Application of biological variation and sigma metrics to evaluate the performance of HbA_1c in external quality...

It is crucial to improve the accuracy of HbA_1c measurement as its essential role in diabetes diagnosis and treatment. We aimed to establish the biological variation (BV) and sigma metrics (SM) models and apply the models to evaluate the analytical performance of HbA_1c in external quality assessment (EQA) program.

Data of HbA_1c EQA (2021) and internal quality control (IQC) (March-August 2021) were collected. The group-specific bias and coefficient of variance (CV) were computed for measuring systems with laboratory number >9 in EQA program. The analytical bias and CV for individual laboratory were estimated from EQA and IQC data. The CV% and bias% were plotted in the BV-SM models for performance evaluation of measuring system and individual laboratory.

Totally, 380 laboratories participated in EQA program. The overall inter-laboratory CV of five EQA samples ranged from 3.02% to 3.63%. There were five measuring systems that met the minimum performance for 5/5 samples: Arkary, Primus, Roche, Mindray and Tosoh, but none of them achieved the optimum performance. Half of the 196 laboratories that reported IQC and EQA results simultaneously achieved 3σ and minimum performance limits. Further analysis indicated that 88.8%, and 31.6% of the laboratories met the minimum performance for bias and CV, respectively.

The biological variation and sigma metrics are appropriate quality management models for evaluating the performance of HbA_1c in EQA program. The intra-laboratory and inter-laboratory imprecision need to be improved in order to achieve the required analytical goals for diabetes diagnosis.