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

Author:

Xu Huiyu1234,Feng Guoshuang5,Ma Congcong1234,Han Yong6,Zhou Jiansuo7,Song Jiatian1234,Su Yuan1234,Zhong Qun1234,Chen Fenghua1234,Cui Liyan7,Li Rong1234

Affiliation:

1. Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

2. Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Peking University, Beijing, China

3. National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

4. Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing, China

5. Beijing Children’s Hospital, Beijing, China

6. Hangzhou Qingguo Medical Technology Co. Ltd., Hangzhou, Zhejiang, China

7. Department of Laboratory Medicine, Peking University Third Hospital, Beijing, China

Abstract

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 (r2), adjusted r2, 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.

Funder

National Natural Science Foundation of China for Distinguished Young Scholars

Innovation & Transfer Fund of Peking University Third Hospital

Major National R&D Projects of China

National Natural Science Foundation of China

Capital Health Research and Development of Special Project

Beijing-Tianjin-Hebei Basic Research Cooperation Project

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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