Keller H, Passing H
Institut für Klinische Chemie und Hämatologie des Kantons St. Gallen.
J Clin Chem Clin Biochem. 1989 Sep;27(9):613-29. doi: 10.1515/cclm.1989.27.9.613.
It is current practice to record the performance of immunoassays by means of precision profiles (according to Ekins), in which the variation coefficient (relative standard deviation) is plotted against the analyte concentration. On the other hand, precision profiles are only occasionally used for evaluating the performance of conventional clinical-chemical methods. It is relatively uncommon to find bias plotted against analyte concentration, presumably because this type of analysis requires reference specimens, whose true analyte concentrations are known or guaranteed by reference methods. If the relative systematic variations are plotted against the true analyte concentrations, and a confidence interval is added to the resulting regression curve, the result is a "bias profile"; if tolerance limits are added, the result is a "deviation profile". The present work describes the preparation of specimens, which can be used to provide experimental data for the three performance profiles. A computer program is used to construct the precision profile, bias profile and/or deviation profile. The mathematical-statistical basis of the program is described in detail. For evaluation of the statistical procedure, three analytes and six methods were used: determination of sodium activity/concentration with an ion sensitive electrode and by flame photometry; determination of creatinine by a manual enzymic and a mechanized Jaffé method; determination of thyrotropin by radioimmunoassay and by luminescence immunoassay. Different purposes are served by bias and deviation profiles. Thus, bias profiles can be used to compare the bias of two methods, whereas a deviation profile can be used to define the analytical range of a method. If the acceptable limits of deviation are added to the deviation profile, then the useful analytical range of the method is immediately apparent.
目前的做法是通过精密度曲线（根据埃金斯方法）来记录免疫分析的性能，其中变异系数（相对标准偏差）与分析物浓度作图。另一方面，精密度曲线仅偶尔用于评估传统临床化学方法的性能。绘制偏差与分析物浓度的关系图相对少见，大概是因为这种类型的分析需要参考标本，其真实分析物浓度是已知的或由参考方法保证的。如果将相对系统变异与真实分析物浓度作图，并在所得回归曲线上添加置信区间，结果就是一个“偏差曲线”；如果添加公差限，结果就是一个“偏差范围曲线”。本工作描述了标本的制备，可用于为这三种性能曲线提供实验数据。使用计算机程序构建精密度曲线、偏差曲线和/或偏差范围曲线。详细描述了该程序的数学统计基础。为了评估统计程序，使用了三种分析物和六种方法：用离子敏感电极和火焰光度法测定钠活性/浓度；用手工酶法和机械化杰氏法测定肌酐；用放射免疫分析法和发光免疫分析法测定促甲状腺激素。偏差曲线和偏差范围曲线有不同的用途。因此，偏差曲线可用于比较两种方法的偏差，而偏差范围曲线可用于定义一种方法的分析范围。如果将可接受的偏差限添加到偏差范围曲线上，那么该方法的有效分析范围就会立即显现出来。
