Assessing menstrual cycles with urinary hormone assays

Abstract

The Study of Women's Health Across the Nation (SWAN) is a multiethnic cohort study of middle-aged women enrolled at seven US sites. A subset of 848 women completed a substudy 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). To prepare for serial analysis of this large, longitudinal database in a population of reproductively aging women, we examined the performance of algorithms designed to identify features of the normal menstrual cycle in midreproductive 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 Daily Hormone Substudy samples. In evaluating luteal status, overall agreement between and within raters was high. 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 2 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% agreement for day of the luteal transition within 3 days of the raters. Adding further conditions to the algorithm increased agreement only slightly, by 1-8%. We conclude that reliable, robust, and relatively simple objective methods of evaluation of the probability and timing of ovulation can be used with urinary hormonal assays in early perimenopausal women.