Cesana Bruno Mario, Antonelli Paolo, Ferraro Simona
Laboratory of Medical Statistics, Biometry and Epidemiology "G.A. Maccacaro", University of Milan, Milan, Italy.
State Industrial Technical Institute (ITIS) Benedetto Castelli, Brescia, Italy.
Clin Chem Lab Med. 2024 Aug 19;63(3):507-514. doi: 10.1515/cclm-2024-0595. Print 2025 Feb 25.
In laboratory setting evaluating the agreement between two measurement methods is a very frequent practice. Unfortunately, the guidelines to refer to are not free from criticisms from a statistical methodological point of view. We reviewed the Clinical and Laboratory Standards Institute guideline EP09c, 3rd ed. pointing out some drawbacks and some aspects that have not been well defined, leaving situations of uncertainty and/or of excessive subjectivity in the judgement.
We have stressed the need of having replicates to estimate the systematic and the proportional biases of the measurement methods to be compared. Indeed, unequal variance of the two measurement methods gives a slope and intercept of the regression between the difference and the mean of the two values of the measurement methods to be compared that can be absolutely calculated from their means, their variances and their correlation coefficient. So, it is not possible to disentangle true from spurious biases. For laboratory professionals we have developed a worked exemplification of an agreement assessment.
We have stressed the need of other approaches than the classic Bland and Altman method to calculate the systematic and proportional biases of two measurement methods compared for their agreement in a study with replicates.
在实验室环境中，评估两种测量方法之间的一致性是一种非常常见的做法。不幸的是，从统计方法学的角度来看，可供参考的指南并非没有受到批评。我们回顾了临床和实验室标准协会的指南EP09c第3版，指出了一些缺点以及一些尚未明确界定的方面，这在判断中留下了不确定性和/或过度主观性的情况。
我们强调了进行重复测量以估计待比较测量方法的系统偏差和比例偏差的必要性。实际上，两种测量方法的方差不相等会导致待比较测量方法的两个值的差值与均值之间回归的斜率和截距，而这可以完全根据它们的均值、方差和相关系数来计算。因此，无法区分真实偏差和虚假偏差。对于实验室专业人员，我们开发了一个一致性评估的实际示例。
我们强调，在有重复测量的研究中，除了经典的布兰德和奥特曼方法外，还需要其他方法来计算两种测量方法的系统偏差和比例偏差，以评估它们的一致性。
