Background/Objectives: Quantitative urine monitors are increasingly being used for a personalized approach to improve menstrual cycle knowledge and to manage fertility. Although several studies have evaluated urine fertility monitors in regular cycles, there is limited research in the use of quantitative monitors in reproductive disorders, such as polycystic ovarian syndrome (PCOS). Methods: Urine hormone data was collected with the Mira monitor from 20 participants, 10 of whom had PCOS and a matched group who had regular cycles. The main aim of this study was to evaluate the levels of luteinizing hormone (LH), estrone-3-glucuronide (E₁3G), and pregnanediol glucuronide (PDG) in PCOS menstrual cycles compared to regular cycles. Results: Women with PCOS had higher BMI than regular cycling women (p=0.02). PCOS cycles were longer (p<0.05), peak day was later in the menstrual cycle (p<0.001), and luteal length was shorter (p < 0.01) compared to regular cycles. In whole cycle comparisons, E₁3G was found to be lower in PCOS cycles (p<0.01) and PDG was found to be higher in PCOS cycles (p<0.05). E₁3G was also lower in the follicular phase of and late luteal phase of PCOS cycles (p<0.00001). Conclusions: The results of this study demonstrate the feasibility of detecting hormonal differences in PCOS compared to regular cycles with at-home measurements with the Mira monitor. The metabolic dysregulation of PCOS is a possible factor in these hormone changes. Larger studies with different sub-types of PCOS will be needed to further clarify these changes and to understand the pathophysiology behind these hormonal changes.

Background: Quantitative at-home urinary hormone monitoring systems are increasingly used for reproductive health tracking, but their analytical behaviour requires systematic characterization. This preliminary laboratory comparison aimed to provide an analytical framework to compare multiple commercially available at-home urine hormone monitoring devices across key performance metrics under controlled artificial urine conditions. Methods: Laboratory experiments were informed by Clinical and Laboratory Standards Institute’s (CLSI) validation principles. Four urine hormone monitoring devices were evaluated using a pre-registered analytical framework for luteinizing hormone (LH), follicle-stimulating hormone (FSH), estrone-3-glucuronide (E3G), and pregnanediol glucuronide (PDG). Metrics included coefficients of variation (CV, for precision), relative deviation (RD, for accuracy), linearity, limit of blank (LoB), limit of detection (LoD) for each device, using artificial urine samples with standard hormone concentrations. Cross-reactivity was tested with other hormones including human chorionic gonadotropin (hCG), cortisol, thyroid stimulating hormone (TSH) and progesterone subtypes. Device-specific evaluations, including the impact of ambient light and various camera systems, were also conducted for relevant devices. Results: There were device- and analyte-specific differences in precision, accuracy, linearity and detection limits. Precision and accuracy ranged from CV/RD values near the 15% acceptability threshold to levels exceeding 50% at some concentrations. External lighting conditions affected camera-based strips at low hormone concentrations. False positive results for LH can occur in the presence of 100 mIU/mL hCG, which could lead to misinterpretation in the context of pregnancy. One device that measures the LH-beta subunit avoided this cross-reactivity. Conclusions: A preliminary analytical framework was applied to evaluate the performance of quantitative urinary hormone devices for at-home use. This framework can be used in future research and development of menstrual health monitoring technologies. Longitudinal clinical studies using human urine samples and appropriate ovulation reference standards are required before conclusions can be drawn regarding ovulation detection, fertile-window estimation or menstrual-phase classification.