Abstract
Objectives
It is important to select proper quality specifications for laboratories and external quality assessment (EQA) providers for their quality control and assessment. The aim of this study is to produce new total error (TE) specifications for lymphocyte subset enumeration by analyzing the allowable TE using EQAS data and comparing them with that based on reliable biological variation (BV).
Methods
A total of 54,400 results from 1,716 laboratories were collected from China National EQAS for lymphocyte subset enumeration during the period 2017–2019. The EQA data were grouped according to lower limits of reference intervals for establishing concentration-dependent specifications. The TE value that 80% of laboratories can achieve were considered as TE specifications based on state of the art. The BV studies compliant with Biological Variation Data Critical Appraisal Checklist (BIVAC) were used to calculate the three levels of TE specifications. Then these TE specifications were compared for determining the recommended TE specifications.
Results
Four parameters whose quality specifications could achieve the optimum criteria were as follows: the percentages of CD3+, CD3+CD4+ (high concentration) and CD3–CD16/56+ cells, and the absolute count of CD3–CD16/56+ cells. Only the TE specifications of CD3–CD19+ cells could achieve the minimum criteria. The TE specifications of remaining parameters should reach the desirable criteria.
Conclusions
New TE specifications were established by combining the EQA data and reliable BV data, which could help laboratories to apply proper criteria for continuous improvement of quality control, and EQA providers to use robust acceptance limits for better evaluation of EQAS results.
Funding source: Ministry of Science and Technology of China
Award Identifier / Grant number: 2013FY113800
Funding source: National key research and development program
Award Identifier / Grant number: 2017YFC0910003
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: 81772254
Research funding: The work was supported by the research fund of National Special Project of Science and Technology Basic Work of Ministry of Science and Technology of China (Grant No. 2013FY113800), National key research and development program (Grant No. 2017YFC0910003) and National Natural Science Foundation of China (Grant No. 81772254).
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2020-0741).
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