Monitoring of ovarian activity by measurement of urinary excretion rates of estrone glucuronide and pregnanediol glucuronide using the Ovarian Monitor, Part II: reliability of home testing

Blackwell, Leonard F.; Vigil, Pilar; Gross, Barbara A.; d’Arcangues, Catherine; Cooke, Delwyn G.; Brown, J. B.

doi:10.1093/humrep/der409

Cited by 30 publications

(27 citation statements)

References 14 publications

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“…With this method, participants tested their urine daily for 10 days around expected ovulation using Ovarian Monitor tests. Greater than 90% agreement was observed between lay users and lab tests in identification of ovulation within one day (Blackwell et al, 2012). This shows slightly improved reliability over the identification of ovulation via urine LH home tests (89% agreement within one day) (Martinez, Bernardus, Vermeiden, & Schoemaker, 1992).…”

Section: Discussionmentioning

confidence: 99%

Determining menstrual phase in human biobehavioral research: A review with recommendations.

Allen¹,

McRae‐Clark²,

Carlson³

et al. 2016

Experimental and Clinical Psychopharmacology

129

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Given the volume and importance of research focusing on menstrual phase, a review of the strategies being used to identify menstrual phase and recommendations that will promote methodological uniformity in the field is needed. We conducted a literature review via Ovid Medline and PsycINFO. Our goal was to review methods used to identify menstrual phase and subphases in biobehavioral research studies with women who had physiologically natural menstrual cycles. Therefore, we excluded articles that focused on any of the following: use of exogenous hormones, the postpartum period, menstrual-related problems (e.g. polycystic ovarian syndrome, endometriosis), and infertility/anovulation. We also excluded articles on either younger (<18 years old) or older (>45 years old) study samples. We initially identified a total of 1,809 articles. After our exclusionary criteria were applied, 146 articles remained, within which our review identified six different methods used to identify menstrual phase and subphases. The most common method used was self-report of onset of menses (145/146 articles) followed by urine luteinizing hormone testing (50/146 articles) and measurement of hormones (estradiol and/or progesterone) in blood samples (49/146 articles). Overall, we found a lack of consistency in the methodology used to determine menstrual phase and subphases. We provide several options to improve accuracy of phase identification, as well as to minimize costs and burden. Adoption of these recommendations will decrease misclassification within individual studies, facilitate cross-study comparisons and enhance the reproducibility of results.

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Section: Discussionmentioning

confidence: 99%

Determining menstrual phase in human biobehavioral research: A review with recommendations.

Allen¹,

McRae‐Clark²,

Carlson³

et al. 2016

Experimental and Clinical Psychopharmacology

129

View full text Add to dashboard Cite

show abstract

“…Using urinary samples, LH levels 2.1 to 61 times baseline levels were observed (38). New monitors that include urinary measurements of progesterone metabolites (24, 25) should help reduce the variability in assessment of ovulatory status; however, further research is needed to compare monitor performance to transvaginal ultrasound among larger cohorts of women (34). …”

Section: Discussionmentioning

confidence: 99%

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

Lynch

Mumford

Schliep

et al. 2014

Fertility and Sterility

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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 Study participants 259 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 eleven previously defined algorithms that utilize estradiol, progesterone, and luteinizing hormone (LH) concentrations. Result(s) Algorithms based on serum LH, estradiol, and progesterone levels detected a prevalence of anovulation across the study period of 5.5% to 12.8% (concordant classification for 91.7% to 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 estradiol metabolite, estrone-3-glucuronide (E3G), 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 to luteal phase progesterone serum-based algorithms. Our study demonstrates that algorithms based on the LH surge, or in conjunction with E3G, potentially estimate a higher percentage of anovulatory episodes. Addition of measurements of post-ovulatory serum progesterone or urine pregnanediol may aid in detecting ovulation.

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“…Irrespective of the sampling regime, the void volume and, often, the time between voids vary, so it is necessary to account for the resulting changes in quantitative assays of any urinary analyte (Brown et al, 2018). The natural approach wherever high quality data are required is simply to measure the urine production rate, as has routinely been done by users of the Ovarian Monitor (Brown et al, 1989;Blackwell et al, 2003;Blackwell et al, 2012;Blackwell et al, 2013;Blackwell et al, 2016). The analyte excretion rate is then calculated by multiplying the analyte concentration by the urine production rate .…”

Section: Introductionmentioning

confidence: 99%

On the distribution of urine output in normally cycling women

Cooke

Blackwell

Brown

2019

Biometrical Letters

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SummaryIt has been suggested that it is possible to monitor the menstrual cycle by measuring the concentration of urinary reproductive steroids. This neglects the variation in void volume and in urine production rate. In neither case has any systematic analysis been reported previously. Overnight urine samples were collected each day for one complete cycle by 24 women and the void volumes and intervoid times were recorded. The void volume and urine production rate were approximately lognormally distributed and the intervoid time was approximately normally distributed. Using these distributions we consider the implications of the variation in void volume and urine production rate for the comparison of the concentrations of a urinary analyte in two samples.

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Monitoring of ovarian activity by measurement of urinary excretion rates of estrone glucuronide and pregnanediol glucuronide using the Ovarian Monitor, Part II: reliability of home testing

Abstract: The study confirmed that the Ovarian Monitor pre-coated assay tubes worked well even in the hands of lay users, without standard curves, quality controls or replicates. Point-of-care monitoring to give reliable fertility data is feasible.

Cited by 30 publications

References 14 publications

Determining menstrual phase in human biobehavioral research: A review with recommendations.

Determining menstrual phase in human biobehavioral research: A review with recommendations.

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

On the distribution of urine output in normally cycling women

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