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

Abstract

Background: The top-down (TD) approach using internal quality control (IQC) data is regarded a practical method for estimating measurement uncertainty (MU) in clinical laboratories. We estimated the MU of 14 clinical chemistry analytes using the TD approach and evaluated the effect of lot changes on the MU.

Methods: MU values were estimated using subgrouping by reagent lot changes or using the data as a whole, and both methods were compared. Reagent lot change was simulated using randomly generated data, and the mean values and MU for two IQC datasets (different QC material lots) were compared using statistical methods.

Results: All MU values calculated using subgrouping were lower than the total values; however, the average differences were minimal. The simulation showed that the greater the increase in the extent of the average shift, the larger the difference in MU. In IQC data comparison, the mean values and MU exhibited statistically significant differences for most analytes. The MU calculation methods gave rise to minimal differences, suggesting that IQC data in clinical laboratories show no significant shift. However, the simulation results demonstrated that notable differences in the MU can arise from significant variations in IQC results before and after a reagent lot change. Additionally, IQC material lots should be treated separately when IQC data are collected for MU estimation.

Conclusions: Lot changes in IQC data are a key factor affecting MU estimation and should not be overlooked during MU estimation.