Application of Sigma metrics in the quality control strategies of immunology and protein analytes

作者：Yanfen Luo, Xingxing Yan, Qian Xiao, Yifei Long, Jieying Pu, Qiwei Li, Yimei Cai, Yushun Chen, Hongyuan Zhang, Chen Cha, Songbang Ou · 发表于：Journal of Clinical Laboratory Analysis · 年份：2021 · DOI：10.1002/jcla.24041 · 被引用次数：11 · 研究领域：Clinical Laboratory Practices and Quality Control、Pesticide Residue Analysis and Safety、Biosimilars and Bioanalytical Methods

Abstract Background Six Sigma (6σ) is an efficient laboratory management method. We aimed to analyze the performance of immunology and protein analytes in terms of Six Sigma. Methods Assays were evaluated for these 10 immunology and protein analytes: Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin M (IgM), Complement 3 (C3), Complement 4 (C4), Prealbumin (PA), Rheumatoid factor (RF), Anti streptolysin O (ASO), C‐reactive protein (CRP), and Cystatin C (Cys C). The Sigma values were evaluated based on bias, four different allowable total error (TEa) and coefficient of variation (CV) at QC materials levels 1 and 2 in 2020. Sigma Method Decision Charts were established. Improvement measures of analytes with poor performance were recommended according to the quality goal index (QGI), and appropriate quality control rules were given according to the Sigma values. Results While using the TEa NCCL , 90% analytes had a world‐class performance with σ>6, Cys C showed marginal performance with σ<4. While using minimum, desirable, and optimal biological variation of TEa, only three (IgG, IgM, and CRP), one (CRP), and one (CRP) analytes reached 6σ level, respectively. Based on σ NCCL that is calculated from TEa NCCL , Sigma Method Decision Charts were constructed. For Cys C, five multi‐rules (1 3s /2 2s /R 4s /4 1s /6 X , N = 6, R = 1, Batch length: 45) were adopted for QC management. The remaining analytes required only one QC rule (1 3s , N = 2, R = 1, Batch length: ...