PharmacyBiostatisticsExperimental PerformanceGood Laboratory PracticeStandardized TestingAssay ValidationBioanalytical Method ValidationInterindividual VariabilityAnalysis Of Biological VariabilityAnalytical Assay VariabilityAnalytical ValidityBioanalytical VariabilityBiological GoalsBiological VariationProficiency Testing
Proficiency testing schemes must define acceptable performance standards, and current practice generally uses either parametric statistical approaches or empirical fixed limits of acceptability, with many data on biological variation now available to facilitate goal‑setting. The study aims to employ biological variation‑based goals for total laboratory error so that results remain unbiased. The authors compare parametric statistical methods with empirical fixed limits of acceptability for analyzing proficiency testing data. Using empirical fixed limits of acceptability yields advantages when acceptability criteria are set to objective biological variation‑based goals.
Proficiency testing schemes must define acceptable standards of performance. A number of strategies have been used to define acceptable standards, or analytical goals, for imprecision, but it does appear that the current widely held view is that imprecision (as SD or coefficient of variation) should be equal to or less than one half of the average intraindividual biological variation. Since the goal for inaccuracy is that results should be unbiased, the biological variation-based goals should be used for total laboratory error. Many data on the biological variation of a wide range of analytes now exist, which facilitates goal-setting. Current proficiency testing schemes generally analyze laboratory data using either a parametric statistical approach or empirical fixed limits of acceptability. The latter strategy appears to have advantages provided that the criteria of acceptability are the objective biological variation-based goals.