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Zhang J, Chen X, Wu J, Feng P, Wang W, Zhong K, Yuan S, Du Y, Zhang C, He F. An assessment of analytical performance using the six sigma scale in second-trimester maternal prenatal screening practices in China. Pract Lab Med 2024; 41:e00422. [PMID: 39155970 PMCID: PMC11327568 DOI: 10.1016/j.plabm.2024.e00422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/11/2024] [Accepted: 07/21/2024] [Indexed: 08/20/2024] Open
Abstract
Objectives We aimed to evaluate the analytical performance of second-trimester maternal serum screening in China, and to compare if there are differences in sigma levels across different methods and months. Methods A retrospective study was conducted to assess the analytical quality levels of laboratories by calculating the Sigma metrics with prenatal screening biomarkers: AFP, Total β-hCG, free β-hCG, uE3. Data from 591 laboratories were selected. Sigma metrics were computed using the formula: Sigma metrics(σ) = (%TEa - |%Bias|)/%CV. The Friedman test and Mann-Whitney test were used to compare differences across various methods and different months. The Hodges-Lehmann was used for determining 95 % confidence intervals of pseudo-medians. Results Only uE3 showed significant monthly variations in sigma calculations. However, around 8 % of laboratories across all four analytes demonstrated sigma levels both above 6 and below 3 in different months. Laboratories utilizing time-resolved fluorescence methods significantly outperformed those using chemiluminescence in sigma level. For AFP, the pseudo-median difference between these methods lies within a 95 % confidence interval of (-3.22, -1.93), while for uE3, it is at (-2.30, -1.40). Notably, the median sigma levels for all analytes reached the 4-sigma threshold, with free β-hCG even attaining the 6-sigma level. Conclusion With current standards, China's second-trimester maternal serum screening is of relatively high analytical quality, and variations in sigma levels exist across different months and methods.
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Affiliation(s)
- Jinming Zhang
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Xingtong Chen
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Jiaming Wu
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Penghui Feng
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Beijing, PR China
| | - Wei Wang
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
| | - Kun Zhong
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
| | - Shuai Yuan
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
| | - Yuxuan Du
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
| | - Chuanbao Zhang
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Falin He
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/ National Center of Gerontology, Beijing, PR China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
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Ercan Ş. Comparison of Sigma metrics computed by three bias estimation approaches for 33 chemistry and 26 immunoassay analytes. ADVANCES IN LABORATORY MEDICINE 2023; 4:236-245. [PMID: 38162416 PMCID: PMC10756147 DOI: 10.1515/almed-2022-0095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 06/05/2023] [Indexed: 01/03/2024]
Abstract
Objectives Sigma metric can be calculated using a simple equation. However, there are multiple sources for the elements in the equation that may produce different Sigma values. This study aimed to investigate the importance of different bias estimation approaches for Sigma metric calculation. Methods Sigma metrics were computed for 33 chemistry and 26 immunoassay analytes on the Roche Cobas 6000 analyzer. Bias was estimated by three approaches: (1) averaging the monthly bias values obtained from the external quality assurance (EQA) studies; (2) calculating the bias values from the regression equation derived from the EQA data; and (3) averaging the monthly bias values from the internal quality control (IQC) events. Sigma metrics were separately calculated for the two levels of the IQC samples using three bias estimation approaches. The resulting Sigma values were classified into five categories considering Westgard Sigma Rules as ≥6, <6 and ≥5, <5 and ≥4, <4 and ≥3, and <3. Results When classifying Sigma metrics estimated by three bias estimation approaches for each assay, 16 chemistry assays at the IQC level 1 and 2 were observed to fall into different Sigma categories under at least one bias estimation approach. Similarly, for 12 immunoassays at the IQC level 1 and 2, Sigma category was different depending on bias estimation approach. Conclusions Sigma metrics may differ depending on bias estimation approaches. This should be considered when using Six Sigma for assessing analytical performance or scheduling the IQC events.
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Affiliation(s)
- Şerif Ercan
- Department of Medical Biochemistry, Lüleburgaz State Hospital, Lüleburgaz Devlet Hastanesi İstiklal Mah, Kırklareli, Türkiye
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Ercan Ş. Comparación de la métrica Sigma calculada con tres métodos de estimación del sesgo en 33 magnitudes químicas y 26 de inmunoensayo. ADVANCES IN LABORATORY MEDICINE 2023; 4:246-257. [PMID: 38162415 PMCID: PMC10756148 DOI: 10.1515/almed-2023-0095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 06/05/2023] [Indexed: 01/03/2024]
Abstract
Objetivos Aunque la métrica Sigma se puede calcular mediante una sencilla ecuación, la diversidad de fuentes de las que se extraen los elementos de la ecuación pueden arrojar diferentes valores Sigma. El objetivo de este estudio era investigar la importancia de las distintas estrategias de estimación del sesgo para el cálculo de la métrica Sigma. Métodos Se calculó la métrica Sigma de 33 magnitudes químicas y 26 magnitudes de inmunoensayo en un analizador Roche Cobas 6,000. El sesgo se calculó mediante tres métodos: a) calculando la media del sesgo mensual obtenida en los estudios de control de calidad externo (EQA, por sus siglas en inglés); 2) calculando los valores de sesgo mediante una ecuación de regresión a partir de datos obtenidos del EQA; y 3) calculando la media de los valores de sesgo mensual de los eventos de control de calidad internos (IQC, por sus siglas en inglés). Se realizó una métrica Sigma para cada uno de los dos niveles de muestras de IQC empleando tres métodos para calcular el sesgo. Los valores Sigma obtenidos se clasificaron en cinco categorías, en función de las reglas Sigma de Westgard, siendo ≥6, <6 y ≥5, <5 y ≥4, <4 y ≥3, y <3. Resultados Al clasificar la métrica Sigma, calculada aplicando tres métodos de estimación del sesgo para cada magnitud, se observó que 16 magnitudes químicas en los niveles 1 y 2 de IQC fueron clasificadas en categorías Sigma diferentes por al menos uno de los métodos de estimación de la desviación. Del mismo modo, dependiendo del método de estimación del sesgo empleado, se clasificaba en diferentes categorías a 12 magnitudes de inmunoensayo con niveles 1 y 2 de IQC. Conclusiones La métrica Sigma puede variar dependiendo del método empleado para calcular el sesgo, lo cual debe ser tenido en cuenta a la hora de evaluar el rendimiento analítico o programar eventos de IQC aplicando el método Seis Sigma.
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Affiliation(s)
- Şerif Ercan
- Departamento de Bioquímica Médica, Lüleburgaz State Hospital, Kırklareli, Türkiye
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Wauthier L, Di Chiaro L, Favresse J. Sigma Metrics in Laboratory Medicine: A Call for Harmonization. Clin Chim Acta 2022; 532:13-20. [PMID: 35594921 DOI: 10.1016/j.cca.2022.05.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 04/27/2022] [Accepted: 05/13/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND AIM Sigma metrics are applied in clinical laboratories to assess the quality of analytical processes. A parameter associated to a Sigma >6 is considered "world class" whereas a Sigma <3 is "poor" or "unacceptable". The aim of this retrospective study was to quantify the impact of different approaches for Sigma metrics calculation. MATERIAL AND METHODS Two IQC levels of 20 different parameters were evaluated for a 12-month period. Sigma metrics were calculated using the formula: (allowable total error (TEa) (%) - bias (%))/(coefficient of variation (CV) (%)). Method precision was calculated monthly or annually. The bias was obtained from peer comparison program (PCP) or external quality assessment program (EQAP), and 9 different TEa sources were included. RESULTS There was a substantial monthly variation of Sigma metrics for all combinations, with a median variation of 32% (IQR, 25.6-41.3%). Variation across multiple analyzers and IQC levels were also observed. Furthermore, TEa source had the highest impact on Sigma calculation with proportions of Sigma >6 ranging from 17.5% to 84.4%. The nature of bias was less decisive. CONCLUSION In absence of a clear consensus, we recommend that laboratories calculate Sigma metrics on a sufficiently long period of time (>6 months) and carefully evaluate the choice of TEa source.
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Affiliation(s)
- Loris Wauthier
- Department of Laboratory Medicine, Clinique St-Luc Bouge, Namur, Belgium
| | - Laura Di Chiaro
- Department of Laboratory Medicine, Clinique St-Luc Bouge, Namur, Belgium
| | - Julien Favresse
- Department of Laboratory Medicine, Clinique St-Luc Bouge, Namur, Belgium; Department of Pharmacy, Namur Research Institute for LIfe Sciences, University of Namur, Namur, Belgium.
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