Validation of urinary reproductive hormone measurements using a novel smartphone connected reader

Abstract

Home use tests to monitor hormone trends during the menstrual cycle have been available over-the-counter for a long time. However, these tests often depend upon manual readouts and hence may lead to false analysis. Furthermore, a lot of these tests are also not quantitative. The aim of this study was to evaluate the accuracy of the quantitative home-based fertility monitor, Inito Fertility Monitor (IFM) and to use it to identify novel hormone trends in natural menstrual cycles. There were two aspects to our analysis: (i) Evaluating the efficacy of Inito Fertility Monitor in the measurement of urinary Estrone-3-glucuronide (E3G), Pregnanediol glucuronide (PdG) and Luteinizing hormone (LH), and (ii) A retrospective study of patients' hormone profiles using IFM. To evaluate the efficacy, the recovery percentage of the three hormones from IFM was evaluated using standard spiked solutions, the accuracy of measurement was calculated and the correlation between reproducible values from IFM and ELISA was established. During the validation of IFM, novel hormone trends were also observed. In order to reinforce the observations, a second group of 52 women was recruited. Assessment of the accuracy of IFM and evaluation of the volunteer urine samples was performed in a laboratory. Home assessment of hormone analysis was carried out using IFM. For the validation study, 100 women aged 21–45 years with cycle lengths ranging from 21 to 42 days were recruited. The participants had no previously diagnosed infertility conditions and their cycle lengths did not vary for more than 3 days from the expected cycle length. Daily first morning urine samples were collected from these 100 women. For the second group, 52 women were selected meeting the same criteria set for the validation study and IFM was provided to these women for testing at home. Coefficient of variation and recovery percentage of IFM with respect to laboratory based ELISA. Percentage occurrence of novel hormone trends and AUC analysis of a novel criteria identified for confirming ovulation. We observed that with all three hormones, IFM had an accurate recovery percentage. We found that the assay has an average CV of 5.05% in PdG measurement, 4.95% in E3G measurement and 5.57% in LH measurement. Furthermore, in predicting the concentration of E3G, PdG and LH in urine samples, we show that IFM has a high correlation with ELISA. In this study, we could also reproduce hormones trends across the menstrual cycle that have been observed by previous studies. We also identified a novel criterion for earlier confirmation of ovulation which could accurately distinguish ovulatory from anovulatory cycles with 100% specificity and had an area under the ROC curve of 0.98. In addition, we identified a new hormone trend which could be observed in 94.5% of the ovulatory cycles. The Inito Fertility Monitor is an effective tool for calculating the urinary concentrations of E3G, PdG and LH and can also be used to provide accurate fertility scores and confirm ovulation. We show that certain hormone trends associated with urinary E3G, PdG and LH could be accurately captured using IFM. In addition, we report a novel criterion for earlier confirmation of ovulation compared to existing criteria. Finally, we present a novel hormone pattern associated with most of the menstrual cycles by examining hormone profiles from the volunteers recruited for the clinical trial.Trial registration: The trial is registered at the current controlled trials ISRCTN registry #ISRCTN15534557.

Using Hormone Data and Age to Pinpoint Cycle Day within the Menstrual Cycle

“…Only cycles for which an LH peak was recorded were included in this study. This methodology relies on the widely accepted assumption that LH and PdG levels are at their baseline prior to an LH surge [ 28 , 29 , 30 ].…”