Title: C-reactive protein across the menstrual cycle
Authors and institutions:
Katherine Wander1
Eleanor Brindle2
Kathleen A. O’Connor1,2
1
Department of Anthropology, University of Washington, Seattle, WA 98195
2
Center for Studies in Demography and Ecology, University of Washington, Seattle, WA 98195
Abbreviated title: CRP across the menstrual cycle
Key words: C-reactive protein, estrogen, progesterone, inflammation, biomarker
Word count: 3678
Corresponding author*: Katherine Wander
Department of Anthropology
Box 353100
University of Washington
Seattle, Washington 98195
(206) 616-9369 (phone)
(206) 543-3295 (fax)
kwander@u.washington.edu
Support: National Science Foundation Graduate Research Fellowship, National Institute of
Child Health and Human Development grant (R24D042828)
*to whom reprint requests should be addressed
1
Abstract
Context: C-reactive protein (CRP) is a widely-used, sensitive biomarker of inflammation.
Studies conducted among users of exogenous hormones suggest that estrogen increases CRP,
while progesterone decreases CRP. Examinations of CRP in cycling women suggest the opposite:
CRP has a negative relationship with endogenous estrogen and a positive relationship with
endogenous progesterone.
Objective: To evaluate the effect of menstrual cycle-related hormone changes and events
(menstruation and ovulation) on CRP.
Design: Urine and blood samples from twelve days during the menstrual cycle were assayed for
CRP, progesterone, estrogen, and follicle stimulating hormone. Ovulation day was identified
using hormone levels. Presence or absence of menses was reported by subjects.
Participants: Collections were made across one or two cycles from eight normally-cycling,
non-contracepting participants.
Main Outcome Measures: Relationships between CRP and predictors (which, based on
literature review, included estrogen, progesterone, follicle stimulating hormone, menses, and
ovulation) were tested using random-effects linear regression.
Results: All cycles were ovulatory; day of ovulation was identified for nine cycles. A ten-fold
increase in progesterone was associated with a 23% increase in CRP (p = .01), a ten-fold increase
in estrogen was associated with a 29% decrease in CRP (p = .05), and menses was associated
with a 17% increase in CRP (p = .18); no association between ovulation or FSH and CRP was
found.
2
Conclusions: Endogenous estrogen is associated with decreases in CRP; endogenous
progesterone is associated with increases in CRP. Hormone changes across the menstrual cycle
should be controlled for in future studies evaluating CRP.
3
Introduction
C-reactive protein (CRP) plays a role in the acute phase response, characterized by
inflammation in response to injury or infection. CRP concentrations are used as a reliable
indicator of ongoing infection. CRP acts to opsonize bacteria and damaged host cells and
activates the complement cascade; upon injury or infection, CRP levels increase up to 10,000fold. In the absence of infection, CRP is used as a biomarker of baseline inflammation. CRP is
uniquely responsive and sensitive, and can be seen as a direct indication of inflammatory stimuli
(for recent review, see 1). Elevations in baseline CRP are associated with increased risk of
cardiovascular disease (2) and diabetes (3).
Individuals’ CRP measures increase dramatically during bacterial infection, and less
dramatically during viral infection (4). Absent infection, baseline CRP measures are moderately
stable over time (5). Weight loss is associated with declines in baseline CRP (6). There is no
systematic diurnal (7) or seasonal (8) variation in CRP within individuals. Between individuals,
CRP concentrations vary independently with many attributes. Among adults, CRP is positively
associated with age (4), females have higher CRP than males (4, 9), and CRP is negatively
associated with birthweight (10). CRP is negatively associated with high-density lipoprotein
cholesterol (4), decreases with increasing measures of physical fitness (11), increases with body
mass index (12), and is higher among smokers than nonsmokers (4).
Oral contraceptive (OC) use (13, 14) and hormone replacement therapy (HRT) (14, 15)
consistently elevate CRP, whether the preparation includes progesterone and estrogen or
estrogen alone. Estrogen administration is also associated with increases in CRP among men
being treated for prostate cancer (16). Such studies repeatedly demonstrate that exogenous
estrogen can increase CRP. Dose and delivery method influence exogenous estrogen’s effect on
4
CRP: one study found significant increases in CRP among women taking a higher estrogen HRT
preparation and significant decreases among women taking a lower estrogen preparation (17);
transdermally-administered HRT shows no effect on CRP (18, 19).
Comparisons of different HRT preparations suggest that exogenous progesterone may be
anti-inflammatory (20, 21, but see 22). A pro-inflammatory effect of exogenous progesterone
administration has been reported in men (23). The use of progesterones of different types
complicates these studies, as progestational agents differ in receptor affinity and glucocorticoid
effects (24). Combination estrogen/progesterone HRT preparations have been found to have
opposite effects on CRP depending on the type of progesterone used, with the HRT preparation
which included the “pure progestational” (so named because it interacts only with progesterone
receptors and has no glucocorticoid effects) Nomegestrol acetate associated with a decrease in
CRP, despite the inclusion of estrogen (24).
Although supported by far fewer studies, endogenous hormones appear to have opposite
effects on CRP than suggested by the above studies. Jilma and colleagues (25) examined
measures from 18 women taken in the follicular phase, at mid-cycle, and in the luteal phase of
one menstrual cycle, and found a significant (univariate) association between individuals’
relative increase in progesterone and CRP from the follicular phase to mid-cycle (r = .60, p
= .01), as well as from the follicular phase to the luteal phase (r = .71, p = .001). Blum and
colleagues (26) examined 15 measures from 15 women across one menstrual cycle. In random
effects maximum likelihood regression, increasing estrogen was associated with decreasing CRP
(β = -.23, p < .001; univariate) such that a ten-fold increase in estrogen was associated with a
41% decrease in CRP. The effect of progesterone on CRP in this study was not significant (p
= .15). Although subjects were sampled daily around ovulation, a potential effect of ovulation
5
per se on CRP concentration was not discussed. CRP concentrations in this study were highest
during menstruation; independent effects of estrogen and menses were not tested.
The results of these studies are inconsistent with the numerous studies examining the effects
of exogenous hormone administration on CRP: orally-administered estrogen at most doses is
associated with elevations in CRP (13, 14, 15, 16), endogenous estrogen seems to be associated
with decreases in CRP (26); exogenous progesterone may be associated with decreases in CRP
(20, 21, 24), endogenous progesterone seems to be associated with increases in CRP (25).
Neither study examining the effects of endogenous hormones reports any evaluation of
confounding between the effects of estrogen and progesterone, despite the fact that changes in
these hormones regularly co-occur across the menstrual cycle. Further, these studies do not
evaluate potential independent effects of menses or ovulation, despite good reason to expect
these events to substantially affect inflammation. Ovulation and menstruation have both been
described as “inflammatory” events. Inflammatory mediators and leukocytes play important
roles in folliculogenesis and follicular rupture. Similarly, prostaglandins and leukocytes play a
direct role in accomplishing menstruation (for recent reviews, see 27, 28). As such, an effect of
these menstrual cycle events on circulating concentrations of CRP bears exploration. Further,
because elevations in follicle stimulating hormone (FSH) are typically associated with both
menstruation and ovulation (29), it is possible that changes in this hormone may explain any
association between those cycle events and CRP; this merits investigation.
Thus, this pilot study was undertaken to verify the unexpected effects of endogenous
reproductive steroids on CRP, to evaluate potential effects of menses, ovulation, and FSH on
CRP, and to evaluate potential confounding and interaction in these relationships.
6
Methods
Participants and specimen collection
Three female participants collected urine and capillary dried blood spots (DBS) for two
months (24 collections per subject), and five made urine and DBS collections for one month (12
collections per subject). Participants were excluded from the study if they were taking any
exogenous hormones or statins, or if they were taking more than occasional anti-inflammatory
medication. Paired DBS and urine collections were made every Monday, Wednesday and Friday
during a subject’s collection period. Two subjects made additional daily urine collections (12
DBS and 28 urine collections per subject). Procedures were approved by the Institutional Review
Board of the University of Washington.
DBS were collected by finger stick with a sterile lancet. Spots of blood were allowed to fall
freely from the subject’s finger onto filter paper (Schleicher and Schuell #903 Specimen
Collection Paper). Filter papers were allowed to dry at room temperature in open air for one to
three days, then were frozen with desiccant until assay.
Within approximately one hour of DBS collection, urine was collected in a plastic vial and
refrigerated. At intervals of approximately two weeks, urine specific gravity measures were
taken and a 600 µL aliquot was made and refrigerated until assay.
To address the possibility that DBS collection procedures were invasive enough to evoke
some measure of inflammatory response, subjects’ start days were assigned irrespective of cycle
day, so that no collection day systematically co-occurred with any cycle day. Further, collections
were not made over the weekend, providing a longer interval for clearance of any collection-
related increases in CRP than during the week and allowing us to test for regularly belowaverage CRP on Mondays.
Assays
DBS were assayed for CRP using an enzyme immunoassay described elsewhere (30). DBS
measures using this assay correlate highly with serum measures of CRP (r = .96). The lower
limit of detection for this assay is .028 mg/L (1.33 nmol/L). The intra-assay coefficient of
variation (CV) at high concentration is 6.4% and low concentration is 5.1%; the inter-assay CV
at high concentration is 6.9% and at low concentration is 9.5%.
Urine samples were assayed for estrone glucuronide (E1G) and pregnanediol 3-glucuronide
(PDG), the major urinary metabolites of estradiol (E2) and progesterone (P4), respectively, using
methods described elsewhere (31, 32). Urinary steroids measured with these assays correlate
highly with serum measures of E2 and P4 (r = .95 and .98, respectively). The E1G lower limit of
detection is 1,452.4 pg/mL (3.1 nmol/L); the PDG assay lower limit of detection is 10.4 ng/mL
(21 nmol/L). High and low concentration intra-assay CVs for the PDG assay are 9.2% and 7.1%;
high and low inter-assay CVs are 10% and 7.1%. High and low concentration intra-assay CV’s
for the E1G assay are 3.6% and 12.2%; high and low inter-assay CVs are 3.2% and 13.7%. Urine
samples were assayed for FSH using an IEMA specific to total (free and intact) beta FSH (33).
Urinary βFSH measured with this assay correlates well with serum intact FSH measures (r =
.86). The FSH assay lower limit of detection is .143 ng/mL (6.8 pmol/L); high and low intraassay CVs are 2.2% and 4.1%; high and low inter-assay CVs 4.3% and 3.7%.
All specimens, calibrators and controls were run in duplicate, and hormone concentrations
were estimated from optical density using a four-parameter logistic model in BIOLINX 2.0
Software (Dynatech Laboratories, Inc., Chantilly, VA, USA). All urinary hormone values were
adjusted by specimen specific gravity (34); E1G results were further corrected for slight assay
non-parallelism using a statistical correction model (31).
Identification of ovulation
Cycles were identified as ovulatory or anovulatory and day of ovulation was identified using
methods developed for intermittent sampling and described elsewhere (29), which rely on
changes in steroid hormones. This method (modified Baird) identifies ovulation day to within
two days of the true ovulation day for 93% of cycles. When a non-collection day was identified
as the day of ovulation, the following collection was defined as ovulation day for these analyses.
Sampling in this study provided slightly fewer samples than that used to develop these methods,
so the decision rule was relaxed regarding the change in the ratio of steroid hormones necessary
to identify ovulation. The protocol calls for a decrease of 60% across a five-day window. Since
cycles clearly identified as ovulatory did not consistently demonstrate this magnitude decrease,
but did demonstrate a 50% decrease, a 50% decrease was accepted in identifying ovulation day
in these analyses.
Statistical analysis
Data were analyzed using StataSE 9.0 (Statacorp, College Station, TX). Statistical
significance was defined as p ≤ .05; suggestive results were defined as .05 < p ≤ .20;
confounding was defined as a change > 10% in the coefficient of the predictor of interest with
the inclusion of a potential confounder. Relationships between CRP and other variables were
analyzed using random-effects linear regression, wherein a random intercept term was estimated
for each participant to account for differences between individuals. Per convention, infectionrelated increases in CRP were defined as CRP > 10 mg/L (476 mmol/L) and were excluded from
analyses. Further, analyses were carried out both with and without CRP > 5 mg/L (238 mmol/L),
a more conservative cut-off, as an infectious cause for this magnitude elevation is possible.
Because previous work (17) demonstrates opposite effects of low and high dose estrogen on
CRP, we chose to test the hypothesis that the effects of estrogen on CRP may change at high
concentrations. To do this, analyses were carried out both with and without points above the 90th
percentile E1G.
Results
Data from eleven menstrual cycles of eight female subjects were used to assess menstrual
cycle-related changes in CRP. Values for E1G and PDG were available for a total of 126 data
points; values for FSH were available for 124 data points. The presence or absence of menses
was reported by participants for 126 data points; menses was reported as present for 37 data
points. All cycles were ovulatory; day of ovulation was identifiable for nine cycles. Continuous
variables (CRP, PDG, E1G, FSH) were found to have skewed distributions and were therefore
transformed using a natural logarithm; within individuals, the transformed CRP values appear to
be normally distributed. No subjects reported using more than occasional anti-inflammatory
medication. The majority of anti-inflammatories reported were ibuprofen and acetaminophen.
Only on one occasion did one subject report using aspirin; the associated collection was dropped
from all analyses. No CRP concentrations exceeded 10 mg/L (476 mmol/L).
Monday collections (including all collections preceded by two or more non-collection days)
were tested for systematically lower than average CRP concentrations within individuals; no
effect was found (β = .085, p = .26). Collection procedures did not artificially elevate CRP.
Confounding was apparent between all predictors of interest for which there was a suggestive
univariate effect (Table 1); only one model was ultimately used for all predictors (Table 2). All
possible two-way interaction terms from the final model were tested individually. None were
found to be significant; however, the interaction term coefficients for ln(PDG)*ln(E1G) (p = .06)
and ln(E1G)*menses (p = .18) were suggestive. Future studies with larger sample sizes should
assess interaction between these variables.
According to the model presented in Table 2, controlling for E1G and menses, a ten-fold
increase (as is typical for steroids across the cycles we observed) in PDG is associated with a
23% increase in CRP (p = .01). Controlling for PDG and menses, a ten-fold increase in E1G is
associated with a 29% decrease in CRP (p = .05). Controlling for hormone concentrations, a
suggestive increase of 17% in CRP (p = .18) is associated with the presence of menses. Rsquared values for this model were low, indicating that a small proportion of the variation
between normally cycling women in CRP is explained by cycle-related variables; however, a
significant proportion of the variation in CRP within a normally cycling woman is explained by
these variables.
The data from two subjects who made daily urine collections for one month each were used
to evaluate a potential lag in the effect of estrogen on CRP. Although a small sample, results
indicate that no such lag effect exists (data not shown); there were no differences in the
association between E1G and CRP when E1G values for the day preceding CRP collection were
substituted in the model.
No association between FSH and CRP, nor any confounding between FSH and other
predictors, was found. Thus, FSH was disregarded in further analyses. The expected positive
associations between FSH and menses (β = .311, p = .01) and FSH and ovulation (β = .679, p
= .00) were evident.
No association between ovulation and CRP (β = -.055, p = .60 when included in the model in
Table 2), nor any confounding between ovulation and the effect of steroids on CRP, was found.
Thus, ovulation was disregarded in further analyses.
No CRP values exceeded 10 mg/L (476 mmol/L); four values exceeded 5 mg/L (238
mmol/L). The final regression model was evaluated both with and without these points; their
exclusion did not substantially alter the magnitude of any coefficients; the coefficient for E1G,
however, loses significance without these data points (Table 3).
When the highest E1G values are excluded from the analysis, the negative relationship
between E1G and CRP becomes stronger, despite the reduction in sample size. The results of the
regression model excluding points with E1G above the 90th percentile [E1G ≥ 101,675.0 pg/mL
(47.63 mmol/L), 13 values] are shown in Table 4. Compared to the results in Table 2,
coefficients for PDG and menses decrease in magnitude and significance, concomitant with a
reduction in sample size; the E1G coefficient increases in magnitude and significance, such that
a ten-fold increase in E1G is associated with a 43% decrease in CRP (p = .02).
Discussion
Within individuals, CRP concentrations are clearly associated with endogenous reproductive
hormones: increases in estrogen are associated with decreases in CRP (p = .05), while increases
in progesterone are associated with increases in CRP (p = .01). Independent of hormone changes,
the presence of menses is associated with nonsignificant increases in CRP (p = .18). Substantial
confounding is apparent between these effects; this may explain the lower magnitude of the
effects reported here, compared to previous studies (25, 26).
Our finding that endogenous estrogen is associated with decreases in CRP is consistent with
previous work (26); this is in contrast to the many studies indicating that exogenous estrogen
increases CRP (13, 14, 15, 16). Investigators draw conflicting conclusions about the extent to
which changes in CRP with exogenous estrogen administration reflect an effect of estrogen on
inflammation, rather than an effect solely on liver CRP production. Some interpret the failure of
transdermally-administered HRT to demonstrate any effect on CRP (17) and the failure to find
concomitant increases in other inflammatory markers among oral HRT users (35) to suggest
estrogen ingested in large amounts has a direct, metabolic effect on liver production of CRP.
However, some of these findings may be attributable to the lower sensitivity and more stringent
sampling requirements of other inflammatory markers, compared to CRP (1). Demonstrated
increases in multiple inflammatory markers among women using OC have been interpreted by
others as elevated baseline inflammation (14). It is possible that differences between the effects
of orally- and transdermally-administered estrogen are attributable to concentration-dependent
effects of estrogen on inflammation, rather than to administration method per se. Transdermallyadministered estrogen may result in circulating estrogen levels which differ from orallyadministered estrogen, with different consequences for inflammation. Circulating E2 levels have
been found to be lower in women using transdermal HRT than in women using oral HRT (19,
36). The same is not true for transdermal contraception
(http://www.fda.gov/bbs/topics/news/2005/NEW01262.html), which may be associated with
elevated CRP (14); we have found no published data directly testing this hypothesis.
The contrast between studies focusing on endogenous estrogen, such as ours (and 26), and
those focusing on exogenous estrogen (OC and HRT) may similarly be best explained by
differences in circulating estrogen levels: estrogen levels in normally-cycling women may not
often reach levels in women using OC or HRT (37), although the opposite may be true for users
of low-dose OC (38). There is evidence to suggest that incremental increases in estrogen at low
and high concentration have opposite effects on inflammatory markers: increases in estrogen
were found to be negatively associated in vivo with CRP (17) and in vitro with monocyte
interleukin (IL)-1β and IL-6 production (39) at lower estrogen levels, and positively associated at
higher estrogen levels. Our finding that excluding points above the 90th percentile for estrogen
strengthens the effect of estrogen on CRP further supports this hypothesis.
Our observation of an anti-inflammatory effect of estrogen at most physiological levels is
consistent with other observations of estrogen’s effect on the immune system: while estrogen
increases production of B lymphocytes, as well as immunoglobulin production, it seems to
decrease monocyte cytokine production and the inflammatory activity of neutrophils and natural
killer (NK) cells (for recent review, see 40). Locally, estrogen seems to have a pro-inflammatory
effect on uterine and other reproductive tissues (41), but its effect on other tissue types is
consistently anti-inflammatory (see, for example, 42, 43, 44).
Our finding of a positive effect of progesterone on CRP is consistent with the relationship
reported by Jilma and colleagues (25), in contrast to the negative or nonexistent effect suggested
by studies of exogenous hormone administration (20, 21, 24). Our finding is difficult to reconcile
with many observations of progesterone’s effects on the immune system: while progesterone
seems to promote the chemotactic activity of neutrophils and increase production of some
inflammatory mediators (IL-6 and leukemia inhibiting factor, LIF) by monocytes (40), an overall
anti-inflammatory effect is generally attributed to progesterone, which includes decreasing NK
cell activity and macrophage tumor necrosis factor (TNF) α and nitric oxide synthase (NOS)
production, as well as inhibiting T-cell development in the thymus and T-cell activity (for recent
review, see 45). Our results suggest that increases in progesterone typical of normally cycling
women have an overall inflammatory effect. Future work should focus on reconciling the
observed effects of progesterone on inflammatory cells with its overall effect on systemic
inflammation.
We report that menstruation is associated with a suggestive increase in CRP; this is
consistent with Blum and colleagues’ (26) observation of highest CRP concentrations during
menstruation. Due to small sample size, our analysis lacks the power to reject alternative
hypotheses at the .05 α-level; thus we interpret this result as a suggestive pro-inflammatory effect
of menstruation. Studies with larger samples should anticipate a pro-inflammatory effect of
menses, consistent with the non-specific immune system’s role in initiating menstruation (28).
Despite the involvement of inflammatory cells and mediators in follicular rupture, ovulation
does not appear to affect systemic inflammation. The possibility exists that our methods of
identifying ovulation, sampling frequency, or power were inadequate to detect such an effect, but
the small magnitude and high p-value of the coefficient that results from ovulation’s inclusion in
our model do not suggest that this is the case.
Our results indicate that studies using CRP as a biomarker should control for changes in
endogenous hormone levels when sampling normally-cycling women. More generally, we
suggest that when study samples include individuals who may be undergoing any transition in
their reproductive life course (for example, adolescents, mothers returning to menses postpartum,
or perimenopausal women), bias in hormone levels may confound results regarding baseline
CRP. For example, variation in age at menarche alone could result in systematic variation in
CRP among an adolescent female sample. To understand how other factors affect CRP among
adolescents, menstrual status or age at menarche should therefore be controlled.
In summary, changes in endogenous estrogen and progesterone within the menstrual cycle
are significantly and independently associated with changes in CRP: progesterone increases
CRP and estrogen decreases CRP; menstruation may increase CRP. Overall, these changes are
consistent with observed interactions between the reproductive and immune systems. The
patterns we observed are not consistent with the effects of exogenously administered hormones;
this may be attributable in part to concentration-dependent effects of estrogen on CRP
production. Our results are consistent with those of others examining endogenous reproductive
steroid levels (25, 26), and our analysis expands on them, providing a single model of the
independent effects of endogenous hormones and menstrual cycle events on CRP. These results
suggest that studies using CRP as a biomarker among reproductive-age women should account
for endogenous hormonal changes and menstruation in sampling and analysis.
Acknowledgments
This material is based upon work supported under a National Science Foundation Graduate
Research Fellowship (KW). This work was supported by a NICHD grant (R24D042828) to the
Center for Studies in Demography and Ecology at the University of Washington. We thank
Jennifer Aranda, Masako Fujita, Steven Goodreau, Anita Rocha, Bettina Shell-Duncan, and Jane
Shofer for their help in the preparation of this manuscript.
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Tables
Table 1: Evaluation of confounding
Univariate associations with ln(CRP) (β, p-value):
ln(PDG)
ln(E1G )
Menses
.030, .33
-.093, .16
.179, .10
Bivariate confounders:
ln(PDG)
-----
-.191, .01
.214, .06
ln(E1G)
.088, .01
-----
.154, .18
Menses
.052, .07
-.045, .49
-----
FSH
.027, .40
-.096, .15
.169, .14
Ovulation
.032, .29
-.080, .24
.169, .13
Results of random-effects linear regression show substantial confounding between these
three predictors of interest. CRP = C-reactive protein; PDG = pregnanediol 3 glucuronide,
reflects serum progesterone levels; E1G = estrone glucuronide, reflects serum estradiol
levels
The top row lists the coefficients and p-values for univariate associations between a
variable and CRP, the lower rows show how those coefficients and p-values change with
the inclusion of each potential confounder (listed to the left). Thus, for example, the
coefficient for E1G increases in magnitude, from -.093 to -.191, and significance, from p
= .16 to p = .01, with the inclusion of PDG in the model.
Table 2: Relationship between CRP and menstrual cycle variables
Coefficient
P-value
95% Confidence interval
ln(PDG)
.090
.01
.023, .157
ln(E1G)
-.148
.05
-.297, -.000
Menses
.156
.18
-.074, .387
Outcome = ln(CRP)
R2 within = .0754, R2 between = .0005, R2 overall = .0053
All continuous variables were natural log transformed; analyses were conducted with
random effects linear regression. CRP = C-reactive protein; PDG = pregnanediol 3
glucuronide, reflects serum progesterone levels; E1G = estrone glucuronide, reflects
serum estradiol levels
Table 3: Effect of excluding elevated CRP measures
Coefficient
P-value
95% Confidence interval
ln(PDG)
.081
.01
.017, .146
ln(E1G)
-.107
.12
-.241, .027
Menses
.182
.11
-.037, .401
Outcome = ln(CRP)
R2 within = .0867, R2 between = .0368, R2 overall = .0001
After excluding all points for which CRP ≥ 5 mg/L, all continuous variables were natural
log transformed and analyzed with random effects linear regression. CRP = C-reactive
protein; PDG = pregnanediol 3 glucuronide, reflects serum progesterone levels; E1G =
estrone glucuronide, reflects serum estradiol levels
Table 4: Effect of excluding high estrogen values
Coefficient
P-value
95% Confidence interval
ln(PDG)
.088
.04
.003, .173
ln(E1G)
-.242
.02
-.441, -.041
Menses
.099
.44
-.151, .349
Outcome = ln(CRP)
R2 within = .0793, R2 between = .0095, R2 overall = .0154
After excluding points for which E1G ≥ 101,675.0 pg/mL, all continuous variables were
natural log transformed and analyzed with random effects linear regression. CRP = Creactive protein; PDG = pregnanediol 3 glucuronide, reflects serum progesterone levels;
E1G = estrone glucuronide, reflects serum estradiol levels