Assessment of anovulation in eumenorrheic women: comparison of ovulation detection algorithms

ObjectiveTo compare previously used algorithms to identify anovulatory menstrual cycles in women self-reporting regular menses.DesignProspective cohort study.SettingWestern New York.Patient(s)Two hundred fifty-nine healthy, regularly menstruating women followed for one (n = 9) or two (n = 250) menstrual cycles (2005-2007).Intervention(s)None.Main Outcome Measure(s)Prevalence of sporadic anovulatory cycles identified using 11 previously defined algorithms that use E2, P, and LH concentrations.Result(s)Algorithms based on serum LH, E2, and P levels detected a prevalence of anovulation across the study period of 5.5%-12.8% (concordant classification for 91.7%-97.4% of cycles). The prevalence of anovulatory cycles varied from 3.4% to 18.6% using algorithms based on urinary LH alone or with the primary E2 metabolite, estrone-3-glucuronide, levels.Conclusion(s)The prevalence of anovulatory cycles among healthy women varied by algorithm. Mid-cycle LH surge urine-based algorithms used in over-the-counter fertility monitors tended to classify a higher proportion of anovulatory cycles compared with luteal-phase P serum-based algorithms. Our study demonstrates that algorithms based on the LH surge, or in conjunction with estrone-3-glucuronide, potentially estimate a higher percentage of anovulatory episodes. Addition of measurements of postovulatory serum P or urine pregnanediol may aid in detecting ovulation.