Clinical Chemistry and Laboratory Medicine. 56(9):1447–1457, SEP 2018

DOI: 10.1515/cclm-2017-1199

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PMID: 29683797

Issn Print: 1434-6621

Publication Date: 2018/09/01


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Uncertainty evaluation in clinical chemistry, immunoassay, hematology and coagulation analytes using only external quality assessment data

Yanyan Qin;Rui Zhou;Wei Wang;Hongyi Yin;Yanmin Yang;Yuhong Yue;Qing Tong;Lu Liu;Yali Jin;Yankun Shi;Shunli Zhang;Jianping Zhang;Rui Zhang;Chang Zuo;Tingting Jia;Ning Wang;Qingtao Wang;

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Abstract

Background:Measurement uncertainty (MU) is a parameter associated with the result of a measurement that characterizes its dispersion. We report results for estimating MU following the application of a top-down procedure using only proficiency test data to establish uncertainty levels for various analytes.Methods:Data were obtained from 142 laboratories participating in the Beijing Center for Clinical Laboratory (BCCL) proficiency testing/external quality assessment (PT/EQA) schemes. The 24-month study included six selected PT shipments to obtain estimates for 50th percentile (median) and 90th percentile MUs and to compare those estimates to usual analytic goals. The number of laboratory participants varied for each trial. The expanded uncertainty (U) was calculated using a cover factor of k=2 for a confidence interval of 95%. All reproducibility, method and laboratory biases came from the PT/EQA data.Results:The median U (k=2) ranged from 3.2% (plasma sodium, indirect ion selective electrode) to 32.8% (triglycerides, free glycerol blanking) for clinical chemistry analyte means from participants in the same method group. Immunoassay analyte median U results ranged from 11.3% (CA125 tumor marker, Roche) to 33.8% (prostate-specific antigen [PSA], Abbott). The range for median U was 3.5% (red blood cell [RBC], Abx) to 30.3% (fibrinogen [FBG], other) for hematology and coagulation analytes. The MUs for most analytes satisfied quality requirements.Conclusions:The use of PT/EQA data, when available, provides an effective means for estimating uncertainties associated with quantitative measurements. Thus, medical laboratories can calculate their own MUs. Proficiency testing organizers can provide participants with an additional MU estimate using only EQA data, which may be updated at the end of each survey.

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