title: A new concept to derive permissible limits for analytical imprecision and bias considering diagnostic requirements and technical state-of-the-art.
abstract: BACKGROUND
  Permissible limits of analytical imprecision and bias are usually derived either from biological variability or from the state of the art. Both concepts require information from external sources which often lack transparency and are difficult to integrate in medical decision-making. Additionally, physicians may be interested in knowing the probability of decision errors due to analytical uncertainty. Therefore, an approach was developed which combines all three concepts.
  
  
  METHODS
  The empirical (observed) biological variation was derived from reference ranges used by the laboratory (CV(E)). CV(E) was corrected to get the biological variation in the theoretical absence of analytical imprecision (CV(C)). Relatively simple equations were derived from the relationship between biological variation and the analytical imprecision (CV(A)) to calculate permissible imprecision and bias. Five quality classes are proposed for the various analytes reflecting the false-positive error rates (FPR). These classes characterize analytical procedures according to their theoretical specificity (FPR). Thus, the new approach combines the theoretical base of biological variation with the technical state-of-the-art.
  
  
  CONCLUSIONS
  As practical examples, the permissible imprecision and bias limits were estimated for a selection of quantities. The limits found were more realistic than present proposals based on Cotlove's rule (fixed fraction of biological variation), but slightly more stringent than national consensus values based on the state-of-the-art. Imprecision and bias do not affect FPR equally, and, therefore, should be assessed separately. It is proposed to insert monthly imprecision and bias results calculated after each control cycle in a table with five quality classes. This table provides a simple overview of the analytical quality performance of the entire laboratory with one glance and can be handled on the Excel platform.
authors.affiliation: Zentrum für Laboratoriumsdiagnostik am Klinikum Bremen Mitte, Bremen, Germany. rainer.haeckel@t-online.de
authors.forename: Rainer
authors.initials: R
authors.lastname: Haeckel
authors.forename: Werner
authors.initials: W
authors.lastname: Wosniok
mesh_terms: D015982:Bias; D019411:Clinical Laboratory Techniques / Q000592:standards*; D003951:Diagnostic Errors; D005189:False Positive Reactions; D005240:Feasibility Studies; D006801:Humans; D011786:Quality Control; D012016:Reference Values; D012680:Sensitivity and Specificity