Predicting serum hormone concentration by estimation of urinary hormones through a home-use device

Abstract

STUDY QUESTION
Can a home-use device be used to predict serum hormone levels?

SUMMARY ANSWER
A home-use device can predict urinary hormone values which are well-correlated to serum concentrations of respective hormones and hence can be used as a proxy for serum measurements.

WHAT IS KNOWN ALREADY
Home-use devices that predict ovulation are calibrated against the actual day of ovulation. However, the correlation of any quantitative system to serum hormone concentrations has not been established.

STUDY DESIGN, SIZE, DURATION
A total of 73 data points obtained from 20 participants across different phases of the menstrual cycle, i.e. bleeding days, follicular phase and luteal phase were used to establish the correlation between serum hormones and urinary metabolite values. Single data points from 20 random users were used to assess the correlation established.

PARTICIPANTS/MATERIALS, SETTING, METHODS
Participants were women in the fertile age groups and only current users of the home-use device. Selection was done based on inclusion and exclusion criteria. Blood hormones were tested using chemiluminescent immunoassays and urinary measurements were taken on the home-use device at home.

MAIN RESULTS AND THE ROLE OF CHANCE
Serum estradiol (E2), progesterone (P4) and LH were correlated with urinary estrone-3-glucuronide (E3G), pregnanediol glucuronide (PdG) and LH with an R2 of 0.96, 0.95 and 0.98, respectively. Repredicted serum concentration obtained by using the correlation equation had a correlation of 0.92, 0.94 and 0.93 in unknown samples.

LIMITATIONS, REASONS FOR CAUTION
The study was designed to include women who have normal cycle lengths regularly; therefore, the values obtained were in the normal range. Certain infertility conditions may cause the values to be higher and correlation in such cases needs to be established.

WIDER IMPLICATIONS OF THE FINDINGS
The results of this study imply a new tool that can be used by fertility specialists as a proxy for blood tests whenever required. Extended study on this system can enable its use in assisted reproductive techniques as well.

STUDY FUNDING/COMPETING INTEREST(S)
No funding was received for this study. S.P. and D.D. are employees of the research and development division of Samplytics Technologies Pvt. Ltd. which is a forwarder for Inito Inc., USA. A.R. and V.A.V. are co-founders of Inito Inc., USA.

TRIAL REGISTRATION NUMBER
The trial was registered at the International Standard Randomised Controlled Trial Number (ISRCTN) registry (Identifier: ISRCTN15534557).

Full text

Predicting serum hormone
concentration by estimation of urinary
hormones through a home-use device
Siddharth Pattnaik
1,
*, Dipankar Das
1
, Varun Akur Venkatesan
2
,
and Aayush Rai
2
1
Samplytics Technologies Pvt. Ltd., Bangalore, Karnataka, India
2
Inito Inc, San Francisco, CA, USA
*Correspondence address. Samplytics Technologies Pvt. Ltd., #44, SKS Plaza, 100 Feet Road, 4th Block Koramangala, Bangalore, Karnataka
560034, India. Tel: þ91-8766563170; E-mail: siddharth@inito.com https://orcid.org/0000-0003-4136-5180
Submitted on November 19, 2021; resubmitted on December 1, 2022; editorial decision on December 19, 2022
STUDY QUESTION: Can a home-use device be used to predict serum hormone levels?
SUMMARY ANSWER: A home-use device can predict urinary hormone values which are well-correlated to serum concentrations of
respective hormones and hence can be used as a proxy for serum measurements.
WHAT IS KNOWN ALREADY: Home-use devices that predict ovulation are calibrated against the actual day of ovulation. However,
the correlation of any quantitative system to serum hormone concentrations has not been established.
STUDY DESIGN, SIZE, DURATION: A total of 73 data points obtained from 20 participants across different phases of the menstrual
cycle, i.e. bleeding days, follicular phase and luteal phase were used to establish the correlation between serum hormones and urinary
metabolite values. Single data points from 20 random users were used to assess the correlation established.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants were women in the fertile age groups and only current users of
the home-use device. Selection was done based on inclusion and exclusion criteria. Blood hormones were tested using chemiluminescent
immunoassays and urinary measurements were taken on the home-use device at home.
MAIN RESULTS AND THE ROLE OF CHANCE: Serum estradiol (E2), progesterone (P4) and LH were correlated with urinary
estrone-3-glucuronide (E3G), pregnanediol glucuronide (PdG) and LH with an R
2
of 0.96, 0.95 and 0.98, respectively. Repredicted serum
concentration obtained by using the correlation equation had a correlation of 0.92, 0.94 and 0.93 in unknown samples.
LIMITATIONS, REASONS FOR CAUTION: The study was designed to include women who have normal cycle lengths regularly;
therefore, the values obtained were in the normal range. Certain infertility conditions may cause the values to be higher and correlation in
such cases needs to be established.
WIDER IMPLICATIONS OF THE FINDINGS: The results of this study imply a new tool that can be used by fertility specialists as a
proxy for blood tests whenever required. Extended study on this system can enable its use in assisted reproductive techniques as well.
STUDY FUNDING/COMPETING INTEREST(S): No funding was received for this study. S.P. and D.D. are employees of
the research and development division of Samplytics Technologies Pvt. Ltd. which is a forwarder for Inito Inc., USA. A.R. and V.A.V. are
co-founders of Inito Inc., USA.
TRIAL REGISTRATION NUMBER: The trial was registered at the International Standard Randomised Controlled Trial Number
(ISRCTN) registry (Identifier: ISRCTN15534557).
Key words: Inito Fertility Monitor / quantitative home-use system / serum hormones / urinary hormones / LH / E3G / PdG
V
CThe Author(s) 2022. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which per-
mits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
Human Reproduction Open, Vol.2023, No.1, hoac058, 2023
https://doi.org/10.1093/hropen/hoac058
ORIGINAL ARTICLE
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Introduction
Home-use fertility monitoring devices have been widely used to in-
crease the probability of conception (Su et al.,2017). These devices
implement principles aimed at measuring physiological changes associ-
ated with ovulation such as measuring basal body temperature
(Marshall, 1968) and physical examination of vaginal discharge (Guida
et al.,1999;Ecochard et al.,2001;Alliende et al., 2005). One such
method is the measurement of urinary hormones using lateral flow
assays. Measurement of urinary hormones is well-correlated with the
ultrasound day of ovulation (US-DO).
Initially, urinary LH tests to predict ovulation were routinely used at
home. While these tests were good enough to implicate the time of
ovulation in a 12 h interval, a major disadvantage was the ambiguity of
timing the tests. Roos et al. (2015) inferred that measuring urinary
estrone-3-glucuronide (E3G) in addition to urinary LH improved the
probability of conception. Recently, a few home tests have been devel-
oped to measure urinary pregnanediol glucuronide (PdG) to confirm
ovulation (Bouchard et al.,2019). The accuracy of these tests concern-
ing the actual day of ovulation has been established. These home-use
tests mostly implement lateral flow assays to estimate the levels of
hormones. This is an indirect prediction method since the concentra-
tion is predicted based on test and control line intensities in an abso-
lute way or a ratio of them. Therefore, the question remains whether
a correlation with serum hormones does apply. In addition, establish-
ing such a correlation will enable clinicians to monitor serum hor-
mones in patients using these devices.
The Inito Fertility Monitor (IFM) is a quantitative home-use system
for measuring E3G, PdG and LH by quantifying lateral flow assays. A
combination of these hormones enables women to predict their fertile
window in the menstrual cycle as well as confirm ovulation, making
this a tool that women could use during the entire menstrual cycle.
The IFM uses a mobile camera to quantify the intensities of test and
control lines on a lateral flow assay and derive the concentration from
the ratio of the test and control lines’ intensities. A previous study has
substantiated the accuracy and reproducibility of the IFM concerning
test strips as well as camera variation (Thakur et al.,2020). Here, we
show that values of urinary metabolites predicted by the IFM are well-
correlated with serum hormone concentrations. We also show that
the correlation equation can be used to predict serum concentrations
of hormones in unknown samples accurately.
Materials and methods
Study participants
The study design was approved by the Institutional Review Board
(IRB) of Sparsh Hospital (EC approval number: CLIN/INI/001). All
women selected for the experimental cohort were new users of the
IFM who were testing for the first cycle at home (retrospectively se-
lected). Women were included in the study if their age was between
21 and 45 years and with an average cycle length between 23 and
45 days. Women were excluded if:
a. They were on infertility medications or hormone replacement therapy
containing hCG or LH.
b. They were using hormonal contraceptives, including oral, emergency
oral, implants, patches, transdermal injections, vaginal ring and proges-
terone intrauterine systems.
c. They were taking clomiphene citrate or other ovulation induction
drugs.
d. They had recently been pregnant, miscarried or breastfeeding.
e. They had irregular cycle lengths.
f. They had missed more than two out of four assigned tests.
The inclusion and exclusion criteria applied to recruit women for
the experimental cohort and verification cohort were the same.
However, the recruitment of the verification cohort was done after
the analysis with the experimental cohort was completed.
Study design
The IFM, Inito fertility test strips and a customized clip to attach the
fertility monitor to mobile phones were shipped to all participants for
testing at home. Testing days were assigned to recruited participants
such that the days were from different phases of the menstrual cycle:
(1) Early follicular phase: cycle day 5–7.
(2) Late follicular phase: cycle days 9–15.
(3) Luteal phase: cycle day 17 or above.
A total of 18 data points were collected in the early follicular phase,
36 data points in the late follicular phase and 19 data points were col-
lected in the luteal phase.
WHAT DOES THIS MEAN FOR PATIENTS?
Many home-use fertility monitors work on the principle of measuring urinary hormones. Semi-quantitative (conveying ranges) and qualita-
tive (yes or no) home-use fertility monitors have been on the market for a long time. However, the lack of a laboratory-grade quantitative
system prevents visualization of hormone concentration trends throughout the menstrual cycle and possible interpretation by doctors to
suggest any intervention. In this study, we compared the accuracy of urinary metabolite measurements using an Inito Fertility Monitor (IFM)
at home with respect to serum hormone concentrations measured in the laboratory. We found the measurements obtained from the IFM
to be well-correlated to serum hormone measurements obtained from the laboratory. Additionally, we showed that the clinical relevance
of reporting ovulation based on progesterone values is accurately captured using pregnanediol glucuronide measurement using the IFM.
Therefore, we propose that the IFM can not only be used by women to accurately monitor their hormone trends but can also be used by
doctors to remotely monitor the effect of their interventions on hormones and hence tailor the remedy accordingly.
2Pattnaik et al.
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On assigned days for testing, 2 ml of venous blood samples were
collected in EDTA-coated BD vacutainer
V
R
(Becton Dickinson and
Co., Mississauga, ON, Canada) by a phlebotomist at home and
samples were transported in the collection tubes to the laboratory
for testing. Serum estradiol (E2), progesterone (P4) and LH were
measured. All participants tested with the first urine of the day
(morning) on the IFM at home. The urine testing was performed
by the women only after the venous blood samples were collected
by the phlebotomist. Test timings were recorded on the back.
Subjects were asked to maintain a fasting period of 10–12 h before
sample collection in order to prevent the effect of any food
consumed on the hormone readings. Serum E2 and P4 were mea-
sured using a chemiluminescent microparticle immunoassay, and
serum LH was measured using a chemiluminescent immunoassay
on an Abbott ARCHITECT i2000SR immunoanalyzer (Abbott
Laboratories, Chicago, IL, USA).
Results
A total of 73 data points were obtained from 20 participants for estab-
lishing the correlation between serum hormones and respective uri-
nary metabolites. We found that serum concentrations of E2, P4 and
LH were well-correlated with IFM-predicted concentrations of urinary
E3G, PdG and LH, respectively (Fig. 1a–c). While E3G and PdG corre-
lated linearly with serum E2 and P4, urinary LH and serum LH were
correlated by quadratic regression. We wanted to further delve into
the reason for this non-linear correlation between urinary LH and se-
rum LH. Therefore, we decided to look at the correlation in different
ranges of LH. We found that at serum LH <8 mIU/ml, the linear cor-
relation coefficient was 0.372 with a slope of 0.0841 indicating that the
urine values did not change significantly in this range of serum LH
(Supplementary Fig. S1a). However, at serum LH >8 mIU/ml, the lin-
ear correlation coefficient was 0.957 with a slope of 0.305 which
would indicate that, in this range, the values are well-correlated
(Supplementary Fig. S1b).
Interestingly, we found that the first-morning urinary metabolite con-
centrations had a better correlation with their respective serum hor-
mones compared to the creatinine normalized values (Fig. 1d–f),
which may indicate that a creatinine-correction may not be required
for predicting serum hormone levels from urine metabolite
concentrations.
Furthermore, using the correlation equation, we wondered if we
could predict the serum hormone concentrations from urinary me-
tabolite measurements. We recruited 20 new users of the IFM and
collected their blood samples following the same protocol as the
primary cohort. This served as the verification cohort. The samples
were collected on random cycle days without any specific
Figure 1. Correlation between urinary measurements by the Inito Fertility Monitor (Inito) and serum hormone con-
centrations (experimental cohort). (a) Linear correlation between urinary estrone-3-glucuronide (E3G) and serum estradiol (E2). (b) Linear
correlation between urinary pregnanediol glucuronide (PdG) and serum progesterone (P4). (c) Quadratic correlation between urinary LH and serum
LH. (d–f) Correlation between creatinine-corrected urinary E3G, PdG and LH as measured by IFM, and serum E2 (d), P4 (e) and LH (f).
Serum hormone concentration from urinary hormones 3
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preference toward a particular phase of the menstrual cycle.
Applying the equation to this new dataset, we found that the pre-
dicted serum concentrations were highly correlated to the actual
serum concentrations (Fig. 2a–c).
In addition, to show that the clinical significance of results based on
these hormones is maintained across both the methods, we used
the prediction of the ovulatory status of the menstrual cycle as the
parameter. Typically, a mid-luteal phase serum progesterone value of
>3 ng/ml was used to confirm ovulation. Recently, it has been shown
that mid-luteal phase measurement of urinary PdG (a threshold value
of >5mg/ml) has a good correlation with serum P4 behavior and can
also be used to confirm ovulation (Ecochard et al.,2013;Leiva et al.,
2019). Therefore, we compared the data points where serum value
was >3 ng/ml to see its correlation with the occurrence of urinary
PdG >5mg/ml measured by the IFM. We found that in all 11 data
points where serum values confirmed ovulation, urinary PdG values
also confirmed ovulation indicating that the clinical relevance of meas-
urements persist in the IFM (Table I).
Discussion
The accuracy and scope of point-of-care (POC) devices have long
been questioned in the fertility space due to the unsatisfactory correla-
tion between the results provided by POC devices and laboratory val-
ues. For monitoring the effects of interventions on hormones, blood
tests are prescribed, which require an invasive procedure to be per-
formed along with a delay in results. Moreover, since cycle lengths and
hormonal patterns may vary from one individual to another (Grieger
and Norman, 2020), the number of such tests cannot be accurately
predicted, therefore demanding the need for a POC device that could
aid testing at home with good correlation to laboratory values. While
most POC devices measure urinary metabolites of fertility hormones
to provide a putative fertile window, the underlying assumption is that
the laboratory correlation will hold good in an indirect measurement
as well. However, this has not been proven so far.
We show that the IFM could reproduce laboratory-level correla-
tions with serum hormones and that the correlation equation could in
Figure 2. Correlation between serum concentration predicted by Inito and actual serum concentration. Linear correla-
tions in the verification cohort between the actual serum concentrations of (a) estradiol (E2), (b) progesterone (P4) and (c) LH and the predicted se-
rum concentrations derived from the equations generated from the experimental cohort based on urinary hormone concentrations obtained from
the Inito Fertility Monitor.
4Pattnaik et al.
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turn be used to predict serum concentrations with a high correlation
coefficient. We predict that such a device could help in predicting the
day of ovulation with higher accuracy compared to semi-quantitative
or qualitative devices. As a result, this may lead to higher chances of
conceiving successfully (Wilcox et al.,1995). Since it has also been sug-
gested that fertilization by older sperm leads to loss of pregnancy, we
speculate that predicting the LH surge closer to ovulation may lead to
more successful pregnancies (Simpson et al.,1988).
Although estrogen assays are known to be inaccurate at lower lev-
els, these levels may not be of significance in the case of female fertility
(Rosner et al., 2013). In addition, all data points for E2 were above
this threshold and hence these challenges in measuring E2 at lower lev-
els may not be a reason for concern for this study.
While identifying the correlation between serum hormones and uri-
nary metabolites, we found that urinary LH correlated in a quadratic
manner with serum LH. There could be two hypotheses which may
explain such a non-linear correlation. The curve obtained resembles
an ELISA-like antigen-antibody kinetic behavior, which follows a sig-
moid curve (Engvall and Perlman, 1971). Such a correlation may imply
that the non-linearity could be stemming from the type of anti-LH anti-
bodies used in the assay which may be changing less at lower concen-
trations and more linearly at higher concentrations of LH. The second
hypothesis is based on the kinetics of plasma clearance of LH. A previ-
ous study that deciphered the clearance of LH in female rats estab-
lished a similar clearance curve for LH (Ascoli et al.,1975). It is
possible that something similar may be occurring in women where the
LH in urine may only be appearing above a certain serum threshold.
We also observed that the creatinine correction showed a reduced
correlation coefficient with serum hormone concentration. An impor-
tant reason for this observation could be the variation in age of the
women recruited in the study. Previous studies have observed a similar
effect of creatinine correction in case of urinary pregnanediol glucuro-
nide (Zacur et al.,1997;Miro et al., 2004) due to a decrease in excre-
tion of creatinine with aging. However, there may be other factors to
consider, such as the fact that women maintained a fasting period that
may not always be true in a real-life scenario. Hydration levels may af-
fect the concentration of urinary hormones and a creatinine correction
may provide better correlation in such cases. Future studies with the
IFM will focus on studying such variations in much more detail.
While we established a good correlation between the methods,
there are certain limitations of the current study. Firstly, the study was
only performed on normally menstruating women. Therefore, the va-
lidity of this correlation in the presence of one or more infertility con-
ditions needs to be studied and would be an interesting subject for
future studies with the IFM. Secondly, the study was performed on a
smaller group of women and the correlation equation was tested on
an even smaller group of women to infer that the equation still ap-
plied. While the correlation coefficient may apply in different infertility
conditions and different racial settings, the correlation equation be-
tween IFM urinary measurements and serum measurements may vary
owing to genetic factors, medication status, health, metabolic rates
(Spaeth et al.,2015) and other reasons that may affect conversion of
estrogen and progesterone to E3G and PdG respectively. For instance,
women on progesterone supplements may record consistently high
PdG values and the correlation with serum progesterone could be lim-
ited by the limits of the assay itself.
Future studies will be aimed at establishing the correlation of these
hormones in infertility-related conditions, patients under ovulation in-
duction, and patients undergoing procedures such as IVF where the
hormone levels tend to be higher than the normal range; hence, it will
be important to establish if the correlation applies even at elevated
levels.
Supplementary data
Supplementary data are available at Human Reproduction Open online.
Data availability
The data underlying this article will be shared on reasonable request
to the corresponding author.
Authors’ roles
S.P., D.D. and V.A.V. contributed to the concept and design of the
study. S.P. and D.D. contributed to the acquisition of data. S.P., V.A.V.
and A.R. contributed to the analysis and interpretation of data. S.P.
drafted the article and all authors contributed to the revision of the ar-
ticle. All authors approved the final version of the article to be
published.
Funding
No funding was received for this study.
Conflict of interest
S.P. heads the research and development division of Samplytics
Technologies Pvt. Ltd. which is a forwarder for Inito Inc., USA. D.D. is
employed as the clinical research scientist at Samplytics Technologies
Pvt. Ltd. A.R. and V.A.V. are the co-founders of Inito Inc., USA.
.................................................... ...................................................
Table I Comparison of serum P4
*
values and urinary
PdG
**
values for data points based on which a cycle was
classified as ovulatory.
P4 Serum (ng/ml) PdG Inito
***
(lg/ml)
6.91 8.37
8.23 13.42
3.81 9.82
8.99 13.72
8.23 11.60
7.69 11.54
3.62 6.25
5.64 10.65
7.23 9.37
3.87 5.78
3.13 6.38
*Progesterone.
**Pregnanediol glucuronide.
***
Measurements from the Inito Fertility Monitor.
Serum hormone concentration from urinary hormones 5
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