4.7 Article

Endocrine features of menstrual cycles in middle and late reproductive age and the menopausal transition classified according to the staging of reproductive aging workshop (STRAW) staging system

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JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM
卷 92, 期 8, 页码 3060-3067

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OXFORD UNIV PRESS INC
DOI: 10.1210/jc.2007-0066

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Context: Female reproductive aging based on changes in menstrual cycle length and frequency progresses through a number of stages as defined by the Stages of Reproductive Aging Workshop (STRAW) staging criteria. Objective: This paper provides a comprehensive description of the endocrine features associated with the STRAW stages. Design: Healthy women aged 21-35 and 45-55 yr submitted three blood samples a week over a single menstrual cycle. They were classified as mid- reproductive age (n = 21), late-reproductive age (n = 16), early menopause transition (n = 16), and late menopause transition (n = 23). Results: There were nine, one, zero, and two anovulatory cycles identified in the late menopause transition, early menopause transition, late-reproductive age, and mid-reproductive age groups, respectively. Ovulatory cycle FSH, LH, and estradiol levels increased with progression of STRAW stage (P = 0.001, P < 0.01, and P < 0.05, respectively), and mean luteal phase serum progesterone decreased (P < 0.01). Early cycle (ovulatory and anovulatory) inhibin B decreased steadily across the STRAW stages (P < 0.01) and was largely undetectable during elongated ovulatory and anovulatory cycles in the menopause transition. Anti- Mullerian hormone decreased markedly (10- to 15-fold) and progressively across the STRAW stages (P < 0.01 and P < 0.001, respectively). Conclusions: Progression through the STRAW stages is associated with elevations in serum FSH, LH, and estradiol and decreases in luteal phase progesterone. The marked fall in inhibin B and particularly anti-Mullerian hormone indicate that they may be useful in predicting STRAW stage but future analyses of early cycle measurements on larger cohorts are needed to draw predictive conclusions.

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