Calculating uncertainty of measurement for serology assays by use of precision and bias

Abstract

Background: In many countries, regulatory authorities that use International Organization for Standardization Standards to assess laboratory competence require an estimate of the uncertainty of measurement (MU) of assay test results. This estimate can be determined by identifying all sources of variation, calculating the extent of variation, and using established methods to combine the uncertainty. Alternatively, laboratory staff may use existing data generated from evaluations, proficiency testing, or external run controls to determine MU. Methods: A quality-control (QC) sample with low reactivity was tested by laboratories participating in a national QC program. The results of testing the QC sample were entered into a shared database by use of an Internet-based program, EDCNet. Using a statistical approach that accounts for imprecision and bias of test results, we estimated the MU of the laboratories. Results: A total of 2167 test results of a single QC sample reported by 18 laboratories were analyzed, and the MU of 1 laboratory was estimated by the statistical model described. Conclusion: Using peer-group run control data, MU of serologic testing can be estimated by taking into account both imprecision and bias. © 2006 American Association for Clinical Chemistry.