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Development of the first urinary reproductive hormone ranges referenced to independently determined ovulation day

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Urinary hormone level analysis provides valuable fertility status information; however, previous studies have not referenced levels to the ovulation day, or have used outdated methods. This study aimed to produce reproductive hormone ranges referenced to ovulation day determined by ultrasound. Women aged 18–40 years (no reported infertility) collected daily urine samples for one complete menstrual cycle. Urinary luteinising hormone (LH), estrone-3-glucuronide (E3G, an estradiol metabolite), follicle stimulating hormone (FSH) and pregnanediol-3-glucuronide (P3G, a progesterone metabolite) were measured using previously validated assays. Volunteers underwent trans-vaginal ultrasound every 2 days until the dominant ovarian follicle size reached 16 mm, when daily scans were performed until ovulation was observed. Data were analysed to create hormone ranges referenced to the day of objective ovulation as determined by ultrasound. In 40 volunteers, mean age 28.9 years, urinary LH surge always preceded ovulation with a mean of 0.81 days; thus LH is an excellent assay-independent predictor of ovulation. The timing of peak LH was assay-dependent and could be post-ovulatory; therefore should no longer be used to predict/determine ovulation. Urinary P3G rose from baseline after ovulation in all volunteers, peaking a median of 7.5 days following ovulation. Median urinary peak E3G and FSH levels occurred 0.5 days prior to ovulation. A persistent rise in urinary E3G was observed from approximately 3 days pre- until 5 days post-ovulation. This study provides reproductive hormone ranges referenced to the actual day of ovulation as determined by ultrasound, to facilitate examination of menstrual cycle endocrinology.
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Clin Chem Lab Med 2015; aop
*Corresponding author: Sarah Johnson, Head of Regulatory and
Clinical Affairs, SPD Development Co., Ltd, Priory Business Park,
Bedford, MK44 3UP, UK, Phone: + 44 1234 835 486,
Fax: + 44 1234 835 006, E-mail: sarah.johnson@spdspark.com
Sarah Weddell and Sonya Godbert: SPD Development Company Ltd,
Bedford, UK
Guenter Freundl, Judith Roos and Christian Gnoth: green-ivf,
Grevenbroich Endocrinology- and IVF-Center and Department of
Gynecology and Obstetrics, University of Cologne, Grevenbroich,
Germany
Sarah Johnson * , Sarah Weddell , Sonya Godbert , Guenter Freundl , Judith Roos and
Christian Gnoth
Development of the first urinary reproductive
hormone ranges referenced to independently
determined ovulation day
DOI 10.1515/cclm-2014-1087
Received November 5 , 2014 ; accepted December 11 , 2014
Abstract
Background: Urinary hormone level analysis provides
valuable fertility status information; however, previous
studies have not referenced levels to the ovulation day, or
have used outdated methods. This study aimed to produce
reproductive hormone ranges referenced to ovulation day
determined by ultrasound.
Methods: Women aged 18 40years (no reported infertil-
ity) collected daily urine samples for one complete men-
strual cycle. Urinary luteinising hormone (LH), estrone-
3-glucuronide (E3G, an estradiol metabolite), follicle
stimulating hormone (FSH) and pregnanediol-3-glucu-
ronide (P3G, a progesterone metabolite) were measured
using previously validated assays. Volunteers underwent
trans-vaginal ultrasound every 2days until the dominant
ovarian follicle size reached 16 mm, when daily scans
were performed until ovulation was observed. Data were
analysed to create hormone ranges referenced to the day
of objective ovulation as determined by ultrasound.
Results: In 40 volunteers, mean age 28.9 years, urinary
LH surge always preceded ovulation with a mean of 0.81
days; thus LH is an excellent assay-independent predictor
of ovulation. The timing of peak LH was assay-dependent
and could be post-ovulatory; therefore should no longer
be used to predict/determine ovulation. Urinary P3G rose
from baseline after ovulation in all volunteers, peaking a
median of 7.5 days following ovulation. Median urinary
peak E3G and FSH levels occurred 0.5days prior to ovula-
tion. A persistent rise in urinary E3G was observed from
approximately 3days pre- until 5days post-ovulation.
Conclusions: This study provides reproductive hormone
ranges referenced to the actual day of ovulation as deter-
mined by ultrasound, to facilitate examination of men-
strual cycle endocrinology.
Keywords: estrone-3-glucuronide; follicle stimulating
hormone; hormone ranges; luteinising hormone; men-
strual cycle; ovulation; pregnanediol-3-glucuronide.
Introduction
The path to pregnancy has changed in recent decades, with
women delaying pregnancy until their 30s or even later [1,
2] when female fertility is known to decrease significantly
[3] , and often after many years of oral contraceptive use.
Despite this, when the decision is taken to start a family,
expectations are that it will happen quickly and many
women wish to control the process. However, many women
are unfamiliar with their ovulatory cycle, e.g., approxi-
mately 40% of women in a recent US study were unaware
that ovulation usually occurs 14days prior to menses or
that clear mucous vaginal discharge is a sign of impending
ovulation [4] . This lack of knowledge of personal ovulatory
cycles is especially pertinent for women following discon-
tinuation of oral contraceptives, which will have masked
their natural cycles, sometimes for many years [5] . In addi-
tion, a third of US women, participating in this recent study,
were unaware of the adverse effects of reproductive aging,
sexually transmitted infections, obesity or irregular menses
on fertility [4] . Furthermore, in a UK study of women trying
to conceive, only 12.7% of women correctly estimated their
day of ovulation, and only 55% estimated an ovulation day
that fell within their fertile window [6] .
There is considerable inter-cycle variability in the
timing of ovulation observed both between women and
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2Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day
between cycles in individual women. The mean individual
range of cycle variability has been reported as 6.7days
[7] , while another study found that 46% of women had
cycles that varied by 7days or more [8] . Therefore, data
of previous cycle lengths alone is not at all sufficient to
determine a woman s fertile period within any given cycle.
This is further illustrated by the fact that anovular cycles
in apparently normal women are reported to occur in
between 2% and 9% of cycles in different studies [9 11] .
Trans-vaginal ultrasound is an effective and standard
method for the detection of the day of ovulation, as long
as examinations are frequent enough (daily/every 2 days)
[12] . Unfortunately, it is costly and partly invasive, and
thus impractical for routine use by women trying to con-
ceive. Serum levels of reproductive hormones can provide
valuable information to women about their cycle and
timing of fertility. Reference hormone ranges in women
with natural menstrual cycles and no reported infertil-
ity provide a valuable tool for understanding the normal
range of hormones in relation to day of cycle. Unfor-
tunately, serum measurements need to be carried out
sequentially to gain an understanding of the whole cycle,
thus this is not usually warranted unless there is reason
for concern. However, these reproductive hormones, or
their metabolites, are also detectable in urine, provid-
ing a convenient and non-invasive method for repeated
investigation.
Some previous studies have compared urinary
hormone profiles relative to each other, but not relative
to the objective day of ovulation [13, 14] . For example, a
recent study by Blackwell etal. looked at urinary hormone
profiles of estrone glucuronide (EG), pregnanediol glu-
curonide (PdG) and luteinising hormone (LH), using a
mixture of laboratory and home-based monitoring, and
concluded that urinary hormone monitoring was a useful
tool for cycle examination [14] . Other studies analysing
serum hormone profiles have used the day of the LH peak
to establish reference ranges [15] , but this introduces rel-
evant imprecision into the profiles, as it makes assump-
tions in timing of peak LH levels relative to ovulation. This
timing can be influenced by intra-individual variation in
time from peak LH to ovulation (approx. 28 48 h) [16] ,
occurrence of peak LH levels post-ovulation and variabil-
ity in the sensitivity of the LH assays to the metabolites of
LH (thus the reported timing of the LH peak can be assay-
dependent). Aligning data to the first day of the cycle is
not appropriate due to the inter-individual variability of
the length of the follicular phase.
Direito etal. analysed hormone levels relative to ultra-
sound-identified ovulation day, using urinary samples,
and corresponding hormone assays conducted in the
1990s [17] . In addition, a study by Ecochard etal. described
the average range of follicle stimulating hormone (FSH)
relative to ultrasound-observed ovulation, also using
urinary analysis performed 15 20 years ago [18] . Studies
conducted on urine samples from the 1990s, although of
great interest, may not be truly representative of women
approximately 20years later, since factors known to affect
fertility, such as alcohol consumption, smoking habits
and body mass index (BMI), have increased in the last
two decades (e.g., BMI has increased by 0.5 kg/m
2 per
decade worldwide [19] ) and menstrual cycle disturbances
like polycystic ovary syndrome (PCOS) are also more
common [20] .
It is very desirable for women to have accurate infor-
mation of their individual cycle and timing of ovulation
in order to successfully plan or avoid a pregnancy, or to
enable them to rapidly identify any possible abnormali-
ties that may affect their fertility. Urinary hormone levels
can provide this detail, but a revisitation of ranges is
critical to reflect the endocrinology of women today. This
study therefore sought to create new urinary reproductive
hormone ranges in relation to the ultrasound-determined
day of objective ovulation.
Materials and methods
Women aged 18 40years with no reported infertility and a minimum
of two natural cycles prior to the study start were recruited via local
and in-clinic advertising in Grevenbroich , Germany. The study was
approved by the Ethics Committee of the Chamber of Physicians,
Duesseldorf, Germany (study NCT01802060), it was conducted from
February to June 2013 and called the Me nstrual Cycle Mo nitoring
Study (MeMo Study).
Study method
Women enrolled on the study were required to collect daily  rst morn-
ing void urine samples from the  rst day of their period (Day 1 of their
menstrual cycle), until the  rst day of their next period, and recorded
menses in a daily diary. During their cycle, women attended the study
site (green-ivf, Center of Gynecological Endocrinology and Reproduc-
tive Medicine, Grevenbroich, Germany) to obtain serum samples and
for trans-vaginal ultrasound to determine the day of ovulation. Trans-
vaginal ultrasound was conducted every 2days until the dominant
follicle diameter reached 16mm (folicules reach 17 27mm in size just
prior to ovulation), at which time the women were required to attend
for daily ultrasound scans, with subsequent scans carried out on
Days 7 and 9 following ovulation. Where ovulation occurred between
visits, the day of ovulation was considered as 0.5days following the
last visit where a dominant follicle was observed. Ultrasound was
conducted by two clinicians (JR and CG) and all images stored for
central review. Daily urine samples were collected into sample pots
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Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day3
containing the bacteriostatic sodium azide. Volunteers were required
to refrigerate samples on collection and return them to the study site
at each visit (every 1 2 days), where samples were frozen at 80 ° C
prior to analysis.
Urinary hormone measurement
Hormone analyses were conducted as batch analyses, ensuring
complete cycles were analysed on single assay plates. Samples were
brought to room temperature and mixed prior to analysis; it had pre-
viously been determined that up to  ve freeze-thaw cycles had no
a ect on analyte concentration.
Urinary LH, estrone-3-glucuronide (E3G, a metabolite of estra-
diol), FSH and pregnanediol-3-glucuronide (P3G) were measured
using in-house assays on the AutoDELFIA platform (Perkin Elmer,
Waltham, MA, USA). Levels of LH were also evaluated using the Per-
kin Elmer assay. All assays utilised monoclonal antibodies.
The Perkin Elmer LH assay employs a β subunit – β subu-
nit sandwich assay and it is able to detect intact LH, free β LH
(LH- β ) and LH β core fragment (LH- β cf). This assay was validated
for use in urine samples and demonstrated the following perfor-
mance characteristics: sensitivity limit of 0.5 mIU/mL (two standard
deviations above mean of zero measurement); intra- and inter-assay
percentage con dence values (CV) were below 3% at all standards
tested (28, 51 and 111 mIU/mL); linearity was seen on dilution of
sample to a 1 in 20 dilution; no hook e ect, a false negative test
result with certain immunoassays due to very high concentrations
of the analyte, was observed when testing at maximal concentra-
tion of 1000mIU/mL.
The in-house LH assay consists of immobilised biotinylated
antibody (antibody # 2119; SPD Development Co., Ltd, Bedford, UK)
that recognises the α LH subunit bound to streptavidin plates, and
a second, europium-labelled antibody that recognises the β subunit
(antibody # 2301; SPD Development Co., Ltd, Bedford, UK), thus it is
only able to measure intact LH. Assay sensitivity was 0.1 mIU/mL and
inter- and intra-assay percentage CV were < 5%; linearity was seen
in dilutions up to 1 in 20 and no high-dose hook was observed when
testing up to 1000 mIU/mL.
FSH was measured with an in-house sandwich assay consist-
ing of europium-labelled anti- β subunit antibody (antibody # 5948;
SPD Development Co., Ltd, Bedford, UK) and biotinylated anti- α FSH
(antibody # 4882; SPD Development Co., Ltd, Bedford, UK) immobi-
lised on streptavidin plates. The sensitivity of this assay was 0.136
mIU/mL; inter- and intra-assay percentage CV was < 5% for stand-
ards tested (1.77, 8.2, 42.9, 219 mIU/mL); linearity was seen up to a 1
in 20 dilution and no high dose hook was observed when testing up
to 1000 mIU/mL.
A competitive in-house immunoassay was used for measuring
E3G, consisting of immobilised high a nity antibody for E3G (antibody
# 4155; SPD Development Co., Ltd, Bedford, UK), with competition for
binding between sample and europium-labelled E3G. Validation of
this assay for use in urine demonstrated the following performance:
sensitivity was 0.5 ng/mL; intra- and inter-assay percentage CV was
below 5% for all standards tested (3, 20, 37, 170 ng/mL); linearity was
seen up to a 1 in 20 dilution of urine sample.
The P3G assay used was also an in-house competitive immunoas-
say based on competition between sample and europium-labelled P3G
for binding by a high a nity antibody (antibody # 5806; SPD Develop-
ment Co., Ltd, Bedford, UK). Assay sensitivity was 0.021 μ g/mL and
intra- and inter-assay percentage CV was below 10% for standards
tested (0.16, 0.8, 4.0, 20.0, 100.0 μ g/mL); linearity was seen up to a 1 in
20 dilution of urine sample.
Data analysis
All results were entered into the study database using the Teleform
system (Autonomy Inc, San Francico, CA, USA). Data were analysed
using SAS version 9.2 to create hormone ranges referenced to the day
of ovulation as determined by ultrasound. The median, 10th and
90th centiles of each hormone were determined using the day refer-
enced to the day of ovulation. Day of urinary LH surge was de ned as
rst rise from baseline by the interpretation of graphical data by the
panel of authors.
Results
Volunteer characteristics
A total of 51 volunteers were recruited into the study on
a first-come, first-in basis; 10 women withdrew or were
withdrawn from the study, including two women who
were found to have ovarian cysts at the time of their
first scan (of which they were previously unaware). One
woman was found to have had an anovular cycle. Thus
data were available for analysis from 40 women; further
details of study withdrawals are shown in Figure 1 .
The mean age of women was 28.9years and 95% were
white; details of volunteer demographics and menstrual
cycle characteristics are provided in Table 1
. The mean
cycle length of volunteers was 28days and the mean day
of ovulation was Day 15.
51 women recruited
3 women withdrew consent
(personal reasons)
7 women site withdrawn
2 cystic ovaries
2 pre-trial pregnancy
3 non-compliant
41 volunteers completed the study
40 volunteers had data available for analysis
1 anovular cycle
Figure 1  Flow diagram of volunteer participation.
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4Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day
Table 1  Volunteer demographics.
n
Mean age, years (SD)  . (.)
Age range, years  . – .
  – , n (%)  (.)
  – , n (%)  (.)
  – , n (%)  (.)
  – , n (%) (.)
Ethnicity, n (%) 
 White  (.)
 Asian (.)
Mean cycle length
a , days (SD)  . (.)
Mean day of ovulation
b (SD)  . (.)
Mean length of luteal phase
a , days (SD)  . (.)
Number of previous pregnancies, n (%)

 (.)
 (.)
 ()
Number of previous live births, n (%)

 (.)
 (.)
 (.)
Number of previous miscarriages, n (%)

 (.)
 (.)
 (.)
Number of previous terminations, n (%)

 (.)
 (.)
(.)
SD, standard deviation. a Excluding pregnant volunteers,
b Also con-
sidered length of follicular phase.
Hormone study ranges
Study urinary hormone ranges consisting of the median
urinary hormone levels and 10th 90th centile ranges
by cycle day, relative to the day of objective ovulation as
assessed by ultrasound, were derived for LH, E3G, FSH
and P3G ( Figure 2 ); Table 2 shows the corresponding
values for the mean urinary level of each hormone relative
to the day of ovulation.
Urinary LH surge preceded ovulation for most women
(mean time from surge to ovulation 0.81 days, standard
deviation [SD] 0.89). Peak urinary LH levels were seen a
median of 0.5days prior to ovulation (5th 95th centile:
1.5 + 0.5 days). However, the timing of LH peak was
dependent on whether the assay was measuring total or
intact LH ( Figure 3 ); peak LH was observed approximately 1
day later with the total LH assay (Perkin Elmer assay) com-
pared with the intact LH assay (in-house assay system).
The timing of the LH surge was the same irrespective of
the assay used. Comparison of LH surge characteristics
observed in individual volunteers is shown in Figure4 ;
these examples illustrate the influence of the assay used
on the surge profile. Six volunteers had LH surge profiles
that did not differ between assays (an example of one
such volunteer is shown in Figure 4A). However, for most
individuals, the total LH assay continued to detect LH for
several days post-surge, with LH levels peaking later than
that observed when using the intact LH assay (an example
of one such volunteer is shown in Figure 4B). In six cases, a
second peak in LH levels was seen with the total LH assay,
whereas the intact LH assay only showed a single peak (an
example of one such volunteer is shown in Figure 4C).
A rise in urinary P3G from baseline occurred after ovu-
lation in all volunteers; levels peaked a median of 7.5days
following ovulation (5th – 95th centile range: + 4.5 – + 10.5
days). Median urinary peak E3G levels were also observed
0.5days pre-ovulation (5th – 95th centile: – 2.5 – + 9.5 days)
and the same median peak day was seen for FSH levels
( – 0.5 days, 5th – 95th centile: – 2.5 – + 0.5 days). There was
a persistent and substantial rise in urinary E3G observed
from approximately 3days prior to ovulation until up to
5days post-ovulation for the 90th centile.
This study did not aim to examine age-related hor-
monal changes, however, differences in the median levels
of women aged < 30 years (n = 20) compared with those
aged    30 years (n = 20) were observed. It was found that
median levels of several hormones were higher in women
age    30 years, although numbers were too low for formal
analysis (median level for < 30 years vs. median level
for    30years: volunteers peak intact LH = 57.1 vs. 71.3mlU/
mL; peak FSH = 19.8 vs. 22.6 mlU/mL; Day 3 FSH = 4.9 vs. 6.7
mlU/mL; peak P3G = 29.1 vs. 34.3 mlU/mL). Whereas no dif-
ference in peak E3G (59 vs. 60.3 mlU/mL) or peak total LH
(69.9 vs. 69.8 mlU/mL) were observed between age groups.
Discussion
This study presents the first urinary reproductive hormone
ranges referenced to the actual day of ovulation, thus pro-
viding ranges to examine menstrual cycle endocrinology.
The high level of agreement between the LH surge
and day of ovulation observed in this study highlights
that urinary LH measurements are a reliable and accurate
predictor of ovulation. The LH surge causes the dominant
follicle to rupture and release a mature ovum and ovula-
tion typically occurs approximately 28 48 h after the LH
surge [16] and will not occur in its absence [21] . In this
study, however, identification of the LH peak was found
to be assay-dependent and could occur post-ovulation,
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Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day5
therefore care must be employed when interpreting LH
profiles. The difference in these profiles is most likely due
to the recognition of LH- β cf in the urine samples. Human
LH is a heterodimeric glycoprotein consisting of a smaller
α subunit (LH- α ) and a larger β subunit. Urinary LH- α and
intact LH- β have been observed to show a similar pattern
to that of complete LH during the menstrual cycle [22, 23] ;
however, LH- β cf material was observed to increase during
and up to 3days after the urinary LH surge [22] . LH- β cf
is a fragment of LH produced by the degradation of LH,
which most likely occurs in the kidneys [22] . LH- β cf was
originally isolated from the human pituitary gland, and
subsequently a urinary form (with minimal structural dif-
ferences) was identified and characterised [24, 25] . LH- β cf
has been shown to be the predominant form of LH in urine
during the peri-ovulatory period and levels peak 1 3days
later than those of intact LH [23] . In contrast, no LH- β cf
surge has been detected in serum. This supports the view
that LH- β cf is a product of metabolic degradation, hence
the lag period observed between the peak levels of intact
LH and LH- β cf peak, as the process of degradation will
extend the time taken to appear in urine [23] . A previous
study by Park etal., which characterised the urinary LH
surge in young women, utilised the LH assay recognis-
ing LH- β cf [26] . Thus, this finding that urinary LH surges
are extremely variable in all aspects of configuration,
amplitude and duration, is likely to be influenced by the
detection of LH- β cf. Similarly, a study by Ecochard etal.
observed two LH peaks in some cycles, and found the
concentration of LH continued to increase post-ovulation
[27] . From observations in other studies analysing the
pattern of LH- β cf, these findings can be explained by the
975311 3 5 7 9
10 86420246810
Day relative to ovulation day
40
30
20
10
0
Urinary LH concentration, mlU/mL
36
34
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26
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18
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14
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0
Number of data points
Number data points
90th percentile
Median 10th percentile Number data points
90th percentile
Median 10th percentile
Number data points
90th percentile
Median 10th percentile
A
9753113579
10 86420246810
Day relative to ovulation day
40
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10
0
Urinary E3G concentration, ng/mL
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Number of data points
B
D
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Day relative to ovulation day
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10
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Urinary FSH concentration, mlU/mL
36
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9753113579
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Day relative to ovulation day
Number data points
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Urinary P3G concentration, µg/mL
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Figure 2 Reference ranges of urinary hormone levels relative to ovulation day (determined by trans-vaginal ultrasound) for: (A) LH (intact);
(B) E3G; (C) FSH; (D) P3G.
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6Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day
Table 2 Mean urinary levels of each hormone relative to the day of ovulation.
Day relative
to ovulationa
n Intact LH, mIU/mL
Median ( – 
centiles)
Total LH, mIU/mL
Median ( – 
centiles)
EG, ng/mL
Median ( – 
centiles)
FSH, mIU//mL
Median ( – 
centiles)
PG, μ g/mL
Median ( – 
centiles)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
–   . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
 . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
  . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
  . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
  . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
  . (. – .) . (. – .) . (. – .) . (. – .) . (. – .)
aData is rounded to whole day.
presence of LH- β cf and its detection by the assay used in
this study. Thus these and similar studies are not describ-
ing the endocrinologically relevant LH surge, but rather
characterising biologically active intact LH and, to a
greater extent, its metabolites. This differential detection
of LH- β cf by different assays confounds the literature with
conflicting descriptions of the LH surge, but these discrep-
ancies are entirely due to assay specificity. It is important
to emphasise that, in our study, the assay that recognises
intact LH and the assay that recognises total LH are both
equally able to define the day of the LH surge. Informa-
tion regarding LH- β cf detection by assays is generally not
available, as most quantitative assays are validated for
serum use, where LH- β cf is not detectable.
Home-based ovulation tests are typically designed to
identify ovulation by detection of this LH surge in urine.
Studies have confirmed their accuracy in detecting the LH
surge relative to serum hormone levels and in predicting
ovulation relative to ultrasound-detected ovulation [28
32] . Thus, the results of this study confirm previous find-
ings on the accuracy of urinary hormone testing to predict
the onset of the fertile window in women and the applica-
tion of urinary LH surge detection for home-based fertility
testing [33] . The data shown here indicate that a LH cut-off
value would be effective in predicting ovulation. However,
as there is overlap between the population baseline value
of intact LH (90th centile around 10 15 mIU/mL prior to
surge) and surge level (10th centile for day of ovulation
9.9 mIU/mL), a single threshold would not provide 100%
accurate prediction. In addition, the observed persis-
tent and notable rise in urinary E3G from approximately
3days prior to ovulation makes E3G a candidate marker
for the onset of a woman s fertile window, as it is generally
accepted that sperm can survive for up to 5days in sperm-
supportive, fertile cervical mucus [9] . More sophisticated
versions of the home-based ovulation test detect both
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Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day7
urinary LH and E3G, to identify the earlier onset of the
fertile window signified by the increase in E3G prior to the
LH surge [34, 35] . A rise of urinary P3G above baseline is a
consistent marker of luteinisation. The human ovum has
a lifespan of < 1 day, and as our data indicate that P3G rise
is consistently > 1 day after ovulation, this rise provides an
excellent marker for closure of the fertile window.
The National Academy of Clinical Biochemistry in
the USA states that point-of-care tests for the detection
of urinary LH have excellent diagnostic sensitivity for the
detection of ovulation [36] . In Guideline 176, they strongly
recommend the use of such devices for the purpose of
detecting ovulation, stating that urine LH tests are recom-
mended to predict ovulation within 48h of a positive test
[36] .
The use of home fertility monitoring is not only valu-
able in enabling women to identify their fertile days, but
can also alert women to possible subfertility. For instance,
persistent lack of an LH surge highlights a high proportion
of anovulatory cycles and may be indicative of PCOS, for
example. PCOS is found in up to 12% of the population
and is often underdiagnosed [37 40] , mainly because of
differing, and sometimes inconsistent, diagnostic criteria.
One limitation of urinary testing is the variation in
urine volume associated with sample collection, which is
a potential source of error due to the effect of volume on
concentration. Creatinine is a waste product of muscle
metabolism, which is relatively constantly excreted in
urine; characteristics that have led to it being utilised
to normalise the quantity of a given analyte in urine
samples. Thus creatinine adjustment is frequently used
to correct for urinary volume effects, but this has been
found to be unnecessary for the determination of specific
hormonal parameters on a given day, e.g., LH peak [41] .
Furthermore, in a study evaluating urinary and serum
pregnanediol, the adjustment for creatinine introduced
an error in older women due to an observed decline in
creatinine clearance with age, and this adjustment is
thus discouraged in such instances [42] . This study has
found that urinary hormone analysis without the need
for creatinine correction can provide all the necessary
detail of menstrual cycle endocrinology. Other potential
limitations of this study are the relatively small sample
size and limited ethnicity representation (95% white).
In a study by Marsh etal., higher estradiol levels were
observed in African-American women compared with
Caucasian women, thus the urinary ranges reported here
may not be representative of women in all ethnic groups,
although no differences in FSH or LH were observed in
this study [43] .
975311 3 5 7 910 86420 2 4 6 810
Day relative to ovulation day
Intact LH assay Total LH assay
10th and 90th centiles 10th and 90th centiles
80
100
60
40
20
0
Urinary LH concentration, mIU/mL
Figure 3 Level of urinary LH relative to ovulation day, as determined by ultrasound, measured using in-house assays (identifying intact LH)
on AutoDELFIA platform (Perkin Elmer) and standard Perkin Elmer assay (identifying total LH).
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8Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day
2 4 6 8 10 14 16 18 20 21 2313579 13151719 222425
100
A
B
C
90
80
70
60
50
40
30
20
10
0
Urinary LH concentration, mIU/mLUrinary LH concentration, mIU/mLUrinary LH concentration, mIU/mL
11 12
Total LH assay Intact LH assay Ovulation day
2 4 6 8 10 14 16 18 20 21 231 3 5 7 9 13 15 17 19 22 24 25
100
90
80
70
60
50
40
30
20
10
0
26 27 28 2911 12
Diary day of cycle
Diary day of cycle
Diary day of cycle
246810 1416182021231 3 5 7 9 13151719 222425
100
90
80
70
60
50
40
30
20
10
0
26 27 28 2911 12
Total LH assay Intact LH assay Ovulation day
Total LH assay Intact LH assay Ovulation day
Figure 4 Individual profiles of volunteers of urinary LH relative to ovulation day, as determined by ultrasound, measured using in-house
assays on AutoDELFIA platform (Perkin Elmer), measuring intact LH and standard Perkin Elmer assay, measuring total LH.
(A) A volunteer where both assays provided equivalent surge profiles; (B) A volunteer where peak LH concentration differed by 2days
between assay; (C) A volunteer where in-house assay showed single peak, whilst Perkin Elmer assay showed 2 peaks.
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Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day9
In conclusion, this study highlights the accuracy and
reliability of urinary hormone measurements for predict-
ing and confirming ovulation, perhaps in some instances,
replacing the need for blood sample analysis. Further-
more, it provides reproductive hormone ranges referenced
to the actual day of ovulation, to give urinary hormone
ranges for use in the examination of menstrual cycle
endocrinology and for close cycle monitoring for timing
of interventions.
Acknowledgments: Editorial support for the development
of this manuscript was provided by Dr. Debra Scates from
IMC Healthcare Communication, sponsored by SPD Devel-
opment Co., Ltd.
Author contributions: All the authors have accepted
responsibility for the entire content of this submitted
manuscript and approved submission.
Financial support: This study was funded by SPD Develop-
ment Co., Ltd., a wholly-owned subsidiary of SPD Swiss
Precision Diagnostics GmbH. Trial registration number:
NCT01802060.
Employment or leadership: S. Johnson, S. Weddell and S.
Godbert are employees of SPD Development Co., Ltd. G.
Freundl has received consultancy from SPD Development
Co., Ltd.
Honorarium: None declared.
Competing interests: The funding organisation(s) played
no role in the study design; in the collection, analysis, and
interpretation of data; in the writing of the report; or in the
decision to submit the report for publication.
References
1. Balasch J, Gratac ó s E. Delayed childbearing: effects on
fertility and the outcome of pregnancy. Fetal Diagn Ther
2011;29:263 – 73.
2. Heffner LJ. Advanced maternal age how old is too old ? N Engl J
Med 2004;351:1924 – 9.
3. Committee opinion No. 589. Female age-related fertility decline.
Fertil Steril 2014;101:633 – 4.
4. Lundsberg LS, Pal L, Gariepy AM, Xu X, Chu MC, Illuzzi LJ. Knowl-
edge, attitudes, and practices regarding conception and fertility:
a population-based survey among reproductive-age United
States women. Fertil Steril 2014;101:767 74.
5. Gnoth C, Frank-Herrmann P, Schmoll A, Godehardt E, Freundl G.
Cycle characteristics after discontinuation of oral contraceptives.
Gynecol Endocrinol 2002;16:307 – 17.
6. Zinaman M, Johnson S, Ellis J, Ledger W. Accuracy of percep-
tion of ovulation day in women trying to conceive. CMRO
2012;28:1 – 6.
7. Johnson SR, Miro F, Barrett S, Ellis J. Levels of urinary human
chorionic gonadotrophin (hCG) following conception and vari
ability of the menstrual cycle in a cohort of women attempting
to conceive. CMRO 2009;25:741 8.
8. Creinin MD, Keverline S, Meyn LA. How regular is regular ?
An analysis of menstrual cycle regularity. Contraception
2004;70:289 – 92.
9. Wilcox AJ, Weinberg CR, Baird DD. Timing of sexual intercourse
in relation to ovulation. N Engl J Med 1995;333:1517 21.
10. Liu Y, Johnson WO, Gold EB, Lasley BL. Bayesian analysis of risk
factors for anovulation. Stat Med 2004;23:1901 19.
11. Hambridge H, Mumford SL, Mattison DR, Ye A, Pollack AZ, Bloom
MS, etal. The influence of sporadic anovulation on hormone
levels in ovulatory cycles. Hum Reprod 2013;28:1687 94.
12. Collins WP. The evolution of reference methods to monitor ovu-
lation. Am J Obstet Gynecol 1991;165:1994 6.
13. Kassam A, Overstreet JW, Snow-Harter C, De Souza MJ, Gold
EB, Lasley BL. Identification of anovulation and transient luteal
function using a urinary pregnanediol-3-glucuronide ratio algo-
rithm. Environ Health Perspect 1996;104:408 13.
14. Blackwell LF, Vigil P, Cooke DG, d Arcangues C, Brown JB.
Monitoring of ovarian activity by daily measurement of urinary
excretion rates of oestrone glucuronide and pregnanediol glucu-
ronide using the Ovarian Monitor, Part III: variability of normal
menstrual cycle profiles. Hum Reprod 2013;28:3306 15.
15. Stricker R, Eberhart R, Chevailler M, Quinn F, Bischof P, Stricker
R. Establishment of detailed reference values for luteinizing hor-
mone, follicle stimulating hormone, estradiol, and progesterone
during different phases of the menstrual cycle on the Abbott
ARCHITECT analyser. Clin Chem Lab Med 2006;44:883 7.
16. Seibel M. Luteinizing hormone and ovulation timing. J Reprod
Med 1986;31:754 – 9.
17. Direito A, Bailly S, Mariani A, Ecochard R. Relationships
between the luteinizing hormone surge and other characteris-
tics of the menstrual cycle in normally ovulating women. Fertil
Steril 2013;99:279 – 85.
18. Ecochard R, Leiva R, Bouchard T, Boehringer H, Direito A,
Mariani A, etal. Use of urinary pregnanediol 3-glucuronide to
confirm ovulation. Steroids 2013;78:1035 – 40.
19. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek
CJ, etal. On behalf of the Global Burden of Metabolic Risk
Factors of Chronic Diseases Collaborating Group (Body Mass
Index). National, regional, and global trends in body-mass index
since 1980: systematic analysis of health examination surveys
and epidemiological studies with 960 country-years and 9.1 mil-
lion participants. Lancet 2011;377:557 67.
20. Hahn KA, Wise LA, Riis AH, Mikkelsen EM, Rothman KJ,
Banholzer K, etal. Correlates of menstrual cycle charac-
teristics among nulliparous Danish women. Clin Epidemiol
2013;5:311 – 9.
21. Kerin JF, Edmonds D, Warnes G, Cox L, Seamark R, Mathews C,
etal. Morphological and functional relations of Graafian fol-
licle growth to ovulation in women using ultrasonic, laparo-
scopic and biochemical measurements. Br J Obstet Gynecol
1981;88:81 – 90.
22. Neven P, Iles RK, Howes I, Sharma K, Shepherd JH, Edwards R,
etal. Substantial urinary concentrations of material resembling
β -core fragment of chorionic gonadrotropin β -subunit in mid-
menstrual cycle. Clin Chem 1993;39:1857 60.
23. O ’ Connor JF, Kovalevskaya G, Birken S, Schlatterer JP, Schechter
D, McMahon DJ, etal. The expression of the urinary forms of
human luteinizing hormone beta fragment in various popula-
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Download Date | 1/20/15 10:05 AM
10Johnson etal.: Urinary reproductive hormone ranges referenced to independently determined ovulation day
tions as assessed by a specific immunoradiometric assay. Hum
Reprod 1998;13:826 – 35.
24. Kurowska E, Szewczuk A. Isolation of human lutropin from
woman urine and comparison of its properties with pituitary
hormone. Arch Immunol Ther Exp 1999;47:179 83.
25. Birken S, Gawinowiz MA, Maydelman Y, Migrom Y. Metabolism
of gonadotropins: comparison of the primary structures of the
human pituitary and urinary LH β cores and the chimpanzee CG β
core demonstrates universality of core production. J Endocrinol
2001;171:131 – 41.
26. Park SJ, Goldsmith LT, Skurnick JH, Wojtczuk A, Weiss G. Char-
acteristics of the urinary luteinizing hormone surge in young
ovulatory women. Fert Steril 2007;88:684 90.
27. Ecochard R, Boehringer H, Rabilloud M, Marret H. Chronological
aspects of ultrasonic, hormonal, and other indirect indices of
ovulation. Br J Obstet Gynecol 2001;108:822 9.
28. Elkind-Hirsch K, Goldzieher JW, Gibbons WE, Besch PK.
Evaluation of the Ovustick urinary luteinizing hormone kit
in normal and stimulated menstrual cycles. Obstet Gynecol
1986;67:450 – 3.
29. Gudgeon K, Leader L, Howard B. Evaluation of the accuracy of
the home ovulation detection kit, Clearplan, at predicting ovula-
tion. Med J Aust 1990;152:345 9.
30. Guermandi E, Vegetti W, Bianchi MM, Uglietti A, Ragni G, Crosig-
nani P. Reliability of ovulation tests in infertile women. Obstet
Gynecol 2001;97:92 – 6.
31. Leiva R, Burhan U, Kyrillos E, Fehring R, McLaren R, Dalzell C,
etal. Use of ovulation predictor kits as adjuncts when using
fertility awareness methods (FAMs): a pilot study. J Am Board
Fam Med 2014;27:427 – 9.
32. Miller PB, Soules MR. Ovulation prediction during menstrual
cycles of normal women. Obstet Gynecol 1996;87:13 7.
33. Cervinski MA, Gronowski AM. Reproductive-endocrine point-of-
care testing: current status and limitations. Clin Chem Lab Med
2010;48:935 – 42.
34. Behre HM, Kuhlage J, Gassner C, Sonntage B, Schem C, Sch-
neider HP, etal. Prediction of ovulation by urinary hormone
measurements with the home use Clearblue Fertility Monitor:
comparison with transvaginal ultrasound scans and serum
hormone measurements. Hum Reprod 2000;12:2478 82.
35. Robinson J, Wakelin M, Ellis J. Increased pregnancy rate with use
of Clearblue Easy Fertility Monitor. Fertil Steril 2007;87:329 34.
36. Gronowski AM, Grenache DG, Markenson G, Weiner R, Demers
LM, St. Louis P. Evidence-based practice for point-of-care testing.
In: Nichols JH, editor. Reproductive testing. Washington, DC:
American Association for Clinical Chemistry (AACC) Press, 2006.
37. Asunci ó n M, Calvo RM, San Mill á n JL, Sancho J, Avila S, Escobar-
Morreale HF. A prospective study of the prevalence of the
polycystic ovary syndrome in unselected Caucasian women from
Spain. J Clin Endocrinol Metab 2000;85:2434 8.
38. Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES, Yildiz
BO. The prevalence and features of the polycystic ovary syn-
drome in an unselected population. J Clin Endocrinol Metab
2004;89:2745 – 9.
39. Diamanti-Kandarakis E, Kouli CR, Bergiele AT, Filandra FA,
Tsianateli TC, Spina GG, etal. A survey of the polycystic ovary
syndrome in the Greek island of Lesbos: hormonal and meta-
bolic profile. J Clin Endocrinol Metab 1999;84:4006 11.
40. Knochenhauer ES, Key TJ, Kahsar-Miller M, Waggoner W, Boots
LR, Azziz R. Prevalence of the polycystic ovary syndrome
in unselected black and white women of the southeastern
United States: a prospective study. J Clin Endocrinol Metab
1998;83:3078 – 82.
41. Miro F, Coley J, Gani MM, Perry PW, Talbot D, Aspinall LJ. Com-
parison between creatinine and pregnanediol adjustments in
the retrospective analysis of urinary hormone profiles during the
human menstrual cycle. Clin Chem Lab Med 2004;42:1043 50.
42. Zacur H, Kaufman SC, Smith B, Wshoff C, Helbig D, Lee YJ, etal.
Does creatinine adjustment of urinary pregnanediol glucuronide
reduce or introduce measurement error ? Gynecol Endocrinol
1997;11:29 – 33.
43. Marsh EE, Shaw ND, Klingman KM, Tiamfook-Morgan TO,
Yialamas MA, Sluss PM, etal. Estrogen levels are higher
across the menstrual cycle in African-American women
compared with Caucasian women. J Clin Endocrinol Metab
2011;96:3199 – 206.
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... A pragmatic solution is to schedule biopsies relative to the preovulatory LH surge (Tewary et al., 2020). A prospective study on a small cohort of healthy women (n ¼ 40) reported that the urinary LH surge occurs mostly within one day prior to ovulation, although the range was 4 days (Johnson et al., 2015;Roos et al., 2015). Furthermore, the rise in urinary pregnanediol-3-glucuronide, a progesterone metabolite, is more variable, occurring over a range of 5 days after ovulation (Johnson et al., 2015;Roos et al., 2015). ...
... A pragmatic solution is to schedule biopsies relative to the preovulatory LH surge (Tewary et al., 2020). A prospective study on a small cohort of healthy women (n ¼ 40) reported that the urinary LH surge occurs mostly within one day prior to ovulation, although the range was 4 days (Johnson et al., 2015;Roos et al., 2015). Furthermore, the rise in urinary pregnanediol-3-glucuronide, a progesterone metabolite, is more variable, occurring over a range of 5 days after ovulation (Johnson et al., 2015;Roos et al., 2015). ...
... A prospective study on a small cohort of healthy women (n ¼ 40) reported that the urinary LH surge occurs mostly within one day prior to ovulation, although the range was 4 days (Johnson et al., 2015;Roos et al., 2015). Furthermore, the rise in urinary pregnanediol-3-glucuronide, a progesterone metabolite, is more variable, occurring over a range of 5 days after ovulation (Johnson et al., 2015;Roos et al., 2015). Thus, while the timing of endometrial biopsies relative to clinical markers of ovulation is useful and convenient, it does not ensure comparable exposures to progesterone stimulation. ...
Article
Full-text available
Study question: Can the accuracy of timing of luteal phase endometrial biopsies based on urinary ovulation testing be improved by measuring the expression of a small number of genes and a continuous, non-categorical modelling approach? Summary answer: Measuring the expression levels of six genes (IL2RB, IGFBP1, CXCL14, DPP4, GPX3 and SLC15A2) is sufficient to obtain substantially more accurate timing estimates and to assess the reliability of timing estimates for each sample. What is known already: Commercially available endometrial timing approaches based on gene expression require large gene sets and use a categorical approach that classifies samples as pre-receptive, receptive or post-receptive. Study design, size, duration: Gene expression was measured by RTq-PCR in different sample sets, comprising a total of 664 endometrial biopsies obtained 4-12 days after a self-reported positive home ovulation test. A further 36 endometrial samples were profiled by RTq-PCR as well as RNA-sequencing. Participants/materials, setting, methods: A computational procedure, named 'EndoTime', was established that models the temporal profile of each gene and estimates the timing of each sample. Iterating these steps, temporal profiles are gradually refined as sample timings are being updated, and confidence in timing estimates is increased. After convergence, the method reports updated timing estimates for each sample while preserving the overall distribution of time points. Main results and the role of chance: The Wilcoxon rank-sum test was used to confirm that ordering samples by EndoTime estimates yields sharper temporal expression profiles for held-out genes (not used when determining sample timings) than ordering the same expression values by patient-reported times (GPX3: P < 0.005; CXCL14: P < 2.7e-6; DPP4: P < 3.7e-13). Pearson correlation between EndoTime estimates for the same sample set but based on RTq-PCR or RNA-sequencing data showed a high degree of congruency between the two (P = 8.6e-10, R2 = 0.687). Estimated timings did not differ significantly between control subjects and patients with recurrent pregnancy loss or recurrent implantation failure (P > 0.05). Large scale data: The RTq-PCR data files are available via the GitHub repository for the EndoTime software at https://github.com/AE-Mitchell/EndoTime, as is the code used for pre-processing of RTq-PCR data. The RNA-sequencing data are available on GEO (accession GSE180485). Limitations, reasons for caution: Timing estimates are informed by glandular gene expression and will only represent the temporal state of other endometrial cell types if in synchrony with the epithelium. Methods that estimate the day of ovulation are still required as these data are essential inputs in our method. Our approach, in its current iteration, performs batch correction such that larger sample batches impart greater accuracy to timing estimations. In theory, our method requires endometrial samples obtained at different days in the luteal phase. In practice, however, this is not a concern as timings based on urinary ovulation testing are associated with a sufficient level of noise to ensure that a variety of time points will be sampled. Wider implications of the findings: Our method is the first to assay the temporal state of luteal-phase endometrial samples on a continuous domain. It is freely available with fully shared data and open-source software. EndoTime enables accurate temporal profiling of any gene in luteal endometrial samples for a wide range of research applications and, potentially, clinical use. Study funding/competing interest(s): This study was supported by a Wellcome Trust Investigator Award (Grant/Award Number: 212233/Z/18/Z) and the Tommy's National Miscarriage Research Centre. None of the authors have any competing interests. J.L. was funded by the Biotechnology and Biological Sciences Research Council (UK) through the Midlands Integrative Biology Training Partnership (MIBTP, BB/M01116X/1).
... This FIE application revealed a strong signal for the entry into the fertile range with daily serum estradiol levels. To test the applicability of the FIE for detection of the periovulatory transition, daily serum P (the standard for luteal phase assessment) and daily PDG levels from four different laboratories were submitted to FIE analysis: serum P from Stricker et al. [18] and Roos et al. [19] and urinary PDG from Johnson et al. [20] and Alliende et al. [14]. Indeed, the FIE analysis with serum P (FIE-P) and with urinary PDG (FIE-PDG) created sequences of positive FIE values-"clusters"-that occurred in the periovulatory interval denoting the transition to the luteal phase. ...
... The day-specific P and PDG levels used for the FIE analysis are tabulated in the Supplementary Materials. Day-specific serum P levels were used as reported by Stricker et al. [18] and Roos et al. [19], and day-specific urinary PDG levels were used as reported by Johnson et al. [20] and provided by Alliende et al. (Supplementary Materials) [14]. These day-specific levels variously included: mean, median, 5th, 10th, 90th, 95th percentile (PCTL) levels. ...
... Mean Fertility Indicator Equation (FIE) values with 95% confidence limits for interval, Day −6 to Day +6, using day-specific serum progesterone levels (top) and day-specific urinary pregnanediol-3-glucuronide levels (bottom) of Stricker et al.[18], Roos et al.[19], Johnson et al.[20] and Alliende et al.(Supplementary Materials and ref [14]). The FIE values, FIE-P and FIE-PDG, are listed inTables 1 and 2. Day 0, day of ovulation. ...
Article
Full-text available
Background and Objectives: The Fertility Indicator Equation (FIE) has been shown to signal the fertile phase during the ovulatory menstrual cycle. It was hypothesized that this formulation, a product of two sequential normalized changes with a sign indicating direction of change, could be used to identify the transition from ovulatory to luteal phase with daily serum progesterone (P) and urinary pregnanediol-3-glucuronide (PDG) levels. Materials and Methods: Day-specific serum P levels from two different laboratories and day-specific urinary PDG levels from an additional two different laboratories were submitted for FIE analysis. These day-specific levels included mean or median, 5th, 10th, 90th and 95th percentile data. They were indexed to the day of ovulation, day 0, by ultrasonography, serum or urinary luteinizing hormone (LH). Results: All data sets showed a clear “cluster”—a periovulatory sequence of positive FIE values with a maximum. All clusters of +FIE signaled the transition from the ovulatory to luteal phase and were at least four days in length. The start day for the serum P and urinary PDG FIE clusters ranged from −3 to −1 and −3 to +2, respectively. The end day for serum P and PDG clusters went from +2 to +7 and +4 to +8, respectively. Outside these periovulatory FIE-P and FIE-PDG clusters, there were no consecutive positive FIE values. In addition, the maximum FIE-P and FIE-PDG values throughout the entire cycles were found in the clusters. Conclusions: FIE analysis with either daily serum P or urinary PDG levels provided a distinctive signature to recognize the periovulatory interval. The Fertility Indicator Equation served to robustly signal the transition from the ovulatory phase to the luteal phase. This may have applications in natural family planning especially with the recent emergence of home PDG tests.
... They correlated multiple peak LH surges with smaller preovulatory follicles and prolonged LH surges (more than 3 days after ovulation) with delayed luteinization, indicating possible luteal insufficiency (7). In addition, the LH surge was discovered to be a better marker than the LH peak itself to predict ovulation (24). As the ovulation and possibility of conception often occurs prior to the detectable LH surge, LH tests only indicate half of all ovulations. ...
Article
Full-text available
Timing for sexual intercourse is important in achieving pregnancy in natural menstrual cycles. Different methods of detecting the fertile window have been invented, among them luteinization hormone (LH) to predict ovulation and biphasic body basal temperature (BBT) to confirm ovulation retrospectively. The gold standard to detect ovulation in gynecology practice remains transvaginal ultrasonography in combination with serum progesterone. In this study we evaluated a wearable temperature sensing patch (femSense®) using continuous body temperature measurement to confirm ovulation and determine the end of the fertile window. 96 participants received the femSense® system consisting of an adhesive axillary thermometer patch and a smartphone application, where patients were asked to document information about their previous 3 cycles. Based on the participants data, the app predicted the cycle length and the estimated day of ovulation. From these predictions, the most probable fertile window and the day for applying the patch were derived. Participants applied and activated the femSense® patch on the calculated date, from which the patch continuously recorded their body temperature throughout a period of up to 7 days to confirm ovulation. Patients documented their daily urinary LH test positivity, and a transvaginal ultrasound was performed on day cycle day 7, 10, 12 and 14/15 to investigate the growth of one dominant follicle. If a follicle reached 15 mm in diameter, an ultrasound examination was carried out every day consecutively until ovulation. On the day ovulation was detected, serum progesterone was measured to confirm the results of the ultrasound. The performance of femSense® was evaluated by comparing the day of ovulation confirmation with the results of ovulation prediction (LH test) and detection (transvaginal ultrasound). The femSense® system confirmed ovulation occurrence in 60 cases (81.1%) compared to 48 predicted cases (64.9%) with the LH test (p = 0.041). Subgroup analysis revealed a positive trend for the femSense® system of specific ovulation confirmation within the fertile window of 24 h after ovulation in 42 of 74 cases (56.8%). Cycle length, therapy method or infertility reason of the patient did not influence accuracy of the femSense® system. The femSense® system poses a promising alternative to the traditional BBT method and is a valuable surrogate marker to transvaginal ultrasound for confirmation of ovulation.
... In some cycles, the oestrogen rise occurs many days before ovulation, resulting in a long fertile window, while in others oestrogen rise can occur on the day of the LH surge. 19,20 When menstrual cycle data is used to predict the fertile period for natural family planning contraception (calendar method), the fertile window predicted is generally very long to prevent women being at high risk of an unwanted pregnancy. These methods also indicate their low contraceptive reliability. ...
Article
Full-text available
Background: Period tracking applications (apps) allow women to track their menstrual cycles and receive a prediction for their period dates. The majority of apps also provide predictions of ovulation day and the fertile window. Research indicates apps are basing predictions on assuming women undergo a textbook 28-day cycle with ovulation occurring on day 14 and a fertile window between days 10 and 16. Objective: To determine how the information period tracker apps give women on their period dates, ovulation day and fertile window compares to expected results from big data. Methods: Five women's profiles for 6 menstrual cycles were created and entered into 10 apps. Cycle length and ovulation day for the sixth cycle were Woman 1-Constant 28 day cycle length, ovulation day 16; Woman 2-Average 23 day cycle length, ovulation day 13; Woman 3-Average 28 day cycle length, ovulation day 17; Woman 4-Average 33 day cycle length, ovulation day 20; and Woman 5-Irregular, average 31 day cycle length, ovulation day 14. Results: The 10 period tracker apps examined gave conflicting information on period dates, ovulation day and the fertile window. For cycle length, the apps all predicted woman 1's cycles correctly but for women 2-5, the apps predicted 0 to 8 days shorter or longer than expected. For day of ovulation, for women 1-4, of the 36 predictions, 3 (8%) were exactly correct, 9 predicted 1 day too early (25%) and 67% of predictions were 2-9 days early. For woman 5, most of the apps predicted a later day of ovulation. Conclusion: Period tracker apps should ensure they only give women accurate information, especially for the day of ovulation and the fertile window which can only be predicted if using a marker of ovulation, such as basal body temperature, ovulation sticks or cervical mucus.
Conference Paper
Menstruation is a finely-controlled cycle that responds to the prevailing endocrine and paracrine environment. However, social stigma has led to inadequate menstrual literacy, both among academics and the larger public. The poorly understood mechanisms of menstruation ultimately lead to suboptimal healthcare treatment and services for biological females, culminating in a physical, financial, and emotional burden. Various hormones signal the beginning and end of each stage of menstruation. In particular, luteinizing hormone (LH) is a major player in ovulation, corpus luteum function, and the stimulation of other key hormones. A LH model could be used to understand the larger control system of menstruation if analyzed in conjunction with models for other major hormones (e.g., FSH, progesterone, and GnRH). Thus, exploring a smaller subsection of LH dynamics within the larger control system of menstruation can lead to a greater understanding of menstruation, contributing towards therapeutics and research for women's health. Using parameters and kinetic equations in the existing body of literature, a transfer function was derived to model LH dynamics. Analysis of system stability reveals overdamped dynamics in LH sensitization at baseline, and underdamped mildly resonant dynamics at the peak of the menstrual cycle, the strength of which depends on the values of the rate constants of LH receptor formation, binding, and desensitization.
Article
Background The AACC Academy revised the reproductive testing section of the Laboratory Medicine Practice Guidelines: Evidence-Based Practice for Point-of-Care Testing (POCT) published in 2007. Methods A panel of Academy members with expertise in POCT and laboratory medicine was formed to develop guidance for the use of POCT in reproductive health, specifically ovulation, pregnancy, premature rupture of membranes (PROM), and high-risk deliveries. The committee was supplemented with clinicians having Emergency Medicine and Obstetrics/Gynecology training. Results Key recommendations include the following. First, urine luteinizing hormone (LH) tests are accurate and reliable predictors of ovulation. Studies have shown that the use of ovulation predicting kits may improve the likelihood of conception among healthy fertile women seeking pregnancy. Urinary LH point-of-care testing demonstrates a comparable performance among other ovulation monitoring methods for timing intrauterine insemination and confirming sufficient ovulation induction before oocyte retrieval during in vitro fertilization. Second, pregnancy POCT should be considered in clinical situations where rapid diagnosis of pregnancy is needed for treatment decisions, and laboratory analysis cannot meet the required turnaround time. Third, PROM testing using commercial kits alone is not recommended without clinical signs of rupture of membranes, such as leakage of amniotic fluid from the cervical opening. Finally, fetal scalp lactate is used more than fetal scalp pH for fetal acidosis due to higher success rate and low volume of sample required. Conclusions This revision of the AACC Academy POCT guidelines provides recommendations for best practice use of POCT in fertility and reproduction.
Preprint
Salivary steroid immunoassays are widely used in psychoneuroendocrinology to investigate the psychological effects of menstrual cycle phase. Though manufacturers advertise their assays as suitable, they have not been rigorously validated for this purpose. We collated data from eight studies across more than 1,200 women and more than 9,500 time points. All studies measured estradiol and progesterone and had at least one independent indicator of cycle phase (day in cycle relative to the luteinising hormone surge or a menstrual onset). Seven studies collected saliva; one study collected serum. In serum, all non-steroid cycle phase measures strongly predicted steroids in the expected manner. By contrast, salivary immunoassays of estradiol were only weakly predictable from cycle phase and showed an upward bias compared to expectations from serum. For salivary immunoassays of progesterone, predictability from cycle phase was more mixed, but two widely used assays performed poorly. Imputing average serum steroid levels from cycle phase may yield more valid values than several widely used salivary immunoassays. Tandem mass spectrometry may provide a valid alternative to widely used immunoassays and could be combined with imputation.
Article
Background: Efficient and safe embryo vitrification techniques have contributed to a marked worldwide increase in the use of elective frozen embryo transfer (FET). Pinpointing the day of ovulation, more commonly by documentation of the LH surge and less commonly by ultrasonography, is crucial for timing of FET in a true natural cycle (t-NC) to maximize the reproductive outcome. Objective and rationale: The definition of the onset of the LH surge should be standardized in t-NC FET cycles; however, a clear definition is lacking in the available literature. The first search question concerns the definition of the onset of the LH surge in a natural cycle. The second search question relates to the duration between the onset of the LH surge and ovulation. Search methods: We searched PubMed, Web of Science and Cochrane Library databases for two search questions from inception until 31 August 2021. 'Luteinizing hormone'[MeSH] OR 'LH' AND 'surge' terms were used to identify eligible articles to answer the first question, whereas 'Luteinizing hormone'[MeSH] OR 'LH' AND 'surge' OR 'rise' AND 'ovulation'[MeSH] OR 'follicular rupture' OR 'follicular collapse' were the terms used regarding the second question. The included publications were all written in the English language, conducted in women of reproductive age with regular ovulatory cycles and in whom serial serum or urine LH measurement was performed. For the quality and risk of bias assessment of the included studies, the Strengthening the Reporting of Observational Studies in Epidemiology and modified Newcastle Ottawa Scale were used. Outcomes: A total of 10 and 8 studies were included for search Questions 1 and 2, respectively. Over the years, through different studies and set-ups, testing in either serum or urine, different definitions for the onset of the LH surge have been developed without a consensus. An increase in LH level varying from 1.8- to 6-fold above the baseline LH level was used in seven studies and an increase of at least two or three standard deviations above the mean of the preceding LH measurements was used in two studies. An LH level exceeding the 30% of the amplitude (peak-baseline LH level) of the LH surge was defined as the onset day by one study. A marked inter-personal variation in the time interval between the onset of the LH surge and ovulation was seen, ranging from 22 to 56 h. When meta-analysis was performed, the mean duration in hours between the onset of the LH surge and ovulation was 33.91 (95% CI = 30.79-37.03: six studies, 187 cycles). Wider implications: The definition of the onset of the LH surge should be precisely defined in future well-designed studies employing state-of-art laboratory and ultrasonographic equipment. The window of implantation in a natural cycle is still a black box, and future research is warranted to delineate the optimal interval to time the embryo transfer in t-NC FET cycles. Randomized controlled trials employing different precise endocrine and/or ultrasonographic criteria for timing of FET in a t-NC are urgently required.
Preprint
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STUDY QUESTION Can the accuracy of timing of luteal phase endometrial biopsies based on urinary ovulation testing be improved by measuring the expression of a small number of genes and a continuous, non-categorical modelling approach? SUMMARY ANSWER Measuring the expression levels of six genes (IL2RB, IGFBP1, CXCL14, DPP4, GPX3, and SLC15A2) is sufficient to obtain substantially more accurate timing estimates and assess the reliability of timing estimates for each sample. WHAT IS KNOWN ALREADY Commercially available endometrial timing approaches based on gene expression require much larger gene sets and use a categorical approach that classifies samples as pre-receptive, receptive, or post-receptive. STUDY DESIGN, SIZE, DURATION Gene expression was measured by RT-qPCR in 260 endometrial biopsies obtained 4 to 12 days after a self-reported positive home ovulation test. A further 36 endometrial samples were profiled by RT-qPCR as well as RNA-sequencing. PARTICIPANTS/MATERIALS, SETTING, METHODS A computational procedure, named 'EndoTime', was established that models the temporal profile of each gene and estimates the timing of each sample. Iterating these steps, temporal profiles are gradually refined as sample timings are being updated, and confidence in timing estimates is increased. After convergence, the method reports updated timing estimates for each sample while preserving the overall distribution of time points. MAIN RESULTS AND THE ROLE OF CHANCE The Wilcoxon Rank Sum Test was used to confirm that ordering samples by EndoTime estimates yields sharper temporal expression profiles for held-out genes (not used when determining sample timings) than ordering the same expression values by patient-reported times (GPX3: p < 0.005; CXCL14: p < 2.7e-6; DPP4: p < 3.7e-13). Pearson correlation between EndoTime estimates for the same sample set but based on RT-qPCR or RNA-sequencing data showed high degree of congruency between the two (p = 8.6e-10, R2 = 0.687). LIMITATIONS, REASONS FOR CAUTION Timing estimates are predominantly informed by glandular gene expression and will only represent the temporal state of other endometrial cell types if in synchrony with the epithelium. Methods that estimate the day of ovulation are still required as these data are essential inputs in our method. Our approach - in its current iteration - performs batch correction such that larger sample batches impart greater accuracy to timing estimations. In theory, our method requires endometrial samples obtained at different days in the luteal phase. In practice, however, this is not a concern as timings based on urinary ovulation testing are associated with a sufficient level of noise to ensure that a variety of time points will be sampled. WIDER IMPLICATIONS OF THE FINDINGS Our method is the first to assay the temporal state of luteal-phase endometrial samples on a continuous domain. It is freely available with fully shared data and open source software. EndoTime enables accurate temporal profiling of any gene in luteal endometrial samples for a wide range of research applications and, potentially, clinical use.
Article
Background Non-invasive self-testing using an objective chemical method to detect ovulation is valuable for women planning conception, practising contraception or undergoing infertility investigations or treatment. Methods Based on luteal phase secretion of progesterone (P4) and excretion of its major metabolite, pregnanediol glucuronide (PDG), we developed a novel direct liquid chromatography-mass spectrometry (LCMS) method to measure PDG and other steroid glucuronides in urine and in dried urine spots (DUS) without deconjugation or derivatization. Urine PDG by LCMS and immunoassay (P3G) and P4 by immunoassay with and without adjustment for creatinine were evaluated in daily first void urine samples from 10 women through a single menstrual cycle in which ovulation was confirmed by serial transvaginal ultrasound. Results Urine PDG with and without creatinine adjustment was stable during the follicular phase with the expected striking rise in the luteal phase peaking at 5 days after ovulation. Using a single spot urine sample (100 µL) or a DUS (<20 µL urine) and an optimal threshold to distinguish pre- from post-ovulatory samples, in ROC analysis urine PDG adjusted for creatinine accurately identified ovulation in 92% of samples was comparable with P3G immunoassay and superior to urine P4 with or without adjustment for creatinine. Extending the analysis to two or three consecutive daily samples reduced the false negative rate from 8% to 2.6% for two and 1.9% for three urine samples. Conclusions This method holds promise as a non-invasive self-test method for women to determine by an objective chemical method their ovulatory status.
Article
Full-text available
The gonadotropins are a family of closely related heterodimeric glycoprotein hormones homologous in structure to disulfide-knot growth factors. Metabolic proteolytic processing in vivo of this disulfide cross-linked region results in urinary excretion of a residual highly stable core structure. The primary structure of the pituitary form of the hLH core was reported earlier, but it has proved difficult to isolate the urinary core, although antibodies to the pituitary core demonstrated its presence. By conventional and immunoaffinity methods, the urinary core has been isolated and its structure determined by both chemical and mass spectrometric methods. The urinary hLH core is the same as the pituitary-extracted hLH core, 6‐40 disulfide bridged to 55‐93, except that the pituitary core is more heterogeneous containing also 49‐93. These findings imply a dual origin of urinary cores, both directly from a secreting tissue and by kidney processing of circulating hormone. We also found that pregnant chimpanzees excrete a CG core with a primary structure identical to that of the human CG core of pregnancy. In conclusion, gonadotropin core generation and urinary excretion of nearly identical gonadotropin metabolites is common among primates. Although possible biological functions of these core fragments remain unproven, they have diagnostic utility because of their stability and abundance.
Article
Full-text available
Purpose: Difficult clinical signs such as confusing cervical mucus or erratic basal body temperature can make the use of fertility awareness methods (FAMs) difficult in some cases. The goal of this study was to assess the feasibility of using a cheap urinary luteinizing hormone (LH)-surge identification kit as an adjunct to identify the infertile phase after ovulation when facing these scenarios. The study used a block-allocation, crossover, 2-arm methodology (LH kit/FAM vs FAM only). Comparison of the 2 arms was done with regard to the accuracy of identification (yes/no) of the luteal phase in each cycle as confirmed by serum progesterone concentrations. We recruited 23 Canadian women currently using FAM, aged 18 to 48 years, who have had menstrual cycles 25 to 35 days long for the past 3 months and perceive themselves to have difficulty with identifying the infertile phase after ovulation. LH kits identified 100% of the luteal phases, whereas FAM indentified 87% (statistically significant). In those identified cycles, LH kits provided a mean of 10.3 days of infertility, and FAM only provided 10 days of infertility (not statistically significant). Among this population, LH kits may offer an adjunct for women who may wish to have an additional double-check. However, there are still clinical circumstances when even an LH kit does not provide confirmation. More research in this area is encouraged.
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We examined the association between lifestyle factors and menstrual cycle characteristics among nulliparous Danish women aged 18-40 years who were participating in an Internet-based prospective cohort study of pregnancy planners. We used cross-sectional data collected at baseline to assess the association of age, body mass index (BMI), physical activity, alcohol and caffeine consumption, and smoking with the prevalence of irregular cycles, short (≤25 days) and long (≥33 days) cycles, and duration and amount of menstrual flow. We used log-binomial and multinomial logistic regression to estimate prevalence ratios and 95% confidence intervals. Low physical activity and heavy alcohol consumption were associated with an increased prevalence of irregular periods. High BMI, smoking, and caffeine and alcohol consumption were related to an increased prevalence of short menstrual cycles and heavy menstrual bleeding. Women in their mid-to-late thirties had shorter and lighter menstrual flow, but a lower prevalence of irregular cycles, compared with women 18-25 years of age. In this study, increased age, high BMI, and sedentary behavior were associated with menstrual-pattern irregularities. These factors may influence the balance and level of endogenous hormones conducive to optimal menstrual function.
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The regeneration of the natural menstrual cycle after discontinuing oral contraceptives (OC) is an important matter for many women. There are only few long-term observations on this subject. In a prospectively collected cycle database on the use of natural family planning in Germany, 175 women have been observed for 3048 cycles immediately after having discontinued oral contraceptives (post-pill group). They have been compared to a control group of 284 women observed for 6251 cycles, who had never taken oral contraceptives. Both groups were comparable in age and sociodemographic structure. 51 % of all first cycles after discontinuing OCs were normal. However, for the total post-pill group the cycle length was significantly prolonged up to the 9 th cycle. Significantly more luteal phases were insufficient post-pill. Major cycle disturbances (cycle length > 35 days, luteal phase of less than 10 days of elevated basal body temperature or anovulatory cycles) were significantly more frequent in the post-pill group up to the 7th cycle. 6 % of the women had a post-pill amenorrhea of 3-11 months. Therapeutical consequences: Cycle disturbances after discontinuing OCs were reversible but the time of regeneration took up to 9 months (significant) or even longer (not significant). These results will help to counsel couples who wish to conceive after discontinuing OCs or who want to continue contraception with alternative methods. The post-pill amenorrhea is reversible as well and therefore mostly should not be treated, also because the hormonal treatment may cause amenorrhea again.
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Objective: To describe the LH surge variants in ovulating women and analyze their relationship with the day of ovulation and other hormone levels. Design: Secondary analysis of a prospective cohort observational study. Setting: Eight natural family planning clinics. Subjects: Normally fertile women (n = 107) over 283 cycles. Intervention(s): Women collected daily first morning urine, charted basal body temperature and cervical mucus discharge, and underwent serial ovarian ultrasound. Main outcome measure(s): Urinary LH, FSH, estrone-3-glucuronide (E3G), pregnanediol-3α-glucuronide (PDG), and day of ovulation by ultrasound (US-DO). Result(s): Individual LH surges were extremely variable in configuration, amplitude, and duration. The study also showed that LH surges marked by several peaks were associated with statistically significant smaller follicle sizes before rupture and lower LH level on the day of ovulation. LH surges lasting >3 days after ovulation were associated with a lower E3G before ovulation, a smaller corpus luteum 2 days after ovulation, and a lower PDG value during the first 4 days after ovulation. Conclusion(s): In clinical practice, LH profiles should be compared with the range of profiles observed in normally fertile cycles, not with the mean profile.
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To assess overall knowledge, attitudes, and practices related to conception and fertility among reproductive-age women in the United States. Online survey of a cross-sectional sample of 1,000 women. United States, March 2013. Women aged 18-40 years. None. Knowledge, attitudes, and practices regarding selected topics in reproductive health. Forty percent of women across all age groups expressed concerns about their ability to conceive. Yet one-third of women were unaware of adverse implications of sexually transmitted infections, obesity, or irregular menses for procreative success, and one-fifth were unaware of the effects of aging. Approximately 40% were unfamiliar with the ovulatory cycle. Overall, younger women (18-24 years) demonstrated less knowledge regarding conception, fertility, and ovulation, whereas older women tended to believe in common myths and misconceptions. Respondents in all age groups identified women's health care providers (75%) and Web sites (40%) as top sources of reproductive health-related information; however, engagement with providers on specific factors affecting fertility is sparse. Knowledge regarding ovulation, fertility, and conception is limited among this sample of reproductive-age US women. Future initiatives should prioritize improved provider engagement and accurate information dissemination in Web-based venues.
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What are the characteristics of, and how variable are, individual normal menstrual cycle profiles of excretion rates for the urinary metabolites oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG)? There is a continuum of menstrual cycle profiles that differ from standard textbook profiles but which can be understood simply in terms of growth, atresia and ovulation of ovarian follicles. Point-of-care assays with the Ovarian Monitor pre-coated assay tubes, using urine samples diluted to a constant volume per unit time, give laboratory accurate clinical data for individual menstrual cycles. Lay operators can perform the point-of-care assay system at home to achieve reliable and reproducible results, which can be used for natural family planning. This prospective study involved 62 women, with normal menstrual cycles, recruited from three centres: Palmerston North, New Zealand, Sydney, Australia and Santiago, Chile. The study lasted 3 years. Women collected daily urine samples and determined their E1G and PdG rates with a pre-coated enzyme assay system known as the Ovarian Monitor. For two cycles, the assays were repeated in a study centre and the results were averaged to give 113 individual menstrual cycles for analysis. The cycles were displayed individually in a proprietary database program. The individual normal hormonal profiles were more complex than the classic composite curves for 40% of the cycles. Of 113 ostensibly normal cycles, only 91 were potentially fertile and 22 had some luteal phase defect. The oestrone glucuronide and PdG excretion rates were reliable and informative in the non-invasive elucidation of ovulation and ovarian function for both simple and complex profiles. Daily monitoring revealed the variability of normal menstrual cycle profiles. The LH peaks were variable and ambiguous markers for ovulation. The study consisted of cycles only from women with regular cycles of 20-40 days duration. All the women were intending to avoid a pregnancy during the study thus the limits of the fertile window were not tested. The principles established in this study should apply to cycles of any length. All peaks in oestrone glucuronide excretion should be tested by concurrent measurements of PdG, which gives a positive indication of the fate of the follicle it represents. The Ovarian Monitor provides a useful addition for practitioners of natural family planning. Financial support for this study was obtained from the UNDP/UNFPA/World Bank/WHO Special Programme of Research, Development and Research Training in Human Reproduction (HRP). D.G.C. is currently employed by and holds stock in Manawatu Diagnostics Ltd, a company in the development phase of a potentially competing product. The remaining authors have nothing to declare.