Influence of reagent lots and multiple measuring systems on estimating the coefficient of variation from quality control data; implications for uncertainty estimation and interpretation of QC results

Abstract

BackgroundClinical laboratories use internal quality control (QC) data to calculate standard deviation (SD) and coefficient of variation (CV) to estimate uncertainty of results and to interpret QC results. We examined the influence of different instruments, and QC and reagent lots on the CV calculated from QC data.MethodsResults for BioRad Multiqual frozen liquid QC samples over a 2-year interval were partitioned by QC and reagent lots. The mean and CV were calculated for each partition for each of three Abbott Architect c8000 instruments for measuring serum alanine amino transferase (ALT), creatinine (enzymatic), glucose and sodium.ResultsCVs differed among partitions and instruments for two QC levels by 5.8- and 3.3-fold for ALT, by 4.7- and 2.1-fold for creatinine, by 2.0- and 2.6-fold for glucose, and by 2.1- and 2.0-fold for sodium. Pooled CVs for two QC levels varied among instruments by 1.78- and 1.11-fold for ALT, by 1.63- and 1.11-fold for creatinine, by 1.08- and 1.06-fold for glucose, and by 1.24- and 1.31-fold for sodium.ConclusionsThe CVs from QC data varied substantially among QC and reagent lots and for different identical specification instruments. The CV used to estimate uncertainty for a measurement result or as the basis for interpreting individual QC results must be derived over a sufficient time interval to obtain a pooled CV that represents “typical” performance of a measuring system. An estimate of uncertainty provided to users of laboratory results will itself have uncertainty that can influence medical decisions.

Practical Considerations for Clinical Laboratories in Top-down Approach for Assessing the Measurement Uncertainty of Clinical Chemistry Analytes

“…The calculated uRw values were combined with the uncertainty of end-user calibrator values to obtain expanded uncertainty [6,7]: (5) All combined uncertainty (uc) values were multiplied by 2 (coverage factor, k = 2) (equation 5). The expanded uncertainty values were expressed as the standard expanded uncertainty (U) with their units and relative expanded uncertainty (%Urel) [6,7,10].…”

“…2) IQC values before and after a reagent lot change were collected separately according to lot number, and u Rw values calculated for each data subgroup were combined to obtain the overall uncertainty (subgrouping uncertainty, u sub ) according to equation (2) [ 6 , 7 , 10 ].…”

“…Various measurement factors, such as sample inhomogeneity, reconstitution procedures for lyophilized materials, reagent and calibrator instability, fluctuations in the laboratory environment, operator bias, routine instrument maintenance, lot changes for calibrators and reagents, and different operators, are common sources of MU [ 5 - 9 ]. It is presumed that IQC data cover all anticipated routine changes in the measuring system for an appropriate period [ 6 , 7 , 10 ]. When repeatability or long-term imprecision data for a well-controlled measurement procedure are plotted as a Gaussian distribution, the magnitude of the dispersion of values around the mean value can be quantified by calculating the standard deviation (SD) [ 6 , 7 , 10 ].…”

“…It is presumed that IQC data cover all anticipated routine changes in the measuring system for an appropriate period [ 6 , 7 , 10 ]. When repeatability or long-term imprecision data for a well-controlled measurement procedure are plotted as a Gaussian distribution, the magnitude of the dispersion of values around the mean value can be quantified by calculating the standard deviation (SD) [ 6 , 7 , 10 ]. Standard uncertainty can be expressed as SD.…”

“…Standard uncertainty can be expressed as SD. Because SD or u values cannot be added or subtracted, relative standard uncertainties ( u rel ) first have to be converted to their respective variances (SD 2 and CV 2 ) in calculations [ 6 , 7 , 10 ].…”