin-Hopkins. When TGs were >250 mg/dl, inaccuracies were seen with all three methods, although NIH equation 2 remained the most accurate. In conclusion, LDL-C calculated by any of the three methods can guide treatment decisions for most patients, including those treated with proprotein convertase subtilisin/kexin type 9 inhibitors.