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

Elizabeth R. Bertone‐Johnson, Audrey J Gaskins, Kristine E Lynch, Sunni L Mumford, Anna Z Pollack, Enrique F Schisterman, Karen C Schliep, Jean Wactawski-Wende, Brian W Whitcomb, Shvetha M Zarek, Elizabeth R Bertone-Johnson, Michelle Danaher

  • University of Massachusetts Amherst ROR
  • Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia. Electronic address: Audrey.jane.gaskins@emory.edu. ROR
  • National Institutes of Health ROR
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development ROR
  • George Mason University ROR
  • University of Utah ROR
  • Department of Epidemiology and Environmental Health, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY. ROR
  • Division of Biostatistics and Epidemiology, University of Massachusetts School of Public Health and Health Sciences, Amherst, Massachusetts.

Fertility and sterility, 102(2), 511-518.e2

DOI 10.1016/j.fertnstert.2014.04.035 PMID 24875398

Abstract

Objective

To compare previously used algorithms to identify anovulatory menstrual cycles in women self-reporting regular menses.

Design

Prospective cohort study.

Setting

Western 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.

Topics

Menstrual CycleDiagnosticsFertility Awareness
anovulation detection eumenorrheic women, ovulation detection algorithm comparison, anovulatory menstrual cycle identification, regular menses anovulation prevalence, progesterone-based ovulation confirmation, luteal phase assessment ovulation, subclinical anovulation healthy women, menstrual cycle monitoring algorithms, prospective cohort anovulation study
PMID 24875398 24875398 DOI 10.1016/j.fertnstert.2014.04.035 10.1016/j.fertnstert.2014.04.035

Cite this article

Lynch, K. E., Mumford, S. L., Schliep, K. C., Whitcomb, B. W., Zarek, S. M., Pollack, A. Z., Bertone-Johnson, E. R., Danaher, M., Wactawski-Wende, J., Gaskins, A. J., & Schisterman, E. F. (2014). Assessment of anovulation in eumenorrheic women: comparison of ovulation detection algorithms. *Fertility and sterility*, *102*(2), 511-518.e2. https://doi.org/10.1016/j.fertnstert.2014.04.035

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