Unknown

Dataset Information

0

Modeling Short- and Long-Term Characteristics of Follicle Stimulating Hormone as Predictors of Severe Hot Flashes in Penn Ovarian Aging Study.


ABSTRACT: The Penn Ovarian Aging Study tracked a population-based sample of 436 women aged 35-47 years to determine associations between reproductive hormone levels and menopausal symptoms. We develop a joint modeling method that uses the individual-level longitudinal measurements of follicle stimulating hormone (FSH) to predict the risk of severe hot flashes in a manner that distinguishes long-term trends of the mean trajectory, cumulative changes captured by the derivative of mean trajectory, and short-term residual variability. Our method allows the potential effects of longitudinal trajectories on the health risks to vary and accumulate over time. We further utilize the proposed methods to narrow the critical time windows of increased health risks. We find that high residual variation of FSH is a strong predictor of hot flash risk, and that the high cumulative changes of the FSH mean trajectories in the 52.5-55 year age range also provides evidence of increased risk above and beyond that of short-term FSH residual variation by itself.

SUBMITTER: Jiang B 

PROVIDER: S-EPMC4628832 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Modeling Short- and Long-Term Characteristics of Follicle Stimulating Hormone as Predictors of Severe Hot Flashes in Penn Ovarian Aging Study.

Jiang Bei B   Wang Naisyin N   Sammel Mary D MD   Elliott Michael R MR  

Journal of the Royal Statistical Society. Series C, Applied statistics 20150326 5


The Penn Ovarian Aging Study tracked a population-based sample of 436 women aged 35-47 years to determine associations between reproductive hormone levels and menopausal symptoms. We develop a joint modeling method that uses the individual-level longitudinal measurements of follicle stimulating hormone (FSH) to predict the risk of severe hot flashes in a manner that distinguishes long-term trends of the mean trajectory, cumulative changes captured by the derivative of mean trajectory, and short-  ...[more]

Similar Datasets

| S-EPMC7311873 | biostudies-literature
| S-EPMC9600712 | biostudies-literature
| S-EPMC6534497 | biostudies-literature
| S-EPMC4712933 | biostudies-literature
| S-EPMC4250110 | biostudies-literature
| S-EPMC7702187 | biostudies-literature
| S-EPMC7302518 | biostudies-literature
| S-EPMC6813335 | biostudies-literature
| S-EPMC7588789 | biostudies-literature
| S-EPMC3348539 | biostudies-literature