A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Predicting the age at natural menopause in middle-aged women (2021)

Hyvärinen, M., Karvanen, J., Aukee, P., Tammelin, T. H., Sipilä, S., Kujala, U. M., Kovanen, V., Rantalainen, T., & Laakkonen, E. K. (2021). Predicting the age at natural menopause in middle-aged women. Menopause: the Journal of the North American Menopause Society, 28(7), 792-799. https://doi.org/10.1097/GME.0000000000001774

JYU-tekijät tai -toimittajat

Hyvärinen, Matti
Karvanen, Juha
Sipilä, Sarianna
Kujala, Urho
Kovanen, Vuokko
Rantalainen, Timo
Laakkonen, Eija

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Hyvärinen, Matti; Karvanen, Juha; Aukee, Pauliina; Tammelin, Tuija H.; Sipilä, Sarianna; Kujala, Urho M.; Kovanen, Vuokko; Rantalainen, Timo; Laakkonen, Eija K.

Lehti tai sarja: Menopause: the Journal of the North American Menopause Society

ISSN: 1530-0374

eISSN: 1530-0374

Julkaisuvuosi: 2021

Ilmestymispäivä: 12.04.2021

Volyymi: 28

Lehden numero: 7

Artikkelin sivunumerot: 792-799

Kustantaja: Lippincott Williams & Wilkins

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1097/GME.0000000000001774

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/75212

Lisätietoja: Video Summary:http://links.lww.com/MENO/A743.

Tiivistelmä

Objective: To predict the age at natural menopause (ANM).
Methods: Cox models with time-dependent covariates were utilized for ANM prediction using longitudinal data from 47 to 55-year-old women (n ¼279) participating in the Estrogenic Regulation of Muscle Apoptosis study. The ANM was assessed retrospectively for 105 women using bleeding diaries. The predictors were chosen from the set of 32 covariates by using the lasso regression (model 1). Another easy-to-access model (model 2) was created by using a subset of 16 self-reported covariates. The predictive performance was quantified with c-indices and by studying the means and standard deviations of absolute errors (MAE ±SD) between the predicted and observed ANM.
Results: Both models included alcohol consumption, vasomotor symptoms, self-reported physical activity, and relationship status as predictors. Model 1 also included estradiol and follicle-stimulating hormone levels as well as SD of menstrual cycle length, while model 2 included smoking, education, and the use of hormonal contraception as additional predictors. The mean c-indices of 0.76 (95% CI 0.71-0.81) for model 1 and 0.70 (95% CI 0.65-0.75) for model 2 indicated good concordance between the predicted and observed values. MAEs of 0.56 ± 0.49 and 0.62 ± 0.54 years respectively for model 1 and 2 were clearly smaller than the MAE for predicted sample mean (1.58 ±1.02).
Conclusions: In addition to sex hormone levels, irregularity of menstrual cycle, and menopausal symptoms, also life habits and socioeconomic factors may provide useful information for ANM prediction. The suggested approach could add value for clinicians’ decision making related to the use of contraception and treatments for menopausal symptoms in perimenopausal women.

YSO-asiasanat: keski-ikä; vaihdevuodet; kuukautiset; ennusteet; elintavat; tilastolliset mallit

Vapaat asiasanat: final menstrual period; menopausal transition; menopause prediction; perimenopause; premenopause.

Tieteenalat: