Faculty of Health Sciences, Department of Clinical Laboratory Sciences, Graduate School of Medicine, Yamaguchi University, Minami-Kogushi 1-1-1, Ube 755-8505, Japan.
Clin Chem Lab Med. 2013 May;51(5):1007-25. doi: 10.1515/cclm-2013-0248.
In a planned International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) worldwide study on reference intervals (RIs), a common panel of serum samples is to be measured by laboratories from different countries, and test results are to be compared through conversion using linear regression analysis. This report presents a validation study that was conducted in collaboration with four laboratories.
A panel composed of 80 sera was prepared from healthy individuals, and 45 commonly tested analytes (general chemistry, tumor markers, and hormones) were measured on two occasions 1 week apart in each laboratory. Reduced major-axis linear regression was used to convert reference limits (LL and UL). Precision was expressed as a ratio of the standard error of converted LL or UL to the standard deviation (SD) comprising RI (approx. 1/4 of the RI width corresponding to between-individual SD). The allowable and optimal levels of error for the SD ratio (SDR) were set as ≤0.250 and ≤0.125, respectively, in analogy to the common method of setting limits for analytical bias based on between-individual SD.
The values for the calculated SDRs depended upon the distribution patterns of test results: skewness toward higher values makes SDRLL lower and SDRUL higher. However, the CV of the regression line slope, CV(b), is less affected by skewness. The average of SDRLL and SDRUL (aveSDR) correlates closely with CV(b) (r=0.995). The aveSDRs of ≤0.25 and ≤0.125 corresponds approximately to CV(b) values of ≤11% and ≤5.5%, respectively. For all results (i.e., n=80), conversion was allowable (optimal) in 98% (89%) of the analytes, as judged by CV(b). Resampling studies using random subsets of data with a data size (n) of 70 to 20 revealed that SDRs and CV(b) gradually increase with reduction of n, especially with n ≤30.
CV(b) is a robust estimator for judging the convertibility of reference values among laboratories, even with a skewed distribution. Assuming 40 sera to be a practical size for the panel, reference values of 89% (80%) of analytes examined were made comparable by regression analysis with the allowable (optimal) level of precision.
在国际临床化学和实验室医学联合会（IFCC）计划进行的一项全球参考区间（RI）研究中，将由来自不同国家的实验室共同测量一组血清样本，并通过使用线性回归分析进行转换来比较测试结果。本报告介绍了一项与四个实验室合作进行的验证研究。
由健康个体制备的 80 份血清组成的面板，每个实验室在两次测量之间相隔 1 周，共测量了 45 个常用测试分析物（常规化学、肿瘤标志物和激素）。使用降半轴线性回归来转换参考限值（LL 和 UL）。精密度表示为转换后的 LL 或 UL 的标准误差与 RI 标准差（SD）的比值（约为个体 SD 对应的 RI 宽度的 1/4）。根据基于个体 SD 的分析偏差限设定方法，将 SD 比值（SDR）的允许和最佳误差水平分别设定为≤0.250 和≤0.125。
计算出的 SDR 值取决于测试结果的分布模式：向较高值的偏度使 SDRLL 降低而 SDRUL 升高。然而，回归线斜率的 CV（CV(b)）受偏度的影响较小。SDRLL 和 SDRUL 的平均值（aveSDR）与 CV(b)密切相关（r=0.995）。aveSDR 值分别约为≤0.25 和≤0.125，对应于 CV(b)值分别约为≤11%和≤5.5%。对于所有结果（即 n=80），根据 CV(b)判断，转换在 98%（89%）的分析物中是允许的（最佳的）。使用数据大小（n）为 70 到 20 的随机数据子集进行的重采样研究表明，随着 n 的减少，SDR 和 CV(b)逐渐增加，尤其是在 n≤30 时。
即使分布存在偏度，CV(b)也是判断实验室间参考值可转换性的稳健估计值。假设 40 份血清是面板的实际大小，则通过回归分析将 89%（80%）的检查分析物的参考值达到允许（最佳）精度水平，从而具有可比性。
