Study Question: Do ovarian reserve tests (ORTs) predict age at natural menopause (ANM) in a cohort of healthy women with a regular menstrual cycle?
Summary Answer: Of the ORTs researched, anti-Müllerian hormone (AMH) alone predicts age at menopause. However, its predictive value decreased with increasing age of the woman, prediction intervals were broad and extreme ages at menopause could not be predicted.
What Is Known Already: A fixed interval is hypothesized to exist between ANM and age at loss of natural fertility. Therefore, if it is possible to predict ANM, one could identify women destined for early menopause and thus at higher risk for age-related subfertility. Of ORTs researched in the prediction of ANM, AMH is the most promising one.
Study Design, Study Size And Duration: A long-term, extended follow-up study was conducted, results of the first follow-up round were previously published. Two hundred and sixty-five normo-ovulatory women (21-46 years) were included between 1992 and 2001, 49 women (18.5%) could not be reached in the current follow-up round.
Participants, Setting, Methods: Two hundred and sixty-five healthy normo-ovulatory women were included, recruited in an Academic hospital. We measured baseline AMH, follicle-stimulating hormone and the antral follicle count (AFC). At follow-up (2009 and 2013), menopausal status was determined via questionnaires. Cox regression analysis calculated time to menopause (TTM) using age and ORT. A check of (non-) proportionality of the predictive effect of AMH was performed. A Weibull survival model was used in order to predict individual ANM.
Main Results And The Role Of Chance: In total, 155 women were available for analyses. Eighty-one women (37.5%) had become post-menopausal during follow-up. Univariable Cox regression analysis demonstrated age and ORTs to be significantly correlated with TTM. Multivariable Cox regression analysis, adjusting for baseline age and smoking; however, demonstrated AMH alone to be an independent predictor of TTM (Hazard Ratio 0.70, 95% Confidence Interval 0.56-0.86, P-value <0.001). A (non-)proportionality analysis of AMH over time demonstrated AMH's predictive effect to decline over time.
Limitations, Reason For Caution: The observed predictive effect of AMH became less strong with increasing age of the woman. Individual AMH-based age at menopause predictions did not cover the full range of menopausal ages, but did reduce the variation around the predicted ANM from 20 to 10.1 years.
Wider Implications Of The Findings: Age-specific AMH levels are predictive for ANM. Unlike in our previous publication however, a declining AMH effect with increasing age was observed. This declining AMH effect is in line with recent long-term follow-up data published by others. Moreover, the accompanying predictive inaccuracy observed in individual age at menopause predictions based on AMH, makes this marker currently unsuitable for use in clinical practice.
Study Funding/competing Interests: No external funds were used for this study. M.D., M.J.C.E, S.L.B., G.J.S. and I.A.J.R. have nothing to declare. J.S.E.L. has received fees and grant support from the following companies (in alphabetical order): Ferring, Merck-Serono, MSD, Organon, Serono and Schering Plough. F.J.M.B. receives monetary compensation: member of the external advisory board for Merck Serono, the Netherlands; consultancy work for Gedeon Richter, Belgium; educational activities for Ferring BV, the Netherlands; strategic cooperation with Roche on automated AMH assay development.
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http://dx.doi.org/10.1093/humrep/dew112 | DOI Listing |
J Clin Anesth
January 2025
Department of Anesthesiology, Nanjing Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China. Electronic address:
Objective: To explore risk factors for 1-year postoperative mortality and to identify its association with the Revised Cardiac Risk Index (RCRI).
Methods: This was a retrospective cohort study involving 54,933 patients aged 18 years and above who were surgically treated under general or regional anesthesia in a tertiary hospital in Singapore. Independent risk factors for 1-year postoperative mortality were identified by univariate Cox regression analysis.
Nutr Res
December 2024
Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China. Electronic address:
The potential impact of one-carbon metabolism (OCM)-related B vitamins (vitamin B, B, B, and folate) on colorectal cancer survival warrants investigation but research is sparse. This cohort study examined the association between the prediagnostic dietary intakes of OCM-related B vitamins and colorectal cancer survival. A total of 2799 colorectal cancer patients from the Guangdong Colorectal Cancer Cohort, enrolled at baseline in 2010, were followed for mortality outcomes through 2023.
View Article and Find Full Text PDFAm J Manag Care
January 2025
Arine, 595 Market St #2550, San Francisco, CA 94105. Email:
Objective: To assess the effects of a nurse-led personalized care plan on the duration of olaparib therapy among patients with cancer.
Study Design: Cohort study conducted from January 2020 to June 2022.
Methods: Data from an independent specialty pharmacy were used to identify patients 18 years and older with at least 1 olaparib (Lynparza) prescription who were at high risk for olaparib nonadherence as assessed using a pharmacy intake survey.
Ann Am Thorac Soc
January 2025
University of California San Francisco, Department of Epidemiology and Biostatistics, San Francisco, California, United States.
Rationale: Globally, in 2019, chronic obstructive pulmonary disease (COPD) was the third leading cause of death. While tobacco smoking is the predominant risk factor, the role of long-term air pollution exposure in increasing risk of COPD remains unclear. Moreover, there are few studies that have been conducted in racial and ethnic minoritized and socioeconomically diverse populations, while accounting for smoking history and other known risk factors.
View Article and Find Full Text PDFAnn Med
December 2025
Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, PR China.
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Methods: Initially, a comprehensive analysis was conducted on exosome-related genes from the BRCA cohort in The Cancer Genome Atlas (TCGA) database. Three prognostic genes (JUP, CAPZA1 and ARVCF) were identified through univariate Cox regression and Lasso-Cox regression analyses, and a metastasis-related risk score model was established based on these genes.
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