Wilkes E H, Whitlock M J, Williams E L
Department of Clinical Biochemistry, North West London Pathology, Imperial College Healthcare NHS Trust, Charing Cross Hospital, Fulham Palace Road, London W6 8RF, United Kingdom.
J Mass Spectrom Adv Clin Lab. 2021 Jun 8;20:42-47. doi: 10.1016/j.jmsacl.2021.06.001. eCollection 2021 Apr.
Heavy-labelled internal standard (IS) compounds are commonly used in liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays to control for stochastic and systematic variation. Identifying samples that suffer from unwanted variation is critically important in order to avoid factitiously inaccurate results. Current approaches for outlier detection typically employ arbitrary thresholds and ignore systematic drift. To improve this, we applied robust linear mixed-effects models (LMMs) to capture the within- and between-run variability in IS signal and generate data-driven acceptance ranges for routine use. Data from in-house LC-MS/MS assays for 25-hydroxyvitamin D and D and prednisolone were retrospectively collected. The variation in the percentage deviation of the internal standard area from the mean of the calibrators was modelled through the use of robust LMMs. The fitted LMMs revealed significant positive drift in IS signal over the analytical runs for vitamin D, with slope coefficients of 0.118 (95% CI: 0.098, 0.138) and 0.192 (0.168, 0.215) for D and D, respectively. In contrast, the models for prednisolone demonstrated a significant negative drift in IS signal, with a slope coefficient of -0.164 (-0.297, -0.036). Non-parametric, cluster bootstrap resampling enabled us to define acceptance ranges for use in future assays. Here, we have described a computational approach to extensively characterise the variation in IS signal in routinely-performed LC-MS/MS assays. This approach facilitates a robust quality assessment of IS outliers in routine practice and thus has the potential to improve patient safety. Importantly, this approach is applicable to other MS assays where linear variation in IS signal is observed.
重标记内标（IS）化合物常用于液相色谱 - 串联质谱（LC - MS/MS）分析中，以控制随机和系统变异。识别存在不必要变异的样本对于避免人为造成的不准确结果至关重要。当前的异常值检测方法通常采用任意阈值并忽略系统漂移。为了改进这一点，我们应用稳健线性混合效应模型（LMMs）来捕捉IS信号在批内和批间的变异性，并生成数据驱动的接受范围以供日常使用。回顾性收集了来自内部LC - MS/MS分析25 - 羟基维生素D、维生素D和泼尼松龙的数据。通过使用稳健LMMs对内部标准面积相对于校准品均值的百分比偏差变化进行建模。拟合的LMMs显示，在维生素D的分析批次中，IS信号存在显著的正向漂移，维生素D和维生素D的斜率系数分别为0.118（95%置信区间：0.098，0.138）和0.192（0.168，0.215）。相比之下，泼尼松龙的模型显示IS信号存在显著的负向漂移，斜率系数为 -0.164（-0.297，-0.036）。非参数聚类自举重采样使我们能够定义未来分析中使用的接受范围。在这里，我们描述了一种计算方法，以广泛表征常规进行的LC - MS/MS分析中IS信号的变化。这种方法有助于在常规实践中对IS异常值进行稳健的质量评估，从而有可能提高患者安全性。重要的是，这种方法适用于观察到IS信号存在线性变化的其他质谱分析。
