Does AMH relate to timing of menopause? Results of an Individual Patient Data meta- analysis.

CONTEXT: Anti-Müllerian hormone based (AMH) age at menopause predictions remain cumbersome due to predictive inaccuracy. OBJECTIVE: To perform an Individual Patient Data (IPD) meta-analysis, regarding AMH based menopause prediction. DATA SOURCES: A systematic literature search was performed using PubMed, Embase and Cochrane databases. STUDY SELECTION: Prospective cohort studies regarding menopause prediction using serum AMH levels were selected by consensus discussion. DATA SELECTION: Individual cases were included if experiencing a regular cycle at baseline. Exclusion criteria were hormone use and gynecological surgery. DATA SYNTHESIS: 2596 women were included, 1077 experienced menopause. A multivariable Cox regression analysis assessed time to menopause (TTM) using age and AMH. AMH predicted TTM, however, added value on top of age was poor (age alone C-statistic 84%; age + AMH HR 0.66 95% CI 0.61-0.71, C-statistic 86%). Moreover, the capacity of AMH to predict early (≤45 years) and late menopause (≥55 years) was assessed. An added effect of AMH was demonstrated for early menopause (age alone C-statistic 52%; age + AMH HR 0.33, 95% CI 0.24-0.45, C-statistic 80%). A Weibull regression model calculating individual age at menopause revealed that predictive inaccuracy remained present and increased with decreasing age at menopause. Lastly, a check of non-proportionality of the predictive effect of AMH demonstrated a reduced predictive effect with increasing age. CONCLUSION: AMH was a significant predictor of TTM and especially of time to early menopause. However, individual predictions of age at menopause demonstrated a limited precision, particularly when concerning early age at menopause, making clinical application troublesome.

Anti-Müllerian hormone does not predict time to pregnancy: results of a prospective cohort study.

In order to study whether ovarian reserve tests (ORTs) can predict time to ongoing pregnancy, we conducted a prospective cohort study in a cohort of healthy pregnancy planners. A total of 102 pregnancy planners were followed for 1 year, or until ongoing pregnancy occurred, after cessation of contraceptives). A baseline measurement of anti-Müllerian hormone (AMH), follicle-stimulating hormone (FSH) and antral follicle count (AFC) was conducted. At the end of follow-up, a semen analysis was performed and chlamydia antibody titres were assessed. A univariate prediction model demonstrated age and the AFC to be significantly capable of predicting time to pregnancy (hazard ratio 0.92, 95% CI 0.87-0.98, p = 0.01; 1.04, 95% CI 1.01-1.07, p = 0.02 respectively). In the multivariate model, however, correcting for female age, we found no predictive effect of AMH, basal FSH or the AFC for time to ongoing pregnancy (hazard ratios 1.43, 95% CI 0.84-2.46, p = 0.36; 0.96, 95% CI 0.86-1.06, p = 0.43; 1.03, 95% CI 1.00-1.07, p = 0.08, respectively). This was confirmed by the low C-statistic. We therefore concluded that baseline AMH, AFC or FSH levels do not predict time to ongoing pregnancy in a cohort of healthy pregnancy planners. These results limit the usability of these ORTs in the assessment of current fertility.

Does anti-Müllerian hormone predict menopause in the general population? Results of a prospective ongoing cohort study.

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.

The Relationship Between Variation in Size of the Primordial Follicle Pool and Age at Natural Menopause.

CONTEXT: Menopause has been hypothesized to occur when the nongrowing follicle (NGF) number falls below a critical threshold. Age at natural menopause can be predicted using NGF numbers and this threshold. These predictions support the use of ovarian reserve tests, reflective of the ovarian follicle pool, in menopause forecasting. OBJECTIVE: The objective of the study was to investigate the hypothesis that age-specific NGF numbers reflect age at natural menopause. DESIGN AND SETTING: Histologically derived NGF numbers obtained from published literature (n = 218) and distribution of menopausal ages derived from the population-based Prospect-European Prospective Investigation into Cancer and Nutrition (Prospect-EPIC) cohort (n = 4037) were combined. PARTICIPANTS: NGF data were from single ovaries that had been obtained postnatally for various reasons, such as elective surgery or autopsy. From the Prospect-EPIC cohort, women aged 58 years and older with a known age at natural menopause were selected. INTERVENTIONS: There were no interventions. MAIN OUTCOME MEASURE(S): Conformity between observed age at menopause in the Prospect-EPIC cohort and NGF-predicted age at menopause from a model for age-related NGF decline constructed using a robust regression analysis. A critical threshold for NGF number was estimated by comparing the probability distribution of the age at which the NGF numbers fall below this threshold with the observed distribution of age at natural menopause from the Prospect-EPIC cohort. RESULTS: The distributions of observed age at natural menopause and predicted age at natural menopause showed close conformity. CONCLUSION: The close conformity observed between NGF-predicted and actual age at natural menopause supports the hypothesis that that the size of the primordial follicle pool is an important determinant for the length of the individual ovarian life span and supports the concept of menopause prediction using ovarian reserve tests, such as anti-Müllerian hormone and antral follicle count, as derivatives of the true ovarian reserve.

Anti-Mullerian hormone is a more accurate predictor of individual time to menopause than mother's age at menopause.

STUDY QUESTION: In the prediction of time to menopause (TTM), what is the added value of anti-Müllerian hormone (AMH) when mother's age at natural menopause (ANM) is also known? SUMMARY ANSWER: AMH is a more accurate predictor of individual TTM than mother's age at menopause. WHAT IS KNOWN ALREADY: Mother's ANM is considered a proxy for daughter's ANM although studies on its predictive accuracy are non-existent. AMH is a biomarker with a known capacity to predict ANM. However, its added value on top of known predictors, like mother's ANM, is unknown. STUDY DESIGN, SIZE, DURATION: Population-based cohort studies were used. To assess any additive predictive value of mother's ANM, 164 mother-daughter pairs were used (Group 1). To assess the added value of AMH, a second group of 150 women in whom AMH and mother's ANM were recorded prior to a 12-year follow-up period during which daughter's ANM was assessed was used (Group 2). PARTICIPANTS/MATERIALS, SETTING, METHODS: Group 1 consisted of participants of the DOM cohort (an ongoing breast cancer study). Group 2 was a pooled cohort of women with regular menstrual cycles from two independent published studies. Cox proportional hazards analysis estimated uni- and multivariate regression coefficients for female age at study entry, mother's ANM and AMH in the prediction of TTM. Discrimination of models was assessed with C-statistics. Clinical added value of AMH was quantified with a net reclassification index (NRI). MAIN RESULTS AND THE ROLE OF CHANCE: A model with female age and mother's ANM had a c-statistic of 79 and 85% in groups 1 and 2, respectively. Both age and mother's ANM were significantly associated with TTM (HR 1.54 and HR 0.93 for age and mother's ANM in Cohort 1 and HR 1.59 and HR 0.89 in Group 2, respectively. P-value for all <0.001). In Group 2, the multivariate model with age, mother's ANM and AMH had a c-statistic of 92%, and only female age and AMH remained significantly associated with TTM (HR 1.41 P < 0.0001; HR 0.93 P = 0.08 and HR 0.06 P < 0.0001 for age, mother's ANM and AMH, respectively). The mean weighted NRI suggests that a 47% improvement in predictive accuracy is offered by adding AMH to the model of age and mother's ANM. In conclusion, AMH and mother's ANM both have added value in forecasting TTM for the daughter based on her age. In comparison, AMH is a more accurate added predictor of TTM than mother's ANM. LIMITATIONS, REASONS FOR CAUTION: The cohort of women is relatively small and different cohorts of women were pooled. WIDER IMPLICATIONS OF THE FINDINGS: This study shows that AMH is a more accurate predictor of ANM than mother's ANM. However, before achieving clinical applicability, the certainty with which a woman's prediction is made must improve. The association between mother's ANM and TTM in daughters did not appear to be influenced by whether ANM was recorded by mothers or daughters--an important finding because in the clinical setting daughters usually provide this information. STUDY FUNDING/COMPETING INTEREST(S): No funding was received and there were no competing interests in direct relation to this study.