Kilpatrick Eric S, Kallner Anders, Atkin Stephen L, Sathyapalan Thozhukat
Division of Clinical Biochemistry, Sidra Medicine, Doha, Qatar.
Department of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden.
Ann Clin Biochem. 2025 May;62(3):184-190. doi: 10.1177/00045632241305936. Epub 2024 Dec 5.
BackgroundThe Sampson-NIH and Martin-Hopkins low-density lipoprotein cholesterol (LDL-C) equations are advocated as being superior to the Friedewald calculation. However, their mathematical complexity means they may have different biological and analytical variation when tracking LDL-C in the same patient. This study has established the biological variation (BV) of calculated and directly measured LDL-C (dLDL-C) in patients taking equivalent doses of a long (atorvastatin) and short (simvastatin) half-life statin. It also modelled how analytical imprecision might add to these BVs.MethodsIn a crossover study of lipid BV involving 26 patients with type 2 diabetes (T2DM) initially taking either simvastatin 40 mg or atorvastatin 10 mg, fasting lipids were measured 10 times over 5 weeks after a 3 month run-in. The same procedure was then followed for the alternate statin. Outlier removal and CV-ANOVA established the BV of dLDL and each formula. Analytical measurement uncertainty was estimated from 6 months of real-world data.ResultsThe intra-individual BV of dLDL-C measurement was considerably lower with atorvastatin than simvastatin (CV 1.3%(95% CI 1.1-1.5%) vs. 11.1%(10.2-12.2%), respectively). No equation could distinguish this difference (Friedewald 11.0%(95% CI 10.0-12.1%) vs. 12.9%(11.8-14.2%), Sampson-NIH 10.4%(9.5-11.5%) vs. 11.7% (10.7-12.8%) and Martin-Hopkins 9.3%(8.5-10.3%) vs. 11.3%(10.3-12.4%)). Real-world analytical CVs were 2.6% (Sampson-NIH), 2.6% (Martin-Hopkins) 2.8% (Friedewald) and 2.0% (dLDL-C).ConclusionsInherent biological LDL-C variability using these formulae is substantially greater than direct measurement in T2DM patients taking atorvastatin. Typical analytical imprecision was also greater. Together, this may fundamentally limit these equations' ability to track true LDL-C changes in patients taking popular statin treatments.
背景
桑普森-美国国立卫生研究院(Sampson-NIH)和马丁-霍普金斯(Martin-Hopkins)低密度脂蛋白胆固醇(LDL-C)方程被认为优于弗里德瓦尔德(Friedewald)计算法。然而,其数学复杂性意味着在追踪同一患者的LDL-C时,它们可能存在不同的生物学和分析变异性。本研究确定了服用等效剂量的长效(阿托伐他汀)和短效(辛伐他汀)半衰期他汀类药物的患者中,计算得出的LDL-C与直接测量的LDL-C(dLDL-C)的生物学变异(BV)。它还模拟了分析不精密度可能如何增加这些BV。
方法
在一项涉及26例2型糖尿病(T2DM)患者的脂质BV交叉研究中,患者最初服用40mg辛伐他汀或10mg阿托伐他汀,在3个月的导入期后,于5周内测量10次空腹血脂。然后对另一种他汀类药物采用相同程序。通过去除异常值和CV-方差分析确定dLDL和每个公式的BV。根据6个月的实际数据估计分析测量不确定度。
结果
阿托伐他汀组dLDL-C测量的个体内BV显著低于辛伐他汀组(CV分别为1.3%(95%CI 1.1-1.5%)和11.1%(10.2-12.2%))。没有一个方程能够区分这种差异(弗里德瓦尔德计算法为11.0%(95%CI 10.0-12.1%)对12.9%(11.8-14.2%),桑普森-NIH方程为10.4%(9.5-11.5%)对11.7%(10.7-12.8%),马丁-霍普金斯方程为9.3%(8.5-10.3%)对11.3%(10.3-12.4%))。实际分析CV分别为2.6%(桑普森-NIH方程)、2.6%(马丁-霍普金斯方程)、2.8%(弗里德瓦尔德计算法)和2.0%(dLDL-C)。
结论
在服用阿托伐他汀的T2DM患者中,使用这些公式计算得出的LDL-C固有生物学变异性显著大于直接测量值。典型的分析不精密度也更高。两者共同作用,可能从根本上限制这些方程追踪服用常用他汀类药物治疗患者真实LDL-C变化的能力。