title: Bayesian estimation of associations between identified longitudinal hormone subgroups and age at final menstrual period.
abstract: BACKGROUND
  Although follicle stimulating hormone (FSH) is known to be predictive of age at final menstrual period (FMP), previous methods use FSH levels measured at time points that are defined relative to the age at FMP, and hence are not useful for prospective prediction purposes in clinical settings where age at FMP is an unknown outcome. This study is aimed at assessing whether FSH trajectory feature subgroups identified relative to chronological age can be used to improve the prediction of age at FMP.
  
  
  METHODS
  We develop a Bayesian model to identify latent subgroups in longitudinal FSH trajectories, and study the relationship between subgroup membership and age at FMP. Data for our study is taken from the Penn Ovarian Aging study, 1996-2010. The proposed model utilizes mixture modeling and nonparametric smoothing methods to capture hypothesized latent subgroup features of the FSH longitudinal trajectory; and simultaneously studies the prognostic value of these latent subgroup features to predict age at FMP.
  
  
  RESULTS
  The analysis identified two FSH trajectory subgroups that were significantly associated with FMP age: 1) early FSH class (15%), which displayed initial increases in FSH shortly after age 40; and 2) late FSH class (85%), which did not have a rise in FSH until after age 45. The use of FSH subgroup memberships, along with class-specific characteristics, i.e., level and rate of FSH change at class-specific pre-specified ages, improved prediction of FMP age by 20-22% in comparison to the prediction based on previously identified risk factors (BMI, smoking and pre-menopausal levels of anti-mullerian hormone (AMH)).
  
  
  CONCLUSIONS
  To the best of our knowledge, this work is the first in the area to demonstrate the existence of subgroups in FSH trajectory patterns relative to chronological age and the fact that such a subgroup membership possesses prediction power for age at FMP. Earlier ages at FMP were found in a subgroup of women with rise in FSH levels commencing shortly after age 40, in comparison to women who did not exhibit an increase in FSH until after 45 years of age. Periodic evaluations of FSH in these age ranges are potentially useful for predicting age at FMP.
authors.affiliation: Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada. bei1@ualberta.ca.
authors.forename: Bei
authors.initials: B
authors.lastname: Jiang
authors.affiliation: Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. msammel@mail.med.upenn.edu.
authors.forename: Mary D
authors.initials: MD
authors.lastname: Sammel
authors.affiliation: Departments of Obstetrics and Gynecology and Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. freemane@mail.med.upenn.edu.
authors.forename: Ellen W
authors.initials: EW
authors.lastname: Freeman
authors.affiliation: Department of Statistics, University of Michigan, Ann Arbor, MI, USA. nwangaa@umich.edu.
authors.forename: Naisyin
authors.initials: N
authors.lastname: Wang
mesh_terms: D000328:Adult; D017668:Age of Onset; D000375:Aging; D001499:Bayes Theorem; D005260:Female; D005640:Follicle Stimulating Hormone / Q000097:blood*; D006801:Humans; D008593:Menopause; D008875:Middle Aged
chemical_list: D005640:Follicle Stimulating Hormone