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- Title
Improving Prediction of Age at Menopause Using Multiple Anti-Müllerian Hormone Measurements: the Tehran Lipid-Glucose Study.
- Authors
Ramezani Tehrani, Fahimeh; Bidhendi Yarandi, Razieh; Solaymani-Dodaran, Masoud; Tohidi, Maryam; Firouzi, Faezeh; Azizi, Fereidoun
- Abstract
<bold>Context: </bold>Several statistical models were introduced for the prediction of age at menopause using a single measurement of anti-müllerian hormone (AMH); however, individual prediction is challenging and needs to be improved.<bold>Objective: </bold>The objective of this study was to determine whether multiple AMH measurements can improve the prediction of age at menopause.<bold>Design: </bold>All eligible reproductive-age women (n = 959) were selected from the Tehran Lipid and Glucose Study. The serum concentration of AMH was measured at the time of recruitment and twice after that at an average of 6-year intervals. An accelerated failure-time model with Weibull distribution was used to predict age at menopause, using a single AMH value vs a model that included the annual AMH decline rate. The adequacy of these models was assessed using C statistics.<bold>Results: </bold>The median follow-up period was 14 years, and 529 women reached menopause. Adding the annual decline rate to the model that included single AMH improved the model's discrimination adequacy from 70% (95% CI: 67% to 71%) to 78% (95% CI: 75% to 80%) in terms of C statistics. The median of differences between actual and predicted age at menopause for the first model was -0.48 years and decreased to -0.21 in the model that included the decline rate. The predicted age at menopause for women with the same amount of age-specific AMH but an annual AMH decline rate of 95 percentiles was about one decade lower than in those with a decline rate of 5 percentiles.<bold>Conclusion: </bold>Prediction of age at menopause could be improved by multiple AMH measurements; it will be useful in identifying women at risk of early menopause.
- Subjects
OLDER women; MENOPAUSE; FAILURE time data analysis; WEIBULL distribution; STATISTICAL models; CLIMACTERIC
- Publication
Journal of Clinical Endocrinology & Metabolism, 2020, pN.PAG
- ISSN
0021-972X
- Publication type
journal article
- DOI
10.1210/clinem/dgaa083