A new research effort has developed an algorithm -- a logical sequence of steps for solving a problem that can be translated into a computer program -- that will allow middle-aged women reaching menopause to accurately identify the timing of their menstrual cycle.
Background
Measuring hormones in a woman's urine has been demonstrated to be useful in field studies of women with a variety of reproductive conditions. By establishing urinary hormone metabolites as proxy markers of circulating gonadotropin (a hormone capable of promoting gonadal growth and function) sex steroid hormones, it was possible to determine when a woman was most fertile as well as to describe the effects of exercise, smoking, weight, and reproductive aging on hormone patterns. The day-to-day patterns of secretion of LH, FSH (follicle-stimulating hormone), estradiol, and progesterone are duplicated reliably by use of an overnight urine specimen. Correction of the urinary hormone value with creatinine excretion reduces within women variations in hormone concentrations, which can be considerable. Preservation of urine with glycerol is required to maintain gonadotropin activity in some but not all assays.
An ongoing multisite, multiethnic, and longitudinal examination of midlife women is the Study of Women's Health Across the Nation (SWAN). SWAN attempts to characterize the reproductive hormone patterns as women approach and traverse the menopausal transition. Included in this effort is the Daily Hormone Substudy that collects and analyzes cycles of daily urinary hormones annually, thus providing both cross-sectional and longitudinal data.
Unlike most previous studies in field settings, the women in SWAN are being observed as their cycles become irregular and eventually cease. A research team composed of members from across the country noted that cycle patterns of women as they traverse the menopause are relatively unexplored. The application of algorithms designed to identify cycles with evidence of estrogen and progesterone activity among younger, regularly cycling women may be less reliable as reproductive aging occurs.
A New Study
A team of physiologists sought to identify in a prospective fashion the characteristics of a presumably ovulatory menstrual cycle that would appear to be most robust, and to incorporate them into a step-by-step process to assess ovarian function in SWAN's sample of women. They examined previously tested algorithms and assessed their ability to provide a standardized, objective assessment of presumed ovulatory status that would maintain predictive capability of hormonal function as study participants preceded toward menopause.
The authors of "Assessing Menstrual Cycles with Urinary Hormone Assays" are N. Santoro from The Division Of Reproductive Endocrinology, Department of Obstetrics, Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY; S. L. Crawford, J. E. Allsworth, and P. McGaffigan at the New England Research Institutes, Watertown, MA; E. B. Gold and B. L. Lasley, from the Departments Of Epidemiology and Preventive Medicine and Population Health and Reproduction, University Of California at Davis, Davis, CA; G. A. Greendale, S. Korenman, and M. Schocken at The Division Of Geriatrics and Center for Health Sciences, University Of California At Los Angeles, Los Angeles, CA; D. McConnell, R. Midgely, and M. Sowers, from The Reproductive Sciences Program and Department of Epidemiology, University of Michigan, Ann Arbor, MI; G. Weiss at the Department of Obstetrics, Gynecology and Women's Health, University of Medicine and Dentistry of New Jersey, Newark, NJ. Their findings appear in the March 2003 edition of the American Journal of Physiology--Endocrinology and Metabolism, one of 14 scientific journals published each month by the American Physiological Society (APS).
Methodology
Women were enrolled from all seven SWAN clinical sites. Eligibility criteria required an intact uterus and at least one ovary present at the time of recruitment; at least one menstrual period in the three months before recruitment; no use of sex steroid hormones within three months before recruitment; not currently pregnant; and compliance in maintaining daily menstrual calendars.
A total of 848 reproductively aging women participated in the study in which their urinary gonadotropins and sex steroid metabolites were assessed during one complete menstrual cycle or up to 50 consecutive days. Urine was analyzed for LH, FSH, estrone conjugates (E1c), and pregnanediol glucuronide (Pdg). The serial analysis entailed an examination of the performance of proposed algorithms designed to identify features of the normal menstrual cycle in mid-reproductive life. Algorithms were based on existing methods and were compared with a "gold standard" of ratings of trained observers on a subset of 396 cycles from the first collection of samples from the study group.
Results
Only 17 of the 396 cycles evaluated were considered indeterminate. Of the 328 cycles rated as containing evidence of luteal activity (ELA), 320 were considered ELA by use of a Pdg threshold detection algorithm. Of 51 cycles that were rated as no evidence of luteal activity, only two were identified by this algorithm as ELA. Evaluation of the day of the luteal transition with methods that detected a change in the ratio of E1c to Pdg provided 85–92 percent agreement of the raters for day of the luteal transition within three days. Adding further conditions to the algorithm increased agreement only slightly, by one to eight percent.
Conclusions
The findings demonstrated the usefulness of objective, computer-based algorithms to describe the primary features of the menstrual cycle with reasonable accuracy. The approximately 90 percent agreement in comparing the data against benchmark standards justifies the ability of algorithms to assess probable ovulation by corpus luteum activity and cycle partition by day of luteal transition to help classify and elucidate the progress toward menopause among a population of reproductively aging women.
Performance of menstrual cycle algorithms was uniformly excellent in mid-reproductive age women. This was a small group obtained for comparison purposes and included women who had been prescreened for menstrual regularity and were therefore highly likely to have ovulatory cycles. Some differences in the hormone patterns of these women were noted when they were compared with the SWAN sample; however, the two groups cannot be considered strictly comparable.
Perimenopausal women experience irregular evidence of luteal activity, relative infertility, and greater variability in cycle characteristics. Cycle parameters and cycle length are more predictable in younger women. Younger women's cycles are far more likely to be fertile. The basis for these changes in cyclicity is a diminished follicular pool, with concomitant changes in the key cycle parameters that are dependable features of the cycles of younger women.
This study has produced an algorithm that could provide invaluable assistance to middle-aged women in determining their peak times of fertility. As women postpone marriage and families, these findings could lead to happiness and preserve heartbreak for an entire generation.
Source : March 2003 edition of the American Journal of Physiology--Endocrinology and Metabolism, one of 14 scientific journals published each month by the American Physiological Society (APS).
The American Physiological Society (APS) was founded in 1887 to foster basic and applied science, much of it relating to human health. The Bethesda, MD-based Society has more than 10,000 members and publishes 3,800 articles in its 14 peer-reviewed journals every year.