scholarly journals Modeling Age at Menopause Using Serum Concentration of Anti-Mullerian Hormone

2013 ◽  
Vol 98 (2) ◽  
pp. 729-735 ◽  
Author(s):  
Fahimeh Ramezani Tehrani ◽  
Masoud Solaymani-Dodaran ◽  
Maryam Tohidi ◽  
Mahmood Reza Gohari ◽  
Fereidoun Azizi
Keyword(s):  
Serum Concentration ◽  
Failure Time ◽  
Population Based ◽  
Accelerated Failure Time Model ◽  
Correct Prediction ◽  
Eligibility Criteria ◽  
Time Model ◽  
Age At Menopause ◽  
Reproductive Aged Women

Abstract Context: Anti-Mullerian hormone (AMH) has already been used for prediction of age at menopause with promising results. Objective: We aimed to improve our previous prediction of age at menopause in a population-based cohort by including all eligible subjects and additional follow-up time. Design and Setting: All reproductive-aged women who met our eligibility criteria were selected from the Tehran Lipid and Glucose Study. The serum concentration of AMH was measured at the time of recruitment, and participant's date of menopause was recorded over a 10-year follow-up. Subjects: A total of 1015 women, aged 20 to 50 years, with regular and predictable menstrual cycles at the initiation of the study were recruited. Main Outcome Measure: The actual ages at menopause were compared with the predicted ones obtained from accelerated failure time model. Results: We observed 277 occurrences of menopause. Median menopausal age was 50 years (range 30.1–58.2 years). The median (SD) of differences between the actual menopausal age and those predicted by our model was 0.5 (2.5) years. Model adequacy (measured by C-statistics) for correct prediction of age at menopause was 92%. The estimated ages at menopause and their 95% confidence intervals for a range of values of AMH and age were calculated and summarized in a table. Conclusions: Using a model built on age and AMH, we can predict age at menopause many years earlier. This could provide opportunities for interventions in those who are at risk of early or late menopause.

Improving Prediction of Age at Menopause Using Multiple Anti-Müllerian Hormone Measurements: the Tehran Lipid-Glucose Study

2020 ◽  
Vol 105 (5) ◽  
pp. 1589-1598 ◽  
Author(s):  
Fahimeh Ramezani Tehrani ◽  
Razieh Bidhendi Yarandi ◽  
Masoud Solaymani-Dodaran ◽  
Maryam Tohidi ◽  
Faezeh Firouzi ◽  
...  
Keyword(s):  
Failure Time ◽  
Reproductive Age ◽  
Accelerated Failure Time Model ◽  
Accelerated Failure Time ◽  
Time Model ◽  
Age At Menopause ◽  
Decline Rate ◽  
Accelerated Failure ◽  
Failure Time Model

Abstract Context 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. Objective The objective of this study was to determine whether multiple AMH measurements can improve the prediction of age at menopause. Design 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. Results 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. Conclusion Prediction of age at menopause could be improved by multiple AMH measurements; it will be useful in identifying women at risk of early menopause.

Cognitive Activity and Onset Age of Incident Alzheimer Disease Dementia

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012388
Author(s):  
Robert S. Wilson ◽  
Tianhao Wang ◽  
Lei Yu ◽  
Francine Grodstein ◽  
David A. Bennett ◽  
...  
Keyword(s):  
Failure Time ◽  
Cognitive Activity ◽  
Older Age ◽  
Activity Score ◽  
Accelerated Failure Time Model ◽  
Accelerated Failure Time ◽  
Onset Age ◽  
Time Model ◽  
Dementia Onset

Objective:To test the hypothesis that higher level of cognitive activity predicts older age of dementia onset in Alzheimer's disease (AD) dementia.Methods:As part of a longitudinal cohort study, 1,903 older persons without dementia at enrollment reported their frequency of participation in cognitively stimulating activities. They had annual clinical evaluations to diagnose dementia and AD, and the deceased underwent neuropathologic examination. In analyses, we assessed the relation of baseline cognitive activity to age at diagnosis of incident AD dementia and to postmortem markers of AD and other dementias.Results:During a mean of 6.8 years of follow-up, 457 individuals were diagnosed with incident AD at a mean age of 88.6 (SD = 6.4; range: 64.1-106.5). In an extended accelerated failure time model, higher level of baseline cognitive activity (mean 3.2, SD = 0.7) was associated with older age of AD dementia onset (estimate = 0.026; 95% confidence interval: 0.013. 0.039). Low cognitive activity (score = 2.1, 10th percentile) was associated with a mean onset age of 88.6 compared to a mean onset age of 93.6 associated with high cognitive activity (score = 4.0, 90th percentile). Results were comparable in subsequent analyses that adjusted for potentially confounding factors. In 695 participants who died and underwent a neuropathologic examination, cognitive activity was unrelated to postmortem markers of AD and other dementias.Conclusion:A cognitively active lifestyle in old age may delay the onset of dementia in AD by as much as 5 years.

scholarly journals Estimation of indirect effect when the mediator is a censored variable

2017 ◽  
Vol 27 (10) ◽  
pp. 3010-3025 ◽  
Author(s):  
Jian Wang ◽  
Sanjay Shete
Keyword(s):  
Censored Data ◽  
Indirect Effect ◽  
Indirect Effects ◽  
Failure Time ◽  
Fasting Glucose ◽  
Accelerated Failure Time Model ◽  
Outcome Variable ◽  
Mediation Model ◽  
Time Model ◽  
Age At Menopause

A mediation model explores the direct and indirect effects of an initial variable ( X) on an outcome variable ( Y) by including a mediator ( M). In many realistic scenarios, investigators observe censored data instead of the complete data. Current research in mediation analysis for censored data focuses mainly on censored outcomes, but not censored mediators. In this study, we proposed a strategy based on the accelerated failure time model and a multiple imputation approach. We adapted a measure of the indirect effect for the mediation model with a censored mediator, which can assess the indirect effect at both the group and individual levels. Based on simulation, we established the bias in the estimations of different paths (i.e. the effects of X on M [ a], of M on Y [ b] and of X on Y given mediator M [ c’]) and indirect effects when analyzing the data using the existing approaches, including a naïve approach implemented in software such as Mplus, complete-case analysis, and the Tobit mediation model. We conducted simulation studies to investigate the performance of the proposed strategy compared to that of the existing approaches. The proposed strategy accurately estimates the coefficients of different paths, indirect effects and percentages of the total effects mediated. We applied these mediation approaches to the study of SNPs, age at menopause and fasting glucose levels. Our results indicate that there is no indirect effect of association between SNPs and fasting glucose level that is mediated through the age at menopause.

scholarly journals Anthropometric Indices and Age at Natural Menopause: A 15-Year Follow-Up Population-Based Study

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Maryam Farahmand ◽  
Fahimeh Ramezani Tehrani ◽  
Maryam Rahmati ◽  
Fereidoun Azizi
Keyword(s):  
Longitudinal Study ◽  
Failure Time ◽  
Shape Index ◽  
Population Based ◽  
Anthropometric Indices ◽  
Eligibility Criteria ◽  
Natural Menopause ◽  
Time Ratio ◽  
Study Results

Background: Following menopause, the risk of many diseases is increased, and this situation may be due to changes in anthropometric indices (AI), while the association between adiposity and age at natural menopause (ANM) is not clear yet. Objectives: This longitudinal study was conducted to investigate the ability of AI in predicting ANM. Methods: For this purpose, a total of 3,876 women aged > 20 years old from participants of the Tehran lipid and glucose study (TLGS) met our eligibility criteria. The association between ANM and various AIs was assessed using the Accelerated Failure Time (AFT) model, and time ratio (TR) with 95% confidence intervals were reported in this longitudinal study. Results: The median [interquartile range (IQR) 25 - 75] of the survival time was 12.5 (7.9 - 15.8) years. At the end of the follow-up, 1,479 (38.2%) of the participants reached menopause. The median time to natural menopause was decreased by about 2% with one standard deviation (SD) increase of both a body shape index (ABSI) (time ratio (TR): 0.98, 95% CI: 0.97, 0.99) and lipid accumulation product (LAP) (TR: 0.98, 95% CI: 0.98, 0.99) z-scores; and this time was increased by about 1% (TR: 1.01, 95% CI: 1.00, 1.02) with one SD increase in body mass index (BMI) z-score. Conclusions: The ABSI, LAP, and BMI were the most useful AIs for identification of the time to menopause onset, and ABSI and LAP were inversely associated with the ANM. Also, the BMI was directly associated with the ANM.

Dependability Analysis of Homogeneous Distributed Software/Hardware Systems

2015 ◽  
Vol 22 (02) ◽  
pp. 1550007
Author(s):  
G. Vijayalakshmi
Keyword(s):  
Reliability Analysis ◽  
Distributed System ◽  
Failure Time ◽  
Load Sharing ◽  
Accelerated Failure Time Model ◽  
Time To Failure ◽  
Critical Systems ◽  
Time Model ◽  
Distributed Software ◽  
Dependability Analysis

With the increasing demand for high availability in safety-critical systems such as banking systems, military systems, nuclear systems, aircraft systems to mention a few, reliability analysis of distributed software/hardware systems continue to be the focus of most researchers. The reliability analysis of a homogeneous distributed software/hardware system (HDSHS) with k-out-of-n : G configuration and no load-sharing nodes is analyzed. However, in practice the system load is shared among the working nodes in a distributed system. In this paper, the dependability analysis of a HDSHS with load-sharing nodes is presented. This distributed system has a load-sharing k-out-of-(n + m) : G configuration. A Markov model for HDSHS is developed. The failure time distribution of the hardware is represented by the accelerated failure time model. The software faults are detected during software testing and removed upon failure. The Jelinski–Moranda software reliability model is used. The maintenance personal can repair the system up on both software and hardware failure. The dependability measures such as reliability, availability and mean time to failure are obtained. The effect of load-sharing hosts on system hazard function and system reliability is presented. Furthermore, an availability comparison of our results and the results in the literature is presented.

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