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Abstract：
Reliable quantification in biological systems of endogenous low- and high-molecular substances, drugs and their metabolites, is of particular importance in diagnosis and therapy, and in basic and clinical research. The analytical characteristics of analytical approaches have many differences, including in core features such as accuracy, precision, specificity, and limits of detection (LOD) and quantitation (LOQ). Several different mathematic approaches were developed and used for the comparison of two analytical methods applied to the same chemical compound in the same biological sample. Generally, comparisons of results obtained by two analytical methods yields different quantitative results. Yet, which mathematical approach gives the most reliable results? Which mathematical approach is best suited to demonstrate agreement between the methods, or the superiority of an analytical method A over analytical method B? The simplest and most frequently used method of comparison is the linear regression analysis of data observed by method A (y) and the data observed by method B (x): y = α + βx. In 1986, Bland and Altman indicated that linear regression analysis, notably the use of the correlation coefficient, is inappropriate for method-comparison. Instead, Bland and Altman have suggested an alternative approach, which is generally known as the Bland-Altman approach. Originally, this method of comparison was applied in medicine, for instance, to measure blood pressure by two devices. The Bland-Altman approach was rapidly adapted in analytical chemistry and in clinical chemistry. To date, the approach suggested by Bland-Altman approach is one of the most widely used mathematical approaches for method-comparison. With about 37,000 citations, the original paper published in the journal The Lancet in 1986 is among the most frequently cited scientific papers in this area to date. Nevertheless, the Bland-Altman approach has not been really set on a quantitative basis. No criteria have been proposed thus far, in which the Bland-Altman approach can form the basis on which analytical agreement or the better analytical method can be demonstrated. In this article, the Bland-Altman approach is re-valuated from a quantitative bioanalytical perspective, and an attempt is made to propose acceptance criteria. For this purpose, different analytical methods were compared with Gold Standard analytical methods based on mass spectrometry (MS) and tandem mass spectrometry (MS/MS), i.e., GC-MS, GC-MS/MS, LC-MS and LC-MS/MS. Other chromatographic and non-chromatographic methods were also considered. The results for several different endogenous substances, including nitrate, anandamide, homoarginine, creatinine and malondialdehyde in human plasma, serum and urine are discussed. In addition to the Bland-Altman approach, linear regression analysis and the Oldham-Eksborg method-comparison approaches were used and compared. Special emphasis was given to the relation of difference and mean in the Bland-Altman approach. Currently available guidelines for method validation were also considered. Acceptance criteria for method agreement were proposed, including the slope and correlation coefficient in linear regression, and the coefficient of variation for the percentage difference in the Bland-Altman and Oldham-Eksborg approaches.
摘要：
内源性低分子和高分子物质的生物系统中的可靠定量，药物和它们的代谢物，在诊断和治疗中特别重要，以及基础和临床研究。分析方法的分析特征有很多不同，包括精度等核心功能，精度,特异性，以及检测限(LOD)和定量(LOQ)。开发了几种不同的数学方法，并将其用于比较应用于同一生物样品中同一化合物的两种分析方法。一般来说,比较两种分析方法获得的结果会产生不同的定量结果。然而，哪种数学方法给出了最可靠的结果？哪种数学方法最适合证明方法之间的一致性，或分析方法A优于分析方法B？最简单和最常用的比较方法是对方法A（y）观察到的数据和方法B（x）观察到的数据进行线性回归分析：y=αβx。1986年，布兰德和奥特曼指出，线性回归分析，特别是相关系数的使用，不适合方法比较。相反，布兰德和奥特曼提出了一种替代方法，这通常被称为Bland-Altman方法。最初,这种比较方法在医学上得到了应用，例如,用两台设备测量血压.Bland-Altman方法在分析化学和临床化学中迅速适应。迄今为止,Bland-Altman方法提出的方法是方法比较中使用最广泛的数学方法之一。有大约37,000次引用，1986年发表在《柳叶刀》杂志上的原始论文是迄今为止该领域最常被引用的科学论文之一。然而，Bland-Altman方法并没有真正建立在定量的基础上。到目前为止，还没有提出任何标准，其中Bland-Altman方法可以构成可以证明分析协议或更好的分析方法的基础。在这篇文章中,从定量生物分析的角度重新评估了Bland-Altman方法，并尝试提出验收标准。为此,将不同的分析方法与基于质谱(MS)和串联质谱(MS/MS)的金标准分析方法进行了比较，即，GC-MS,GC-MS/MS,LC-MS和LC-MS/MS还考虑了其他色谱和非色谱方法。结果对于几种不同的内源性物质，包括硝酸盐,anandamide,高精氨酸，人血浆中的肌酐和丙二醛，讨论了血清和尿液。除了Bland-Altman的方法,使用线性回归分析和Oldham-Eksborg方法比较方法并进行比较。在Bland-Altman方法中，特别强调了差异与均值的关系。还考虑了目前可用的方法验证指南。提出了方法协议的接受标准，包括线性回归中的斜率和相关系数，以及Bland-Altman和Oldham-Eksborg方法中百分比差异的变异系数。
