Clinical Center, Department of Laboratory Medicine, National Institutes of Health, Bethesda, Maryland.
Prism Health Dx Inc, Austin, Texas.
JAMA Cardiol. 2020 May 1;5(5):540-548. doi: 10.1001/jamacardio.2020.0013.
Low-density lipoprotein cholesterol (LDL-C), a key cardiovascular disease marker, is often estimated by the Friedewald or Martin equation, but calculating LDL-C is less accurate in patients with a low LDL-C level or hypertriglyceridemia (triglyceride [TG] levels ≥400 mg/dL).
To design a more accurate LDL-C equation for patients with a low LDL-C level and/or hypertriglyceridemia.
DESIGN, SETTING, AND PARTICIPANTS: Data on LDL-C levels and other lipid measures from 8656 patients seen at the National Institutes of Health Clinical Center between January 1, 1976, and June 2, 1999, were analyzed by the β-quantification reference method (18 715 LDL-C test results) and were randomly divided into equally sized training and validation data sets. Using TG and non-high-density lipoprotein cholesterol as independent variables, multiple least squares regression was used to develop an equation for very low-density lipoprotein cholesterol, which was then used in a second equation for LDL-C. Equations were tested against the internal validation data set and multiple external data sets of either β-quantification LDL-C results (n = 28 891) or direct LDL-C test results (n = 252 888). Statistical analysis was performed from August 7, 2018, to July 18, 2019.
Concordance between calculated and measured LDL-C levels by β-quantification, as assessed by various measures of test accuracy (correlation coefficient [R2], root mean square error [RMSE], mean absolute difference [MAD]), and percentage of patients misclassified at LDL-C treatment thresholds of 70, 100, and 190 mg/dL.
Compared with β-quantification, the new equation was more accurate than other LDL-C equations (slope, 0.964; RMSE = 15.2 mg/dL; R2 = 0.9648; vs Friedewald equation: slope, 1.056; RMSE = 32 mg/dL; R2 = 0.8808; vs Martin equation: slope, 0.945; RMSE = 25.7 mg/dL; R2 = 0.9022), particularly for patients with hypertriglyceridemia (MAD = 24.9 mg/dL; vs Friedewald equation: MAD = 56.4 mg/dL; vs Martin equation: MAD = 44.8 mg/dL). The new equation calculates the LDL-C level in patients with TG levels up to 800 mg/dL as accurately as the Friedewald equation does for TG levels less than 400 mg/dL and was associated with 35% fewer misclassifications when patients with hypertriglyceridemia (TG levels, 400-800 mg/dL) were categorized into different LDL-C treatment groups.
The new equation can be readily implemented by clinical laboratories with no additional costs compared with the standard lipid panel. It will allow for more accurate calculation of LDL-C level in patients with low LDL-C levels and/or hypertriglyceridemia (TG levels, ≤800 mg/dL) and thus should improve the use of LDL-C level in cardiovascular disease risk management.
低密度脂蛋白胆固醇(LDL-C)是心血管疾病的一个关键标志物,通常通过 Friedewald 或 Martin 方程进行估算,但在 LDL-C 水平较低或高甘油三酯血症(甘油三酯[TG]水平≥400mg/dL)患者中,计算 LDL-C 的准确性较低。
为 LDL-C 水平较低和/或高甘油三酯血症的患者设计更准确的 LDL-C 方程。
设计、设置和参与者:对 1976 年 1 月 1 日至 1999 年 6 月 2 日期间在国立卫生研究院临床中心就诊的 8656 名患者的 LDL-C 水平和其他脂质测量数据进行了分析,使用 β-量化参考方法(18715 个 LDL-C 测试结果)进行了分析,并将其随机分为大小相等的训练和验证数据集。使用 TG 和非高密度脂蛋白胆固醇作为自变量,采用多元最小二乘法回归法开发了极低密度脂蛋白胆固醇方程,然后将其用于 LDL-C 的第二个方程。使用内部验证数据集和多个外部数据集(β-量化 LDL-C 结果[ n=28715]或直接 LDL-C 测试结果[ n=252888])对方程进行了测试。统计分析于 2018 年 8 月 7 日至 2019 年 7 月 18 日进行。
通过各种准确性测量(相关系数[R2]、均方根误差[RMSE]、平均绝对差[MAD])评估计算的和通过β量化测量的 LDL-C 水平之间的一致性,并评估在 LDL-C 治疗阈值为 70、100 和 190mg/dL 时患者的错误分类百分比。
与β量化相比,新方程比其他 LDL-C 方程更准确(斜率为 0.964;RMSE=15.2mg/dL;R2=0.9648;与 Friedewald 方程相比:斜率为 1.056;RMSE=32mg/dL;R2=0.8808;与 Martin 方程相比:斜率为 0.945;RMSE=25.7mg/dL;R2=0.9022),特别是对于高甘油三酯血症患者(MAD=24.9mg/dL;与 Friedewald 方程相比:MAD=56.4mg/dL;与 Martin 方程相比:MAD=44.8mg/dL)。新方程可以准确计算 TG 水平高达 800mg/dL 的患者的 LDL-C 水平,与 Friedewald 方程在 TG 水平低于 400mg/dL 时一样准确,并且当将高甘油三酯血症(TG 水平为 400-800mg/dL)患者分为不同的 LDL-C 治疗组时,错误分类的患者减少了 35%。
与标准脂质组相比,新方程可以由临床实验室轻松实施,而且不会增加任何成本。它将能够更准确地计算 LDL-C 水平较低和/或高甘油三酯血症(TG 水平,≤800mg/dL)患者的 LDL-C 水平,从而应改善 LDL-C 水平在心血管疾病风险管理中的应用。