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AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun

BACKGROUND: The anti-Müllerian hormone (AMH) is gaining attention as a key factor in determining ovarian reserve and polycystic ovarian syndrome, and its clinical applications are becoming more widespread worldwide. OBJECTIVE: To identify the most accurate formula for converting AMH assay results be...

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Autores principales: Xu, Huiyu, Feng, Guoshuang, Ma, Congcong, Han, Yong, Zhou, Jiansuo, Song, Jiatian, Su, Yuan, Zhong, Qun, Chen, Fenghua, Cui, Liyan, Li, Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249628/
https://www.ncbi.nlm.nih.gov/pubmed/37304879
http://dx.doi.org/10.7717/peerj.15301
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author Xu, Huiyu
Feng, Guoshuang
Ma, Congcong
Han, Yong
Zhou, Jiansuo
Song, Jiatian
Su, Yuan
Zhong, Qun
Chen, Fenghua
Cui, Liyan
Li, Rong
author_facet Xu, Huiyu
Feng, Guoshuang
Ma, Congcong
Han, Yong
Zhou, Jiansuo
Song, Jiatian
Su, Yuan
Zhong, Qun
Chen, Fenghua
Cui, Liyan
Li, Rong
author_sort Xu, Huiyu
collection PubMed
description BACKGROUND: The anti-Müllerian hormone (AMH) is gaining attention as a key factor in determining ovarian reserve and polycystic ovarian syndrome, and its clinical applications are becoming more widespread worldwide. OBJECTIVE: To identify the most accurate formula for converting AMH assay results between different platforms, so that the developed AMH converter can be used to reduce the need for multiple AMH tests at different hospitals. METHODS: Assuming that the Beckman Access, Kangrun, and Roche Elecsys(®) AMH assays fit a linear relationship from the lowest to the highest concentration (a global relationship), we used Passing–Bablok regression to determine the conversion equation between each two assays. When the relationship between two AMH assays was a local one, spline regression was used. Bland–Altman plots were drawn to check systemic bias and heterogeneity of variance across different ranges of values. The fitting effects of the models were evaluated using the squared coefficient of determination (r(2)), adjusted r(2), root mean square error (RMSE), Akaike information criterion (AIC), and corrected AIC. RESULTS: The coefficient of variance for multiple controls in the Kangrun, Roche, and Beckman assays was lower than 5%, and the bias of multiple controls was lower than 7%. A global linear relationship was observed between the Kangrun and Roche assays, with the intercept being zero, for which Passing-Bablok regression was employed for data conversion between the two platforms. For the other two pairs of platforms, i.e., Roche and Kangrun or Beckman and Kangrun, spline regression was applied, with the intercepts not including zero. The six corresponding formulas were developed into an online AMH converter (http://121.43.113.123:8006/). CONCLUSION: This is the first time Passing–Bablok plus spline regression has been used to convert AMH concentrations from one assay to another. The formulas have been developed into an online tool, which makes them convenient to use in practical applications.
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spelling pubmed-102496282023-06-09 AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun Xu, Huiyu Feng, Guoshuang Ma, Congcong Han, Yong Zhou, Jiansuo Song, Jiatian Su, Yuan Zhong, Qun Chen, Fenghua Cui, Liyan Li, Rong PeerJ Biochemistry BACKGROUND: The anti-Müllerian hormone (AMH) is gaining attention as a key factor in determining ovarian reserve and polycystic ovarian syndrome, and its clinical applications are becoming more widespread worldwide. OBJECTIVE: To identify the most accurate formula for converting AMH assay results between different platforms, so that the developed AMH converter can be used to reduce the need for multiple AMH tests at different hospitals. METHODS: Assuming that the Beckman Access, Kangrun, and Roche Elecsys(®) AMH assays fit a linear relationship from the lowest to the highest concentration (a global relationship), we used Passing–Bablok regression to determine the conversion equation between each two assays. When the relationship between two AMH assays was a local one, spline regression was used. Bland–Altman plots were drawn to check systemic bias and heterogeneity of variance across different ranges of values. The fitting effects of the models were evaluated using the squared coefficient of determination (r(2)), adjusted r(2), root mean square error (RMSE), Akaike information criterion (AIC), and corrected AIC. RESULTS: The coefficient of variance for multiple controls in the Kangrun, Roche, and Beckman assays was lower than 5%, and the bias of multiple controls was lower than 7%. A global linear relationship was observed between the Kangrun and Roche assays, with the intercept being zero, for which Passing-Bablok regression was employed for data conversion between the two platforms. For the other two pairs of platforms, i.e., Roche and Kangrun or Beckman and Kangrun, spline regression was applied, with the intercepts not including zero. The six corresponding formulas were developed into an online AMH converter (http://121.43.113.123:8006/). CONCLUSION: This is the first time Passing–Bablok plus spline regression has been used to convert AMH concentrations from one assay to another. The formulas have been developed into an online tool, which makes them convenient to use in practical applications. PeerJ Inc. 2023-06-05 /pmc/articles/PMC10249628/ /pubmed/37304879 http://dx.doi.org/10.7717/peerj.15301 Text en ©2023 Xu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biochemistry
Xu, Huiyu
Feng, Guoshuang
Ma, Congcong
Han, Yong
Zhou, Jiansuo
Song, Jiatian
Su, Yuan
Zhong, Qun
Chen, Fenghua
Cui, Liyan
Li, Rong
AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title_full AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title_fullStr AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title_full_unstemmed AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title_short AMHconverter: an online tool for converting results between the different anti-Müllerian hormone assays of Roche Elecsys(®), Beckman Access, and Kangrun
title_sort amhconverter: an online tool for converting results between the different anti-müllerian hormone assays of roche elecsys(®), beckman access, and kangrun
topic Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249628/
https://www.ncbi.nlm.nih.gov/pubmed/37304879
http://dx.doi.org/10.7717/peerj.15301
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