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Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach
INTRODUCTION: Two methods were compared for evaluating the sigma metrics of clinical biochemistry tests using two different allowable total error (TEa) specifications. MATERIALS AND METHODS: The imprecision (CV%) and bias (bias%) of 19 clinical biochemistry analytes were calculated using a trueness...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868403/ https://www.ncbi.nlm.nih.gov/pubmed/31386228 http://dx.doi.org/10.1002/jcla.22989 |
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author | Li, Runqing Wang, Tengjiao Gong, Lijun Peng, Peng Yang, Song Zhao, Haibin Xiong, Pan |
author_facet | Li, Runqing Wang, Tengjiao Gong, Lijun Peng, Peng Yang, Song Zhao, Haibin Xiong, Pan |
author_sort | Li, Runqing |
collection | PubMed |
description | INTRODUCTION: Two methods were compared for evaluating the sigma metrics of clinical biochemistry tests using two different allowable total error (TEa) specifications. MATERIALS AND METHODS: The imprecision (CV%) and bias (bias%) of 19 clinical biochemistry analytes were calculated using a trueness verification proficiency testing (TPT)‐based approach and an internal quality control data inter‐laboratory comparison (IQC)‐based approach, respectively. Two sources of total allowable error (TEa), the Clinical Laboratory Improvement Amendments of 1988 (CLIA '88) and the People's Republic of China Health Industry Standard (WS/T 403‐2012), were used to calculate the sigma metrics (σ(CLIA,) σ(WS/T)). Sigma metrics were calculated to provide a single value for assessing the quality of each test based on a single concentration level. RESULTS: For both approaches, σ(CLIA) > σ(WS/T) in 18 out of 19 assays. For the TPT‐based approach, 16 assays showed σ(CLIA) > 3, and 12 assays showed σ(WS/T) > 3. For the IQC‐based approach, 19 and 16 assays showed σ(CLIA) > 3 and σ(WS/T) > 3, respectively. CONCLUSIONS: Both methods can be used as references for calculating sigma metrics and designing QC schedules in clinical laboratories. Sigma metrics should be evaluated comprehensively by different approaches. |
format | Online Article Text |
id | pubmed-6868403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68684032019-11-25 Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach Li, Runqing Wang, Tengjiao Gong, Lijun Peng, Peng Yang, Song Zhao, Haibin Xiong, Pan J Clin Lab Anal Research Articles INTRODUCTION: Two methods were compared for evaluating the sigma metrics of clinical biochemistry tests using two different allowable total error (TEa) specifications. MATERIALS AND METHODS: The imprecision (CV%) and bias (bias%) of 19 clinical biochemistry analytes were calculated using a trueness verification proficiency testing (TPT)‐based approach and an internal quality control data inter‐laboratory comparison (IQC)‐based approach, respectively. Two sources of total allowable error (TEa), the Clinical Laboratory Improvement Amendments of 1988 (CLIA '88) and the People's Republic of China Health Industry Standard (WS/T 403‐2012), were used to calculate the sigma metrics (σ(CLIA,) σ(WS/T)). Sigma metrics were calculated to provide a single value for assessing the quality of each test based on a single concentration level. RESULTS: For both approaches, σ(CLIA) > σ(WS/T) in 18 out of 19 assays. For the TPT‐based approach, 16 assays showed σ(CLIA) > 3, and 12 assays showed σ(WS/T) > 3. For the IQC‐based approach, 19 and 16 assays showed σ(CLIA) > 3 and σ(WS/T) > 3, respectively. CONCLUSIONS: Both methods can be used as references for calculating sigma metrics and designing QC schedules in clinical laboratories. Sigma metrics should be evaluated comprehensively by different approaches. John Wiley and Sons Inc. 2019-08-06 /pmc/articles/PMC6868403/ /pubmed/31386228 http://dx.doi.org/10.1002/jcla.22989 Text en © 2019 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Li, Runqing Wang, Tengjiao Gong, Lijun Peng, Peng Yang, Song Zhao, Haibin Xiong, Pan Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title | Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title_full | Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title_fullStr | Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title_full_unstemmed | Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title_short | Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
title_sort | comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868403/ https://www.ncbi.nlm.nih.gov/pubmed/31386228 http://dx.doi.org/10.1002/jcla.22989 |
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