Human Reproduction Vol.21, No.1 pp. 80–89, 2006
Advance Access publication September 30, 2005. Combined lifestyle modification and metformin in obese patients with polycystic ovary syndrome. A randomized, placebo-controlled, double-blind multicentre study Thomas Tang1, Julie Glanville1, Catherine J.Hayden1, Davinia White2, Julian H.Barth3 and Adam H.Balen1,4
1Department of Reproductive Medicine, Clarendon Wing, The General Infirmary, Leeds LS2 9NS, UK 2Department of Reproductive Medicine, St Mary’s Hospital, London W2 and 3Department of Clinical Biochemistry, The General Infirmary, Leeds LS1 3EX, UK
4To whom correspondence should be addressed. E-mail: Adam.balen@leedsth.nhs.uk
BACKGROUND: It has been reported that women with polycystic ovary syndrome (PCOS) benefit from metformin therapy. METHODS: A randomized, placebo-controlled, double-blind study of obese (body mass index >30 kg/m2), oligo-/amenorrhoeic women with PCOS. Metformin (850 mg) twice daily was compared with placebo over 6 months. All received the same advice from a dietitian. The primary outcome measures were: (i) change in menstrual cycle; (ii) change in arthropometric measurements; and (iii) changes in the endocrine parameters, insulin sensitivity and lipid profile. RESULTS: A total of 143 subjects was randomized [metformin (MET) = 69; placebo (PL) = 74]. Both groups showed significant improvements in menstrual frequency [median increase (MET = 1, P < 0.001; PL = 1, P < 0.001)] and weight loss [mean (kg) (MET = 2.84; P < 0.001 and PL = 1.46; P = 0.011)]. However, there were no significant dif- ferences between the groups. Logistic regression analysis was used to analyse the independent variables (metformin, percentage of weight loss, initial BMI and age) in order to predict the improvement of menses. Only the percentage weight loss correlated with an improvement in menses (regression coefficient = 0.199, P = 0.047, odds ratio = 1.126, 95% CI 1.001, 1.266). There were no significant changes in insulin sensitivity or lipid profiles in either of the groups. Those who received metformin achieved a significant reduction in waist circumference and free androgen index. CONCLUSIONS: Metformin does not improve weight loss or menstrual frequency in obese patients with PCOS. Weight loss alone through lifestyle changes improves menstrual frequency. Key words: menstrual frequency/metformin/obese/polycystic ovary syndrome/weight loss
Introduction
Pasquali et al., 2003), menstrual disorders and hyperinsulinaemia
The polycystic ovary syndrome (PCOS) is the commonest endo-
(Conway et al., 1990; Lord and Wille, 2002). Obesity corre-
crine disturbance in women (Balen and Michelmore, 2002) and
lates with an increased rate of menstrual cycle disturbance and
the commonest cause of anovulatory infertility. PCOS is a hetero-
infertility (Kiddy et al., 1990; Balen et al., 1995). Weight loss
geneous disorder with features including hyperandrogenism,
improves the endocrine profile, the menstrual cyclicity, the
menstrual irregularity and obesity (Balen et al., 1999; Rotterdam
likelihood of ovulation and of a healthy pregnancy (Pasquali
ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group,
et al., 1989; Kiddy et al., 1992; Huber-Buchholz et al., 1999).
2004). The association between insulin resistance, compensatory
Studies by Clark et al. (1995, 1998), demonstrated that weight
hyperinsulinaemia and hyperandrogenism have provided insight
loss achieved by an exercise schedule, combined with a hypo-
into the pathogenesis of PCOS (Tsilchorozidou et al., 2004). Insu-
caloric diet over a 6 month period, improved insulin sensitiv-
lin resistance occurs in both slim and overweight women with
ity, endocrine parameters, menstrual regularity, the frequency
PCOS, although there is debate on the proportion of women with
of spontaneous ovulation and the chance of pregnancy.
PCOS with reduced insulin sensitivity (Cibula et al., 2004). At
Even a modest weight loss of 2–5% of total body weight can
least 40% of women with PCOS are obese (Balen et al., 1995)
restore ovulation in overweight women with PCOS as well as
and they are more insulin resistant than weight-matched individu-
achieving a reduction of central fat and an improvement in
als with normal ovaries (Dunaif et al., 1995; Morales et al., 1996).
insulin sensitivity (Huber-Buchholz et al., 1999). Rather than
Obesity and particularly abdominal obesity as indicated by
absolute weight, it is the distribution of fat that is important
an increased waist:hip ratio is correlated with reduced fecun-
with android (central) obesity being more of a risk factor than
dity (Zaadstra et al., 1993; Kirchengast and Huber, 2004;
gynaecoid obesity (Despres et al., 2001; Lord and Wille,
The Author 2005. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org Metformin in obese PCOS patients
2002). Visceral adipose tissue is more metabolically active
PCOS was defined as the presence of polycystic ovaries on trans-
than subcutaneous fat and the amount of visceral fat correlates
vaginal scan, >10 cysts, 2–8 mm in diameter, usually combined with
with insulin resistance and hyperinsulinaemia. Weight reduc-
increased ovarian volume >10 cm3, and an echo-dense stroma (after
tion of 5–10% may result in ∼30% loss of visceral adipose tis-
the transabdominal ultrasound criteria of Adams et al., 1985), together
sue (Despres et al., 2001) and this may explain why a modest
with either oligomenorrhoea or amenorrhoea. Many patients also hadclinical or biochemical hyperandrogenism, although this was not an
weight loss can significantly improve metabolic and reproduc-
entry criterion for the study. All patients had a baseline androgen pro-
tive function. Waist circumference has been shown to correlate
file, including measurement of testosterone and androstenedione. If
better with visceral fat than waist:hip ratio (WHR) (Lord and
either were significantly elevated, additional tests were performed to
Wille, 2002), and a waist circumference in women >88 cm is
exclude hypercortisolism and congenital adrenal hyperplasia (CAH)
indicative of an increased metabolic risk (Despres et al., 2001).
(full steroid profile, 24 h urinary cortisol and adrenocorticotrophin
Lifestyle modification is a key component for the improve-
hormone stimulation test). When the study was devised the Rotterdam
ment of reproductive function for overweight, anovulatory
consensus definitions of PCOS (2004) and of the polycystic ovary
women with PCOS (Norman et al., 2002, 2004; Pasquali et al.,
(Balen et al., 2003) had not been defined, although all of our patients
2003). Weight loss should therefore be encouraged prior to
would have been classified as having PCOS by those criteria.
ovulation induction treatments, since these are less effective
Pretreatment inclusion criteria also included the presence at least
when the body mass index (BMI) is >28–30 kg/m2 (Hamilton-
one patent Fallopian tube and a normal semen analysis from the malepartner. All participants had normal serum prolactin concentrations,
Fairley et al., 1992). Monitoring treatment is also harder in the
thyroid, renal and liver function and haematological indices, including
obese as visualization of the ovaries is more difficult which
raises the risk of multiple ovulation and multiple pregnancy.
Exclusion criteria included concurrent hormone therapy within the
Furthermore, pregnancy carries greater risks in the obese, for
previous 6 weeks, any chronic disease that could interfere with the
example: miscarriage, gestational diabetes, hypertension and
absorption, distribution, metabolism or excretion of metformin, and
problems with delivery (Gjonnaess et al., 1989; Sebire et al.,
renal or liver disease. Patients with significant systemic disease or dia-
2001; Cedergren, 2004; Linné, 2004).
betes (Type 1 or 2) were excluded. Patients with irregular menstrual
It is logical to assume that therapy that achieves a fall in
bleeding were thoroughly assessed to exclude pathology of the genital
serum insulin concentrations should improve the symptoms of
tract other than PCOS and a negative pregnancy test was a prerequi-
PCOS (Norman et al., 2004). The biguanide metformin both
inhibits the production of hepatic glucose, thereby decreasing
Protocol
insulin secretion, and enhances insulin sensitivity at the cellularlevel (Matthaei et al., 2000). The efficacy of metformin in
A multicentre research ethics committee approval (MREC 1999/8/12)and the local research ethics committee approval of each participating
PCOS was first described by Velazquez et al. (1994) and a
centre were obtained. After obtaining written consent, a full physical
number of small, and often short duration, observational studies
examination was performed including assessment of BMI, waist and
followed which showed variable outcomes. Most of the rand-
hip circumference and blood pressure. A baseline transvaginal ultra-
omized studies have involved only a small number of partici-
sound scan was performed to assess ovarian morphology, uterine size
pants. Indeed in a systematic review by Costello and Eden
and endometrial thickness. A standardized 75 g oral glucose tolerance
(2003), nine out 12 published studies on the effects of met-
test (OGTT) was performed with measurement of fasting insulin con-
formin alone on the menstrual cycle in women with PCOS had
centration and glucose at 0 and 120 min. Baseline serum endocrinol-
a sample size of <30 women. Lord et al. (2003) published a sys-
ogy included the measurement of FSH, LH, testosterone, sex
tematic review in the Cochrane Database which concluded that
hormone-binding globulin (SHBG), total cholesterol and triglycerides.
metformin has a beneficial effect for women with PCOS, by
The subjects were randomized to receive either metformin or pla-
reducing serum insulin concentrations and thereby lowering
cebo. The randomization process was carried out by the clinical trialsoffice in the pharmacy department and blinded to patients and investi-
androgen levels and improving reproductive outcomes. Back in
gators. A block-of-four randomization technique was performed using
1997 we conceived what we anticipated to be an appropriately
random tables from Linder et al. (1970). The code was kept in the trial
powered, prospective randomized, double-blind, placebo-
office until the last patient completed the study. Placebo tablets for
controlled multicentre study to evaluate the combined effects of
metformin were identical in appearance (size and colour) to met-
lifestyle modification and metformin on obese anovulatory
formin and were supplied by Penn Pharmaceuticals Ltd (Tredegar,
women (BMI >30 kg/m2) with PCOS. The study has taken a
Gwent). One tablet (metformin 850 mg or placebo) was prescribed to
considerable time to complete and here we present our findings.
be taken 12 hourly for a period of 6 months.
Patients in each group received standardized dietary advice from a
research dietitian. Each subject was assessed by the dietitian and an
Materials and methods
individualized diet [high in carbohydrate (50%) and low in fat (10%)]
Women were recruited from infertility clinics with anovulatory PCOS
was given with the aim of a reduction in daily intake by 500 kcal. Writ-
and a BMI of >30 kg/m2, aged between 18 and 39 years inclusive and
ten information was given on PCOS and appropriate information on a
a desire to conceive. Anovulation was defined as the presence of
balanced weight-reducing diet. The patients were also encouraged to
amenorrhoea or oligomenorrhoea (cycle length >35 days) (Munster
increase daily exercise (such as walking, using stairs) by 15 min,
et al., 1993; Berek et al., 1996) and the absence of ovarian follicular
although this was not formally assessed. The participants received fur-
activity on serial ultrasound scans. The patients had not received ovu-
ther encouragement to adhere to the regime at the monthly review visits.
lation induction therapy from the fertility clinic as the usual criterion
Each participant was assessed monthly with a re-evaluation of
for any form of ovulation induction (clomiphene citrate or gonadotro-
anthropometric measurements, endocrine and biochemical parameters
pin therapy) was a BMI of <30 kg/m2.
together with an ultrasound scan and record of the patient’s menstrual
T.Tang et al.
cycle. Side-effects of the treatment and reason for any withdrawals
under steady state conditions; an alternative reference method is the
from the study were recorded. The assessment was performed by the
intravenous glucose tolerance test (IV-GTT). Both require sophisti-
same person in each centre (usually the research nurse). All nursing
cated investigation centres, are labour intensive, expensive and cannot
and medical personnel were blind to the treatment arm, with the
really be performed for large scale studies. In routine clinical practice
research pharmacy in Leeds being the only place where this informa-
an OGTT or simple ratios of fasting glucose/insulin are fairly sensi-
tion was held for the duration of the study. Compliance was assessed
tive (Moran and Norman, 2004). More accurate indices of insulin sen-
by the return of empty drug containers.
sitivity and secretion derived from fasting plasma insulin and bloodglucose concentrations are reasonable substitutes for the euglycaemic
Outcome measures
clamp and IV-GTT, these include the HOMA and QUICKI methods
The primary outcome measures were: (i) change in menstrual cycle;
(ii) change in arthropometric measurements; and (iii) changes in the
The homeostatic model assessment (HOMA) is a computer-gener-
endocrine parameters, insulin sensitivity and lipid profile. The main
ated model consisting of a series of non-linear empirical equations
secondary outcome measure was pregnancy rate.
solved numerically to predict glucose, insulin and C-peptide concen-trations in the fasting state for the assessment of pancreatic beta cell
Power calculation
function and insulin sensitivity (Matthews et al., 1985). The use ofHOMA correlates well with the euglycaemic clamp method and the
In the study by Velazquez et al. (1997a), metformin alone improved
IV-GTT but cannot be compared between different studies unless the
menstrual regularity in 21/40 (53%) of subjects. If we anticipate an
insulin assay is standardized (Bonara et al., 2000). The estimation of
overall 83% improvement with a combination of diet and metformin
the QUICKI provides a robust and reproducible estimate of insulin
(i.e. a further 30% improvement compared with metformin alone), the
sensitivity that shows excellent linear correlation with the gold stand-
standardized difference (d) would be 0.64. The chosen power in the
ard clamp estimation with similar variability and discrimination
study was 90% with a type I error of 0.05. From the power table
power (Katz et al., 2000). The relative advantages of QUICKI over
(Machin and Campbell, 1987), when d = 0.64 and the power = 0.90,
HOMA include the fact that the data derived from a single blood sam-
the projected sample size was 110, with 55 subjects in each arm of the
ple performs just as well as an average of multiple sampling, and the
study. When the study was designed the literature from which to cal-
simplicity of the mathematical model. Furthermore, therapeutic
culate power was limited, if we were to consider the more recently
changes in insulin sensitivity have been as readily demonstrated with
published Cochrane meta-analysis by Lord et al. (2003), which
this simple method as with the euglycaemic clamp (Mathur et al.,
reported an overall improvement in ovulation rates in 71/156 and
2001). A recent review on the determination of insulin sensitivity in
37/154 subjects in the metformin group and the control group respec-
PCOS has highlighted the good correlation of QUICKI with the clamp
tively with an odds ratio of 3.88 (95% CI 2.25, 6.69) versus placebo
technique (Kauffman and Castracane, 2003).
for rate of ovulation in favour of metformin. Based on these recent
Data were analysed on the basis of intention to treat. All the sub-
values, the standardized difference is 0.57 with the projected sample
jects who withdrew within the first 4 months of the study period,
size of 130. At the end of the study period, the actual recruitment
excluding those who conceived, were classified as non-responders.
This is because we wished to include only those who completed≥4 months, and preferably 6 months of the trial. For parametric data,
Biochemical assays
the assumption of normal distribution was assessed by a normal plot
All the samples were stored at −20°C and were analysed in the bio-
and the Kolmogorov–Smirnov test. The assumption of the two groups
chemistry department of the coordinating centre. The analyses were as
having the same variances was tested by using the F-test. Paired t-test
previously described (Wijeyaratne et al., 2002). Plasma glucose was
or two-sample t-test was applied as indicated. When the data did not
measured using an enzymatic colorimetric assay (Hitachi, Roche) with
meet the above assumptions, a log transformation of the data was
intra-assay coefficients of variation (CV) of 1.9% at 20.2 mmol/l and
carried out. If the transformed data was still not meeting the assump-
30% at 2.4 mmol/l. A time-resolved fluoroimmunoassay (AutoDEL-
tions, non-parametric methods, Wilcoxon signed rank test or Mann–
FIA; Perkin Elmer) was used to measure insulin and serum SHBG con-
Whitney test were applied. P < 0.05 was considered to be statistically
centrations, with plasma insulin intra-assay CV of 1.7% at 180.96
significant. The Z-test was used to analyse the two proportions with
pmol/l and 2.4% at 33.9 pmol/l and inter-assay CV of 3.5% at 180.96
pmol/l and 2.3% at 33.9 pmol/l. The serum SHBG intra-assay CV was
In the multiple linear regression analysis, the same normality test
6% at 103.36 nmol/l and 7% at 14.88 nmol/l; and the inter-assay CV
was used as in the t-test and the test for constant variance was com-
was 1% at 103.36 nmol/l and 1% at 14.88 nmol/l. Serum testosterone
puted by using the Spearman rank correlation between the absolute
was measured after organic extraction using an in-house radioimmu-
values of the residuals and the observed value of the dependent varia-
noassay with an inter-assay CV of 7.7% at 2.20 nmol/l. Free androgen
ble. When the criteria of normality or constant variance were not met,
index (FAI) was derived from the ratio of the total testosterone concen-
a log transformation of the data was performed. Durbin–Watson sta-
tration (nmol/l) to the concentration of SHBG (nmol/l) × 100.
tistic was used to test residuals for their independence of each other.
In the logistic regression analysis, the regression coefficients com-
Data analysis and statistics
puted by minimizing the sum of squared residuals in multiple logistic
The insulin sensitivity (IS) was calculated from the Quantitative Insu-
regression are also the maximum likelihood estimates. P is the
lin Sensitivity Check Index (QUICKI), described by Katz et al.P-value calculated for the Wald statistic, which is the regression coef-
(2000). QUICKI = 1/[log(I ) + log(G )], with I = fasting insulin con-
ficient divided by the SE. All the statistical analyses were performed
centrations in mIU/ml (conversion from pmol/l to mIU/ml: multiplied
by a factor of 0.144) and G = fasting glucose concentrations in mg/dl
(conversion from mmol/l to mg/l: multiplied by a factor of 18.0). Recruitment progress
The hyperinsulinaemic–euglycaemic glucose clamp technique is
During a 4 year period, between 1999 and 2003, a total of eight cen-
the ‘gold standard’ for quantifying insulin sensitivity in vivo because
tres took part in the recruitment process. A total of 183 women were
it directly measures the effects of insulin to promote glucose utilization
screened for inclusion in the study. Of these, 40 women were
Metformin in obese PCOS patients
excluded due to previously undiagnosed tubal disease or co-existing
pregnancies). Eight women withdrew from the placebo arm (six due
male factor infertility. As a result, a total of 143 subjects were rand-
to ‘side-effects’ and two due to spontaneous pregnancies, within the
omized to receive metformin (n = 69) or to receive placebo (n = 74)
first 2 months of the study). The difference in the drop-out rates,
(Figure 1). In the metformin arm, 13 subjects withdrew within the first
excluding because of pregnancy (metformin, 15.9% versus placebo,
4 months of the trial (11 due to side-effects and two due to spontaneous
8.0%) was not significant (P = 0.229, 95% CI –2.69 to 18.5). At theend of the study, the numbers of patients who completed the trial inthe metformin and placebo arms were 56 and 66 respectively. Com-pliance was high and the drop-out rate relatively low as these werepatients motivated by a desire to conceive and the knowledge that
they needed to attain a BMI of <30 kg/m2 to qualify for ovulation
The total number of patients per centre, with those who withdrew in
parentheses, were: Leeds 65 (6), St Mary’s Hospital, London 41 (1),
MRC Reproductive Medicine Centre, Edinburgh 3 (1), Royal Shrews-
bury Hospital, Shrewsbury 12 (4), Royal Free Hospital, London 6 (0),St Bartholomew’s Hospital, London 4 (3), Hope Hospital, Salford 4 (0)and The Jessop Hospital for Women, Sheffield 8 (2). Demographic data
There were no significant differences in the baseline character-
istics of the subjects between the two groups (Table I). In themetformin and placebo groups respectively, the mean BMI
(37.6 versus 38.9 kg/m2), the median number of menstrual
cycles in the preceding 6 months (2 versus 2), the mean waistcircumference (111.9 versus 108.8 cm) and waist:hip ratio(WHR) (0.907 versus 0.900) were similar. The anthropometric
measurements of the subjects who withdrew prematurely werealso not significantly different from those who completed the
Figure 1. The progress of the subjects through the study. Table I. The baseline characteristics of the subjects in metformin and placebo groups
Proportion of subjects who withdrew, excluding pregnancy (%)
aMann–Whitney rank sum test was used to analyse the difference, and the median instead of the mean is reported. bLog transformation was carried out on the data before the analysis with two sample t-test. cQuantitative Insulin Sensitivity Check Index (QUICKI) method = 1/[log(I ) + log(G )]. I = fasting insulin levels in mIU/ml (conversion from pmol/l to mIU/ml: multiplied by a factor of 0.144). G = fasting glucose levels in mg/dl (conversion from mmol/l to mg/l: multiplied by a factor of 18.0). T.Tang et al.
As expected, there was a positive correlation between insu-
cycle pattern and fertility. Thus the observed improvement in
lin sensitivity and serum SHBG concentrations (log insulin
menstrual frequency can be viewed as an indication of improve-
sensitivity = –0.593 + 0.093 × (log SHBG), adjusted R2 = 0.11,
ment of ovulation rate and potential fecundity. P = 0.001). Additionally, there was a negative correlation
On the basis of intention to treat (ITT), 36 women (52.2%)
between insulin sensitivity and serum triglyceride concentra-
in the metformin group and 43 women (58.1%) in the placebo
tions and BMI (log insulin sensitivity = –0.454 – 0.061 × (log
group experienced improvement in menses. However, the dif-
triglycerides), adjusted R2 = 0.060, P = 0.011), even after
ference between the two groups was not significant (P = 0.589,
adjustment for age, waist circumference and serum testoster-
one concentration. Surprisingly, no association between waistcircumference and serum insulin concentration and insulin sen-
Anthropometric measurements
Significant reductions in body weight and BMI were observed
The mean duration of infertility was similar in each group
in both groups (Tables II and III). However, the changes in
[MET 4.5 (SD 2.9) years versus PLA 4.9 (3.0) years, P =
the means between the groups were not significant (–1.02 versus
0.624]. There was no difference in the percentage of primary
–0.46, 95% CI –1.15, 0.03, P = 0.063). The study was not
infertility (MET 69% versus PLA 73%, P = 0.851) or subjects
powered to determine a difference in weight even though the
who had previously been prescribed clomiphene citrate, usu-
metformin group lost twice as much weight as the placebo
ally by their primary care physician and not in the context of
group. There was a significant reduction of waist circumfer-
the fertility clinic, where body mass would have precluded
ence in the metformin group (before 113.5 cm, after 111.1 cm,
treatment (MET 43% versus PLA 49%, P = 0.718). P = 0.002) (Table II) but not in the placebo group (before 108.5cm, after 109.1 cm, P = 0.764) (Table III). The difference in
Menstrual frequency
the changes of the mean values between the two groups was
At the end of the study period, the menstrual cycles over the
not statistically significant (–2.34 versus +0.58, 95% CI –7.14,
time-course of the study increased significantly with a median
1.30, P = 0.173). Similarly, the changes in the mean of both
of improvement of one menstrual cycle per 6 months in both
systolic and diastolic blood pressure were not significantly dif-
groups (Tables II and III). However, there was no difference
between the groups (P = 0.580). Patients who menstruated<4 weeks from starting treatment were not considered to have
Endocrine parameters and lipid profiles
ovulated in response to the study. A number of studies have used
Both the fasting insulin and glucose data were skewed and
menstrual frequency as an assessment of reproductive function
therefore logarithmic transformations were performed on the
women with PCOS and an improvement in menstrual regularity
data before analysis. The geometric means of the fasting insu-
is considered to be a good surrogate for ovarian function and
lin concentrations in the metformin group did not change sig-
ovulatory frequency in women with PCOS (Morin-Papunen
nificantly over the course of the study (baseline 72.8 pmol/l,
et al., 1998; Fleming et al., 2002; Haas et al., 2003). Furthermore,
final 80.7 pmol/l, ratio of means 1.11, P = 0.524, Table II).
Kolstad et al. (1999) studied the relationship between menstrual
Similarly, no significant changes in the geometric means of the
Table II. The outcomes in the metformin group (n = 56)
aWilcoxon signed rank test was used to analyse the difference and the median instead of the mean is reported. bLog transformation was carried out on the data before the analysis. Geometric means, mean ratio (a/b) and the corresponding 95% CI were reported after the results were back-transformed. cQuantitative insulin sensitivity check index (QUICKI) method = 1/[log(I ) + log(G )].
CI = confidence interval; NS = not significant; SHBG = sex hormone-binding globulin. Metformin in obese PCOS patients Table III. The outcomes in the placebo group (n = 66)
aWilcoxon signed rank test was used to analyse the difference, and the median instead of the mean is reported. bLog transformation was carried out on the data before the analysis. Geometric means, mean ratio (a/b) and the corresponding 95% CI were reported after the results were back-transformed. cQuantitative insulin sensitivity check index (QUICKI) method = 1/[log(I ) + log(G )].
CI = confidence interval; NS = not significant; SHBG = sex hormone-binding globulin.
fasting insulin concentrations in the placebo group occurred
Table IV. Multiple linear regression analysis of the change of free androgen
(baseline 74.1 pmol/l, final 81.8 pmol/l, ratio of means 1.10,
index (log end of study levels – log baseline levels) on the percentage of
P = 0.438, Table III). The difference between the changes
weight change, the use of metformin, the change of insulin sensitivity and the
between the two treatment arms was also not significantly dif-
ferent (1.11 versus 1.10, 95% CI 0.672–1.49, P = 0.985). Simi-
larly, there were no significant changes in fasting glucoseconcentrations within and between groups (Tables II and III).
Improvements in insulin sensitivity were not observed in either
the metformin group or the placebo group (Tables II and III).
The changes of means in insulin sensitivity were also not dif-
ferent between the two groups (data not shown).
aPercentage of weight change = 100%×(baseline-end of study weight)/base-
There were no significant changes in the geometric mean
SHBG concentrations in either the metformin or placebo arms
Adjusted R2 = 0.0442. The analysis of variance for the regression: F = 1.855, P = 0.128, residual
(Tables II and III), neither was there a difference between the
groups (data not shown). There was, however, a significant
reduction in the FAI in the metformin arm of the study, with amean ratio (final:baseline) of 0.84 (95% CI 0.73, 0.96, P =0.013) and this was because of a significant fall in total testo-
difference is 0.26 and the required sample size to assess a dif-
sterone of –0.3 nmol/l (95% CI –0.08, –0.47, P = 0.008)
ference in pregnancy rates would be 600 subjects.
(Table II). This was confirmed by multiple linear regressionanalysis after adjustment for baseline BMI, change in insulin
Subgroup analysis of those who lost weight
sensitivity and the percentage of weight change (P = 0.046,
On the basis of intention to treat (ITT), 36 women (52.2%) in
the metformin group and 43 women (58.1%) in the placebo
At the end of the study period, both the total cholesterol and
group experienced improvement in menses. However, the dif-
triglyceride concentrations remained unchanged (Tables II and
ference between the two groups was not significant (P = 0.589,
III) with no between-group differences (data not shown).
95% CI –10.4, 22.2). If these data are analysed by completionof protocol, the difference is still not significant (P = 0.94, 95%
Pregnancy rates
There were two pregnancies in each arm of the study within
Forty-two subjects (60.8%) in the metformin group and 35 sub-
2 months of commencing and a further four pregnancies in the
jects (47.3%) in the placebo group managed to lose weight. The
metformin arm in the 5th and 6th months of the study. The
difference between the two groups was not significant (P = 0.147,
total numbers of conceptions in the metformin (8.7%) and the
95% CI –28.5, 29.9). When we calculated the actual percentage
placebo (2.7%) groups were not significantly different (P = 0.233,
weight change (PWC) [100% × (baseline weight – end of study
95% CI –1.5, 13.5). Based on our findings, the standardized
weight)/baseline weight] among only those women who managed
T.Tang et al.
database (Lord et al., 2003). We were unable to demonstrate
Table V. Multiple logistic regression analysis of the improvement in menses
that metformin had an additional benefit on the improvement
on the percentage of weight change and initial body mass index (BMI)
of menstrual frequency over weight loss through lifestyle mod-
ification and, furthermore, in the study population metformin
did not induce weight loss. After adjustment for baseline BMI
and age, only weight loss, but not the use of metformin, was
associated with a significant improvement in menstrual cyclic-
ity. In addition, the higher the BMI, the more likely women
with PCOS were to benefit from weight loss with respect to
aPercentage of weight change = 100%×(baseline – end of study weight)/base-
The entry criteria required BMI to be >30 kg/m2, yet the
Pearson χ2 statistic: 116.7 (P = 0.411). Likelihood ratio test statistic: 14.0 (P< 0.001).
mean BMI was ∼38 kg/m2 and comprised typical central obes-
Hosmer–Lemeshow statistic: 10.1 (P = 0.261).
ity. These were patients who would not be suitable for ovula-
tion induction for anovulatory infertility because of theirobesity and so had not yet been enrolled in the ovulation induc-tion programme, although some had previously received clo-
to lose weight, we showed that the mean percentage of weight
miphene citrate from their primary care physician before
loss in the metformin and placebo groups was 3.98 and 4.41%
referral to the fertility clinic. The rate of withdrawal in the met-
respectively. The difference was not significant (P = 0.554, 95%
formin group was not significantly different from the placebo
group and was lower than that reported by Fleming et al.
By using multiple logistic regression analyses of the improve-
(2002) in their large trial in which 42% dropped out of the met-
ment in menses on the PWC, the use of metformin, the baseline
formin arm compared with 17% of the placebo arm. This may
BMI and age, we were able to demonstrate that weight loss (a
be explained by the fact that all of our patients had a wish to
positive value of PWC) had a significantly positive effect on
conceive and may therefore have had a greater incentive to
improvement in menses (P = 0.047, regression coefficient =
0.199, odds ratio 1.126, 95% CI 1.00, 1.27). The use of met-
A surprise finding was the lack of change in insulin sensitiv-
formin had no influence on menstrual frequency in our study
ity in either the metformin or placebo groups. This is probably
explained by the extreme obesity of our patients and the rela-
The best model to predict the improvement in menses is
tively small amount of weight lost. It has been demonstrated
0.127 × (PWC) + 0.098 × (initial BMI) – 3.185 (see Table V).
that insulin sensitivity and androgen concentrations are
This implies that the greater the BMI the more likely it was that
unlikely to improve in patients who lose <5% of their initial
improvement in menses would have been experienced through
weight (Kiddy et al., 1992). Furthermore, the effect of met-
formin in women with PCOS is reduced by increasing obesity(Crave et al., 1995; Fleming et al., 2002; Maciel et al., 2004). Analysis of those with the metabolic syndrome
Our findings were similar to the study of Ehrmann et al. (1997)
The metabolic syndrome is defined as requiring three out of the
in which the average BMI was 39 kg/m2. Furthermore, the dose
following five criteria: waist circumference >88 cm, elevated
of metformin (850 mg twice daily) may be insufficient in this
triglycerides ≥1.7 mmol/l, lowered high-density lipoprotein cho-
group of patients and we are currently performing a dose-finding
lesterol <1.3 mmol/l, elevated blood pressure (≥130/85 mmHg)
study, using different doses at different body weights.
and impaired glucose tolerance test. Twenty-six of those in the
Metformin, however, did improve the FAI, secondary to a
metformin arm and 23 in the placebo arm had the metabolic syn-
significant fall in total testosterone without a change in the
drome. There was no difference in outcome between the met-
insulin sensitivity or SHBG. This observation suggests that
formin group and placebo group respectively in the median
metformin may have a direct effect on ovarian steroidogenesis
change of menstrual frequency (1 versus 1, P = 0.916), percent-
without effecting a change in circulating insulin concentrations
age weight loss (3.14 versus 2.65% P = 0.79), change in waist
(Pirwany et al., 1999; la Marca et al., 2002; Mansfield et al.,
circumference (–1.5 versus –0.93 cm, P = 0.692), change in
2003). There is a consensus that metformin has an additive
serum testosterone concentration (0.889 versus 0.968 nmol/l,
effect in achieving ovulation and pregnancy when combined
P = 0.408), change in FAI (0.891 versus 0.995, P = 0.435),
with drugs to induce ovulation (mainly clomiphene citrate)
change in insulin sensitivity (–0.003 versus 0.000, P = 0.914) or
(Costello and Eden, 2003; Lord et al., 2003). The effect may be
either cholesterol or triglyceride concentrations.
quick and this too supports the possibility of a direct effect onthe ovary rather than a systemic effect on metabolism.
The use of metformin and other insulin-lowering or -sensi-
Discussion
tizing agents has excited much interest in the management of
We report a large randomized controlled trial (RCT) to investi-
PCOS. The literature is replete with studies of varying design,
gate the effects of metformin on very obese patients with ano-
using varying regimens and assessing different outcomes. A
vulatory PCOS. The duration of the study period (6 months)
relatively small number of these studies (a total of 13) have
and the dose of metformin used (850 mg, twice daily) were the
been of appropriate design to be included in the Cochrane sys-
longest and the highest of the RCT reported in the Cochrane
tematic review (Lord et al., 2003). This included seven studies
Metformin in obese PCOS patients
comparing metformin with placebo in a total of 310 patients,
androgen-lowering medication (Gambineri et al., 2004). We
which showed that metformin was beneficial for ovulation
have found, however, that in very obese women with anovula-
(odds ratio 3.88, 95% CI 2.25, 6.69, P < 0.0001). The largest
tory PCOS, metformin, at a dose of 850 mg twice daily, had no
study to be included in this series was of 92 patients (Fleming
effect on menstrual frequency, body weight or insulin sensitiv-
et al., 2002). The meta-analysis also demonstrated that met-
ity, despite a fall in total testosterone and waist circumference.
formin was effective in reducing fasting insulin and total testo-
Furthermore a modest reduction in weight through lifestyle
sterone concentrations but had no effect on BMI or waist
modification was the most significant predictor for an
circumference (Lord et al., 2003).
Costello and Eden (2003) in their systematic review reached
similar conclusions and again a wide range of entry criteriawere reported. In particular the average ‘mean BMI’ of those
Acknowledgements
studies that compared metformin with placebo was 31.3 kg/m2
We are grateful to colleagues in participating centres: Dr R.Anderson(MRC Reproductive Medicine Centre, Edinburgh), Dr B.Bentick
(range 21.4–39.8 kg/m2). There were variable effects reported,
(Consultant Gynaecologist, Royal Shrewsbury Hospital, Shrewsbury),
with not all studies demonstrating an improvement in insulin
Dr P.Hardiman (Consultant Gynaecologist, Royal Free Hospital,
sensitivity or fall in testosterone levels (Costello and Eden,
London), Dr N.Panay (formerly Gynaecologist, Fertility Centre,
2003). As with our study, neither of the two RCT that reported
St Bartholomew’s Hospital, London), Dr H.Buckler (Consultant
an improvement in menstrual cyclicity showed a fall in BMI;
Physician, Hope Hospital, Salford) and Professor W.Ledger (Depart-ment of Obstetrics and Gynaecology, The Jessop Hospital for women,
both reported a fall in testosterone concentrations and only one
Sheffield). We also thank Ms M.O’Kane (Clinical Specialist Dietitian,
an improvement in fasting insulin (Moghetti et al., 2000;
Department of Nutrition and Dietetics, The General Infirmary at
Leeds, Leeds) for her advice and efforts to encourage our subjects to
Pasquali et al. (2000) studied 20 obese women with PCOS
lose weight. Grant: The Special Trustees of the Leeds Teaching Hos-
with a control group of 20 obese women without PCOS who
were comparable for age and pattern of body fat distribution. All were given a low-calorie diet (1200–1400 kcal/day) for
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Submitted on April 25, 2005; resubmitted on June 29, 2005; accepted on June
Prevention of venous thromboembolism in North America: Results of a survey among general sureeons Joseph A. Caprini, MD, Juan I. Arcelus, MD, PhD, Kevin Hoffinan, B A , Tanya Mattern, BS, Maureen Laubach, RVT, Gail P. Size, RVT, Clara I. Traverse, MD, PhD, and Robert Coats, BS, Purpose: The purpose of this study was to analyze current attitudes toward the prevention of postoperative venous thr
Abortion is a guaranteed right. The definition of an abortion is the termination of a pregnancy owing to or resulting in the death of the fetus. If women do not have this right, they will turn to "back-alley" abortions, which are inadequate and life threatening. Or, these women will try to perform the abortion themselves. Women in Nicaragua, India, Ethiopia, Uganda, Kenya, and Poland,