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基于改良 Sampson-NIH 方程的 LDL-C 估算方法。

An improved method for estimating low LDL-C based on the enhanced Sampson-NIH equation.

机构信息

Clinical Center, Department of Laboratory Medicine, National Institutes of Health, Bethesda, MD, USA.

Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.

出版信息

Lipids Health Dis. 2024 Feb 8;23(1):43. doi: 10.1186/s12944-024-02018-y.

Abstract

BACKGROUND

The accurate measurement of Low-density lipoprotein cholesterol (LDL-C) is critical in the decision to utilize the new lipid-lowering therapies like PCSK9-inhibitors (PCSK9i) for high-risk cardiovascular disease patients that do not achieve sufficiently low LDL-C on statin therapy.

OBJECTIVE

To improve the estimation of low LDL-C by developing a new equation that includes apolipoprotein B (apoB) as an independent variable, along with the standard lipid panel test results.

METHODS

Using β-quantification (BQ) as the reference method, which was performed on a large dyslipidemic population (N = 24,406), the following enhanced Sampson-NIH equation (eS LDL-C) was developed by least-square regression analysis: [Formula: see text] RESULTS: The eS LDL-C equation was the most accurate equation for a broad range of LDL-C values based on regression related parameters and the mean absolute difference (mg/dL) from the BQ reference method (eS LDL-C: 4.51, Sampson-NIH equation [S LDL-C]: 6.07; extended Martin equation [eM LDL-C]: 6.64; Friedewald equation [F LDL-C]: 8.3). It also had the best area-under-the-curve accuracy score by Regression Error Characteristic plots for LDL-C < 100 mg/dL (eS LDL-C: 0.953; S LDL-C: 0.920; eM LDL-C: 0.915; F LDL-C: 0.874) and was the best equation for categorizing patients as being below or above the 70 mg/dL LDL-C treatment threshold for adding new lipid-lowering drugs by kappa score analysis when compared to BQ LDL-C for TG < 800 mg/dL (eS LDL-C: 0.870 (0.853-0.887); S LDL-C:0.763 (0.749-0.776); eM LDL-C:0.706 (0.690-0.722); F LDL-C:0.687 (0.672-0.701). Approximately a third of patients with an F LDL-C < 70 mg/dL had falsely low test results, but about 80% were correctly reclassified as higher (≥ 70 mg/dL) by the eS LDL-C equation, making them potentially eligible for PCSK9i treatment. The M LDL-C and S LDL-C equations had less false low results below 70 mg/dL than the F LDL-C equation but reclassification by the eS LDL-C equation still also increased the net number of patients correctly classified.

CONCLUSIONS

The use of the eS LDL-C equation as a confirmatory test improves the identification of high-risk cardiovascular disease patients, who could benefit from new lipid-lowering therapies but have falsely low LDL-C, as determined by the standard LDL-C equations used in current practice.

摘要

背景

准确测量低密度脂蛋白胆固醇(LDL-C)对于利用新型降脂疗法(如 PCSK9 抑制剂(PCSK9i))非常重要,这些疗法适用于他汀类药物治疗后 LDL-C 水平仍未充分降低的高危心血管疾病患者。

目的

通过开发一种新的方程来提高低 LDL-C 的估计值,该方程将载脂蛋白 B(apoB)作为一个独立变量,同时结合标准脂质面板测试结果。

方法

使用β定量(BQ)作为参考方法,对大量血脂异常人群(N=24406)进行了分析,通过最小二乘回归分析得出了以下增强的 Sampson-NIH 方程(eS LDL-C):[公式:见文本]

结果

基于回归相关参数和与 BQ 参考方法的平均绝对差值(mg/dL),eS LDL-C 方程是最适合广泛 LDL-C 值的最准确方程(eS LDL-C:4.51,Sampson-NIH 方程[S LDL-C]:6.07;扩展 Martin 方程[eM LDL-C]:6.64;Friedewald 方程[F LDL-C]:8.3)。它还具有通过回归误差特征图评估 LDL-C<100mg/dL 时最佳的曲线下面积准确性评分(eS LDL-C:0.953;S LDL-C:0.920;eM LDL-C:0.915;F LDL-C:0.874),并且在比较 BQ LDL-C 时,对于 TG<800mg/dL 的患者,eS LDL-C 是用于将患者分类为低于或高于添加新降脂药物的 70mg/dL LDL-C 治疗阈值的最佳方程(eS LDL-C:0.870(0.853-0.887);S LDL-C:0.763(0.749-0.776);eM LDL-C:0.706(0.690-0.722);F LDL-C:0.687(0.672-0.701))。大约三分之一的 F LDL-C<70mg/dL 的患者的检测结果偏低,但约 80%的患者通过 eS LDL-C 方程被正确地重新分类为更高(≥70mg/dL),这使得他们可能有资格接受 PCSK9i 治疗。与 F LDL-C 方程相比,M LDL-C 和 S LDL-C 方程在 70mg/dL 以下的假低值结果较少,但 eS LDL-C 方程的重新分类仍增加了正确分类的患者数量。

结论

使用 eS LDL-C 方程作为确认性测试,可以提高高危心血管疾病患者的识别能力,这些患者可能受益于新型降脂疗法,但标准 LDL-C 方程检测结果偏低。

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