Kristiansen Jesper
The National Institute of Occupational Health, Lersø Parkallé 105, DK-2100 Copenhagen, Denmark.
Clin Chem. 2003 Nov;49(11):1822-9. doi: 10.1373/clinchem.2003.021469.
The aim of the Guide to Expression of Uncertainty in Measurement (GUM) is to harmonize the different practices for estimating and reporting uncertainty of measurement. Although there are clear advantages in having a common approach for evaluating uncertainty, application of the GUM approach to chemistry measurements is not straightforward. In the above commentary, Krouwer suggests that the GUM approach should not be applied to diagnostic assays, because (a) the quality of diagnostic assays is to low, and (b) the GUM uncertainty intervals are too narrow to predict the outliers that occasionally trouble these methods.
Some of the examples presented by Krouwer are reviewed. Sodium measurements are modeled mathematically to illustrate the GUM approach to uncertainty. A standardized uncertainty evaluation process is presented.
Modeling of sodium measurements demonstrates how the GUM uncertainty interval reflects the treatment of a bias: The width of the uncertainty interval varied depending on whether a correction for a calibrator lot bias was applied, but in both cases it was consistent with the distribution of measurement results. Expanding the uncertainty interval to include outliers runs counter to the definition of uncertainty. Used appropriately, the GUM uncertainty can be helpful in detecting outliers. In standardizing the uncertainty evaluation, the importance of the analytical imprecision and traceability was emphasized. It is problematic that manufacturers of commercial assays rarely inform about the uncertainty of the values assigned to the calibrators. As demonstrated by an example, external quality-assurance data may be used to estimate this uncertainty.
The GUM uncertainty should be applied to measurements in laboratory medicine because it may actually support the forces that drive the work on improving the quality of measurement procedures. However, it is important that the GUM approach is made more manageable by standardizing the uncertainty evaluation procedure as much as possible. It is essential to focus on the traceability and uncertainty of calibrators and reagents supplied by manufacturers of assays. Information about uncertainty is necessary in the evaluation of the uncertainty associated with manufacturers' measurement procedures, and in general it may force manufacturers to increase their efforts in improving the metrologic and analytical quality of their products.
《测量不确定度表示指南》(GUM)的目的是协调测量不确定度评估和报告的不同做法。尽管采用通用方法评估不确定度有明显优势,但将GUM方法应用于化学测量并非易事。在上述评论中,克鲁韦尔认为GUM方法不适用于诊断检测,原因如下:(a)诊断检测的质量过低;(b)GUM不确定度区间过窄,无法预测偶尔困扰这些方法的异常值。
对克鲁韦尔给出的一些示例进行了回顾。对钠测量进行数学建模,以说明GUM方法用于不确定度评估的情况。给出了一个标准化的不确定度评估过程。
钠测量的建模展示了GUM不确定度区间如何反映偏差的处理:不确定度区间的宽度因是否对校准品批次偏差进行校正而有所不同,但在两种情况下均与测量结果的分布一致。将不确定度区间扩大以包含异常值与不确定度的定义相悖。如果使用得当,GUM不确定度有助于检测异常值。在使不确定度评估标准化时,强调了分析不精密度和可溯源性的重要性。商业检测制造商很少告知校准品赋值的不确定度,这是个问题。如一个示例所示,外部质量保证数据可用于估计此不确定度。
GUM不确定度应应用于检验医学测量,因为它实际上可能有助于推动提高测量程序质量的工作。然而,通过尽可能使不确定度评估程序标准化,使GUM方法更易于管理很重要。必须关注检测制造商提供的校准品和试剂的可溯源性和不确定度。不确定度信息对于评估与制造商测量程序相关的不确定度是必要的,总体而言,它可能促使制造商加大努力提高其产品的计量和分析质量。