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DOI: 10.1530/EJE-07-0515
European Journal of Endocrinology, Vol 158, Issue 5, 711-719
Copyright © 2008 by European Society of Endocrinology
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CLINICAL STUDIES

Body mass index and ovarian function are associated with endocrine and metabolic abnormalities in women with hyperandrogenic syndrome

S Cupisti, N Kajaia, R Dittrich, H Duezenli, M W Beckmann and A Mueller

Department of Obstetrics and Gynecology, Erlangen University Hospital, Universitaetsstrasse 21-23, D-91054 Erlangen, Germany

(Correspondence should be addressed to A Mueller; Email: andreas.mueller{at}uk-erlangen.de)


   Abstract
Top
 Abstract
Introduction
 Patients and methods
 Results
 Discussion
 References
 
Background: The aim of this study was to evaluate associations of clinical features, such as hirsutism, polycystic ovaries (PCOs), ovulatory dysfunction, and body mass index (BMI) ≥25 kg/m2, with metabolic abnormalities in hyperandrogenic women.

Methods: Hirsutism was based on the modified Ferriman–Gallwey score. Ovulatory function was classified as eumenorrhea, oligomenorrhea and amenorrhea, and PCOs were assessed using the ultrasound criteria recommended in the Rotterdam definition. An oral glucose tolerance test was performed. Different insulin resistance (IR) indices were calculated.

Results: Hirsute women had significantly higher BMI, DHEA sulfate (DHEAS) and free androgen index (FAI), and significantly lower values for sex hormone-binding globulin (SHBG). Women with amenorrhea were younger in comparison to women with eumenorrhea and had significantly higher values for fasting insulin (FI) and 1- and 2-h insulin levels; lower values for glucose to insulin ratio (GIR), quantitative insulin sensitivity check index (QUICKI), and SHBG. Women with PCO had significantly higher levels of LH and low-density lipoprotein (LDL), whereas high-density lipoprotein (HDL) levels were significantly lower. Women with a BMI ≥25 kg/m2 had significantly higher values for age, fasting plasma glucose, FI, and 1- and 2-h glucose and insulin levels, homeostatic model for assessment of IR (HOMA-IR), homeostatic model for assessment of B-cell function (HOMA-B), and FAI, whereas their GIR, insulin sensitivity index, QUICKI, SHBG, and HDL were significantly lower.

Conclusions: In women with hyperandrogenic syndrome, BMI≥25 kg/m2 and amenorrhea appear to be associated with severe endocrine and metabolic abnormalities.


   Introduction
Top
 Abstract
 Introduction
Patients and methods
 Results
 Discussion
 References
 
The most common endocrine disorder seen in gynecological practice, with the clinical and biochemical features of hyperandrogenemia, is known as polycystic ovary syndrome (PCOS). It affects ~4–6% of women of reproductive age (1). The syndrome is associated with gynecological, endocrine, dermatological, and metabolic changes. It is a collection of signs and features in which no single phenomenon is diagnostically relevant on its own (2). The issue of how to define the syndrome appropriately has continued to generate significant controversy (2, 3).

The definition of PCOS has altered since 1844, when it was first described by Chereau 1844 (4) and Rokitanski 1844 (5). The heterogeneity of the syndrome was evident even in the initial descriptions in 1935 (6). The definition of PCOS used today was developed at an expert conference sponsored by the National Institutes of Health (NIH) in April 1990, leading to the publication of the NIH criteria (7). Another expert conference was organized in Rotterdam in May 2003 (8, 9).

On the basis of these definitions of PCOS, completely different phenotypes are possible (2, 3). It has become evident in recent years that both definitions lead to problems in practical use, resulting in subsets of women that differ too widely and have different metabolic risk profiles, consequently requiring different treatment approaches. The different phenotypes are also difficult to compare in clinical research, due to the heterogeneity of their metabolic risk profiles (2, 3).

The Androgen Excess Society recently suggested that the original NIH criteria should be accepted with some modifications, including the Rotterdam recommendation of ultrasound evidence of polycystic ovaries (PCOs), with PCOS being defined as an androgen excess syndrome or ‘hyperandrogenic syndrome’ after other androgen excess or related disorders have been excluded; the four features of ovulatory dysfunction, hirsutism, hyperandrogenemia, and PCOs should be taken into consideration (2).

Despite the controversy over the definition, ~50–70% of women with PCOS have been described as having hyperinsulinemic insulin resistance, which may play a major pathological role in the development of the syndrome (10, 11). Moreover, insulin resistance plays a causative role in the development of the metabolic syndrome (10, 12), with severe endocrine and metabolic disturbances leading to several complications later in life (13, 14, 15, 16). Diagnosing PCOS or hyperandrogenic syndrome thus implies an increased risk for these complications later in life. Lean and obese hyperandrogenic women in particular may have completely different metabolic risk profiles and may need different treatment approaches in relation to several complications that may develop later in life.

The aim of the present study was to evaluate possible associations of clinical features such as hirsutism, PCO, and ovulatory dysfunction (expressed in the form of menstrual disturbances, as an easily assessed marker) with metabolic and endocrine disturbances in hyperandrogenic women. By definition, all of the women included fulfilled the PCOS criteria in accordance with the revised Rotterdam 2003 criteria and the proposal by the Androgen Excess Society that PCOS should be defined as a predominately hyperandrogenic syndrome. In addition, the association of BMI ≥25 kg/m2 with metabolic and endocrine disturbances in these women was assessed.


   Patients and methods
Top
 Abstract
 Introduction
 Patients and methods
Results
 Discussion
 References
 
Patients

During the study period (January 2005–December 2006), 214 women were referred to the Division of Gynecological Endocrinology and Reproductive Medicine at our hospital for the evaluation of possible androgen excess or hyperandrogenism. The inclusion criteria were hirsutism, hyperandrogenemia, PCO, and ovulatory dysfunction (expressed in the form of menstrual disturbances), in the absence of other endocrine abnormalities also affecting ovulatory function, for example, hyperprolactinemia, functional hypothalamic amenorrhea, or thyroid dysfunction. The exclusion criteria were: 21-hydroxylase-deficient non-classical adrenal hyperplasia (NCAH), hyperandrogenic insulin resistance and acanthosis nigricans (HAIRAN) syndrome, or an androgen-secreting neoplasm. All of the women included thus met the definition of PCOS provided by the Rotterdam criteria as well as the NIH criteria. Women who had been receiving hormonal therapy, including oral contraceptive pills or steroid medications within 3 months of their initial visit were not included. The study was approved by the local ethics committee. All of the patients provided written informed consent and completed a uniform medical history questionnaire with an emphasis on menstrual dates and regularity, hirsutism, acne, gynecological history, history of infertility, medications, and family history.

Procedures

All of the women underwent a complete screening panel, including physical examination, weight and height measurement, ultrasound examination of the ovaries, and their body mass index (BMI) was calculated. Hirsutism was scored in accordance with the modified Ferriman–Gallwey score (17). PCOs were diagnosed on ultrasound when at least one ovary had a volume above 10 ml or there were 12 or more follicles measuring 2–9 mm in diameter. The interval between bleeding episodes was assessed. The major clinical signs, such as oligomenorrhea or amenorrhea, vary in duration but are generally unambiguous (18). Women with regular bleeding episodes between 26 and 32 days were categorized as eumenorrheic. Women with cycles longer than 32 days were categorized as oligomenorrheic. In those women, serum was obtained between days 3 and 5 of their menstrual cycle. Women with amenorrhea within the previous year were categorized as anovulatory without further testing, and blood was taken for hormonal analysis at random. Women with cycles of less than 26 days were not included in the study.

Calculation of insulin resistance

All the patients were on an unrestricted diet. An oral glucose (75 g) tolerance test was carried out, with glucose (mg/dl) and insulin (µIU/ml) measured at 0, 60, and 120 min. After glucose and insulin levels had been measured, the following mathematical models were used to assess insulin resistance

  1. The glucose to insulin ratio (GIR) was calculated using the formula described by Legro et al. (19).
  2. The homeostatic model for assessment of insulin resistance (HOMA-IR) was calculated using the following formula (20): FG (mmol/l)xFI (µU/ml)/22.5.
  3. The homeostatic model for assessment of B-cell function (HOMA-B) was calculated using the formula (20): 20xFI (µU/ml)/(FG (mmol/l) – 3.5).
  4. The quantitative insulin sensitivity check index (QUICKI) was calculated using the formula (21): 1/(log (FI) (µU/ml)+log (FG) (mg/dl)).
  5. The Matsuda insulin sensitivity index (ISI) was calculated using the formula (22): 10 000/{surd}(FG (mg/dl)xFI (µU/ml)xG (mg/dl)xI (µU/ml)) (FG, fasting plasma glucose; FI, fasting plasma insulin; G, mean plasma glucose concentration; and I, mean insulin concentration during the oral glucose tolerance test).

Exclusion of related disorders

For evaluation of an androgen-secreting neoplasm, the total testosterone cut off value used was above 7 nmol/l, at which point computed tomography of the adrenal gland is normally carried out at our institution to exclude an androgen-secreting neoplasm. To exclude 21-hydroxylase deficiency in patients with a 17-hydroxyprogesterone (17-HP) level above 6 nmol/l, 17-HP levels stimulated by adrenocorticotropic hormone (ACTH) were measured (23, 24). In brief, all tests were started between 0800 and 0900 h with the patients in the fasting state. A baseline sample was obtained, and thereafter 0.25 mg ACTH (Synacthen, Novartis, Germany) was administered intravenously over 60 s and blood was sampled after 60 min. Both the baseline and 60-min samples were assayed for 17-HP levels. If the stimulated 17-HP level was above 30 nmol/l, the woman was considered to have 21-hydroxylase-deficient non-classical adrenal hyperplasia.

Biochemical measurements

All of the assays were carried out in our routine diagnostic endocrinology laboratory using established commercial assays routinely monitored by participation in external quality control programs.

Total testosterone (TT), DHEA sulfate (DHEAS), and sex hormone-binding globulin (SHBG) were measured with chemiluminescent enzyme immunoassays (Immulite 2000, Diagnostic Products Corporation, Los Angeles, CA, USA). The calibration range of the TT assay was 0.7–55 nmol/l with an analytical sensitivity of 0.5 nmol/l. The cross-reaction with 5{alpha}-dihydrotestosterone was 2%. The calibration range of the DHEAS assay was 0.41–27 µmol/l with an analytical sensitivity of 0.08 µmol/l. No cross-reactivity with other compounds was known. The calibration range of the SHBG assay was up to 180 nmol/l with an analytical sensitivity of 0.02 nmol/l. The inter- and intra-assay coefficients of variation (CVs) were always below 11% at mid-range concentrations. No cross-reactivity with other compounds was known.

Estradiol was measured using a solid-phase competitive chemiluminescent enzyme immunoassay (Immulite 2000, Diagnostic Products Corp). The calibration range of the assay was 73–7342 pmol/l with an analytical sensitivity of 55 pmol/l. The intra-assay CVs were 9.9, 7.8, and 4.3% at the levels of 327, 660, and 1692 pmol/l respectively. The corresponding inter-assay CVs were 16, 11, and 6.7%. The cross-reactivity with 17β-estradiol valerate was 1.14%.

Prolactin was measured using an immunometric assay (Immulite 2000, Diagnostic Products Corp). The calibration range of the assay was up to 3180 mIU/l with an analytical sensitivity of 3.4 mIU/l. The intra-assay CVs were 2.8, 3.6, and 2.3% at the levels of 186.6, 402.6, and 466.6 mIU/l respectively. The corresponding interassay CVs were 8.2, 7.4, and 5.9%. No cross-reactivity with other compounds is known.

Lutinizing hormone (LH) was measured with an immunometric assay (Immulite 2000, Diagnostic Products Corp). The calibration range of the assay was up to 200 mIU/ml with an analytical sensitivity of 0.05 mIU/ml. The intra-assay CVs were 3.04, 3.71, and 3.6% at the levels of 1.04, 1.89, and 8.7 mIU/ml respectively. The corresponding inter-assay CVs were 6.6, 6.2, and 6.7%. The cross-reactivity with human chorionic gonadotropin was 0.20%. FSH was measured with an immunometric assay (Immulite 2000, Diagnostic Products Corp). The calibration range of the assay was up to 170 mIU/ml with an analytical sensitivity of 0.1 mIU/ml. The intra-assay CVs were 2.5, 2.9, and 2.1% at the levels of 4, 9.1, and 40 mIU/ml respectively. The corresponding inter-assay CVs were 6.3, 5.5, and 4.3%. The cross-reactivity with thyrotrophin was 0.01%.

Plasma insulin was determined using a solid-phase two-site chemiluminescent immunometric assay (Immulite 2000, Diagnostic Products Corp). The calibration range of the assay was up to 300 µIU/ml with an analytical sensitivity of 2 µIU/ml. The intra-assay CVs were 5.5, 4.0, 3.3, 3.9, 3.8, and 3.7% at the levels of 7.67, 12.5, 17.2, 26.4, 100, and 291 µIU/ml respectively. The corresponding inter-assay CVs were 7.3, 4.9, 4.1, 5.0, 4.2, and 5.3%. The cross-reactivity with proinsulin was 8%. Plasma concentration was measured with the glucose oxidase method using an automatic biochemical analyzer (Immulite 2000, Diagnostic Products Corp).

Total cholesterol (Ch), low-density cholesterol (LDL), high-density cholesterol (HDL), and triglycerides (TGs) were regularly measured after an overnight fasting period of 12 h, using routine clinical chemistry methods and then documented.

Calculation of the free androgen index (FAI)

The FAI was obtained as the quotient 100xtotal testosterone (TT)/SHBG (24, 25).

Statistical analysis

Numerical variables are presented as mean±S.D. unless otherwise noted. We employed non-parametric statistical tests that are based on ranks of observations and require no assumptions about the underlying distribution of data. All hypothesis tests were two sided. For bivariate analysis, two-sample Wilcoxon tests (i.e., Wilcoxon rank-sum tests) were used to compare parameters between hyperandrogenic women with and without specific categorical variables (hirsutism, PCO, oligomenorrhea, amenorrhea, and BMI>25 kg/m2). Afterwards, we explored the possible influence of categorical variables (hirsutism, PCO, amenorrhea, and BMI >25 kg/m2) of the other endocrine and metabolic parameters using a multivariate ANOVA, and a P value <0.05 was considered statistically significant. All statistical analyses were carried out using the Statistical Program for the Social Sciences (SPSS version 13.0 for Windows; SPSS Inc., Chicago, IL, USA).


   Results
Top
 Abstract
 Introduction
 Patients and methods
 Results
Discussion
 References
 
A total of 214 women with clinical or biochemical signs of hyperandrogenemia presented for the evaluation of possible androgen excess or hyperandrogenism at the Division of Gynecological Endocrinology and Reproductive Medicine in Erlangen University Hospital between January 2005 and December 2006. Twenty women were not included, as they had been receiving hormonal treatment within 3 months of their initial visit. Eight women had hyperprolactinemic oligo-ovulation/anovulation and two women showed evidence of 21-OH-deficient NCAH. All of the women included in the study had at least one androgen level increased. No ovarian tumors were identified using ultrasonography in any of the women, and none of them had HAIRAN syndrome. The study population thus consisted of 184 women with hyperandrogenic syndrome.

Comparison of hyperandrogenic women with hirsutism with hyperandrogenic women without hirsutism

Women classified as hirsute had significantly higher BMI, DHEAS, and FAI values. They showed significantly lower values for SHBG. The results are shown in Table 1.


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  		Table 1 The differences between endocrine and metabolic variables in the group of women with hirsutism in comparison with the group of women without hirsutism.

 
Comparison of hyperandrogenic women with amenorrhea or oligomenorrhea with hyperandrogenic women with regular menses

Women classified as having oligomenorrhea showed no significant differences in comparison with women with eumenorrhea. However, women classified as having amenorrhea were younger in comparison with women with eumenorrhea and had significantly higher values for fasting insulin and 1- and 2-h insulin levels. They had lower values for GIR and QUICKI. They also had significantly lower values for SHBG than hyperandrogenic women with eumenorrhea. The results are shown in Table 2.


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  		Table 2 The differences between endocrine and metabolic variables in the group of women with oligomenorrhea in comparison with the group of women with eumenorrhea, and the differences in the group of women with amenorrhea in comparison with the group of women eumenorrhea.

 
Comparison of hyperandrogenic women with ultrasound criteria of PCOs with hyperandrogenic women with normal ovarian morphology

Women with ultrasound evidence of PCOs had significantly higher levels of LH and LDL, whereas HDL was significantly lower. The results are shown in Table 3.


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  		Table 3 The differences between endocrine and metabolic variables in the group of women with polycystic ovaries (PCO) in comparison with the group of women without PCO.

 
Comparison of overweight hyperandrogenic women (BMI ≥25 kg/m2) with normal weight hyperandrogenic women (BMI <25 kg/m2)

Hyperandrogenic women with BMI ≥25 kg/m2 had significantly higher values for age, FG, FI, and 1- and 2-h glucose and insulin levels, HOMA-IR, HOMA-B, and FAI, whereas GIR, ISI, QUICKI, SHBG, and HDL were significantly lower. The results are shown in Table 4.


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  		Table 4 The differences between endocrine and metabolic variables in the group of women with BMI ≥25 kg/m2 in comparison with the group of women with BMI <25 kg/m2.

 
Results of the multivariate ANOVA

Bivariate analysis showed no difference between women classified as having oligomenorrhea in comparison with women with eumenorrhea. Therefore, oligomenorrhea as a possible predictive value was excluded from further multivariate analysis.

The possible influences of the other categorical variables (hirsutism, PCO, amenorrhea, and BMI >25 kg/m2) of the endocrine and metabolic variables are described as follows.

In women with BMI >25 kg/m2 HOMA-IR was significantly increased, while after adjustment with BMI >25 kg/m2, the clinical features hirsutism, PCO, and amenorrhea had no influence (Table 5). In women with BMI >25 kg/m2 or amenorrhea, HOMA-B was significantly increased, while after adjustment with BMI >25 kg/m2 and amenorrhea, the clinical features hirsutism and PCO had no influence (Table 6). In women with BMI >25 kg/m2, ISI was significantly decreased, while after adjustment with BMI >25 kg/m2, the clinical features hirsutism, PCO, and amenorrhea had no influence (Table 7). In women with BMI >25 kg/m2, QUCKI was significantly decreased while after adjustment with BMI >25 kg/m2, the clinical features hirsutism, PCO, and amenorrhea had no influence (Table 8). In women with BMI >25 kg/m2 or hirsutism or amenorrhea, SHBG levels were significantly decreased while after adjustment with BMI >25 kg/m2, the clinical features hirsutism and amenorrhea, PCO showed no influence of SHBG levels (Table 9).


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  		Table 5 Homeostatic model for assessment of insulin resistance (HOMA-IR), multivariate ANOVA.

 

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  		Table 6 Homeostatic model for assessment of B-cell function (HOMA-B), multivariate ANOVA.

 

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  		Table 7 Insulin sensitivity index (ISI), multivariate ANOVA.

 

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  		Table 8 Quantitative insulin sensitivity check index (QUICKI), multivariate ANOVA.

 

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  		Table 9 Sex hormone-binding globulin (SHBG), multivariate ANOVA.

 

   Discussion
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
References
 
The aim of this study was to evaluate possible associations of the clinical features hirsutism, PCO, and ovulatory dysfunction with metabolic changes or risk factors in hyperandrogenic women. By definition, all of the women included met the PCOS criteria in accordance with the revised Rotterdam 2003 criteria and the proposal made by the Androgen Excess Society (3). Additionally, we assessed the association of BMI ≥25 kg/m2 with metabolic changes, as an elevated BMI has been described as increasing the risk for adverse health consequences, especially among patients with metabolic syndrome or IR (26). In the study population, the incidence of BMI ≥25 kg/m2 and amenorrhea – as a marker of chronic anovulation, which is the most severe form of disturbance in ovarian function (18) – was associated with the most severe changes in the endocrine and metabolic profile in hyperandrogenic women, whereas the incidences of hirsutism, PCO, and oligomenorrhea were associated only with minor or no changes in metabolic parameters in the women studied.

IR in particular is known to be a prominent feature associated with the risk of the metabolic syndrome and the development of type 2 diabetes. The urgent need for a simple way of measuring insulin resistance has led to the creation of a large number of insulin sensitivity indices that have been reviewed elsewhere (22, 27, 28, 29). However, Moltz showed recently that it is possible to determine IR using defined cut off points for glucose (102 mg/dl) and insulin (13 µU/ml) when screening for the metabolic syndrome (30). Insulin sensitivity indices that use fasting glucose and insulin values may not provide greater objectivity in assessing insulin resistance than fasting values for glucose and insulin itself (31, 32, 33). The advantage of using GIR, HOMA-IR, HOMA-B, and QUICKI may therefore be questionable. The Matsuda ISI is the only index that incorporates 1- and 2-h levels for OGTT into the calculation model, and it has been reported that the Matsuda ISI is best able to predict the risk of insulin resistance and provides the best relative sensitivity and specificity rates in comparison with other markers (31, 33). Recently, reference values have also been established for the Matsuda ISI in order to distinguish between patients with insulin resistance and those who are insulin sensitive (31). In this study, Matsuda ISI showed a significant negative correlation with the incidence of three (out of five) clinical features. However, the ISI values were significantly lower only in women with BMI ≥25 kg/m2.

In general, BMI ≥25 kg/m2 was significantly associated with changes in all of the insulin sensitivity indices and may therefore serve as a predictive marker of IR in hyperandrogenic women. The increase in fasting insulin and glucose values in hyperandrogenic women was also significantly associated and correlated with BMI ≥25 kg/m2. This result appears to be in accordance with the results reported by Moltz (30). Furthermore, amenorrhea may also serve as a possible predictive marker of IR in hyperandrogenic women. However, we found that only an alteration in QUICKI, FI, 1-, and 2-h insulin values was significantly associated with the incidence of amenorrhea. All insulin values and all of the insulin sensitivity indices (except for QUICKI) correlated significantly with the incidence of amenorrhea. Overall, a diagnostic advantage for the calculated insulin sensitivity indices that use fasting glucose and insulin values was also not observed in this study, although investigating this was not the aim of the study.

In addition, it may be difficult to use the cut off points for the selected indices, and it should be noted that these indices are not absolutely strict for the diagnosis of impaired carbohydrate metabolism, although they may help identify women who have the highest risk for developing diabetes (31). Recently, SHBG was found to be a predictive marker of insulin resistance (34), which showed a significant negative correlation with the incidence of hirsutism, amenorrhea, and BMI ≥25 kg/m2 and was also significantly altered in patients with amenorrhea or BMI ≥25 kg/m2. Diagnosing insulin resistance in women with hyperandrogenemic syndrome or androgen excess may help identify endocrine and metabolic risk factors and identify individuals for targeted treatment with insulin sensitizers, in order to improve treatment approaches and prevent complications later in life (35, 36).

In the hyperandrogenic women studied, each specific clinical feature appears to be related to extensive differences in the endocrine and metabolic profiles. The definitions of PCOS have changed in recent years, and completely different phenotypes have been described (2, 3). It has become evident in recent years that all of the current definitions lead to problems in practical use, resulting in subsets of women with excessively different characteristics who have different metabolic risk profiles and require different treatment approaches. The term ‘PCOS’, therefore, does not describe a uniform population and covers a wide range of metabolic changes in different individuals (2, 3). It may be asked whether continued use of the term ‘PCOS’ takes sufficient account of more recently identified aspects of the etiology and pathogenesis of this complex syndrome. Using the misleading and simplified term ‘PCOS,’ which comprises a variety of different entities, involves a risk of misinterpretation and of underestimation or overestimation of symptoms, as well as overlooking contraindications (37). However, classifications of hyperandrogenism in women are available that take greater account of ovarian function, obesity, and hyperinsulinemic insulin resistance as the key clinical factors leading to different therapy approaches. Geisthovel and Rabe have proposed a classification with five different subsets: functional cutaneous androgenization and functional androgenizing syndrome I–IV (37, 38).

It may be necessary to implement a classification with strictly defined therapy-targeted concepts and diagnostic procedures for female functional androgenization (37), particularly since obese hyperandrogenic women with insulin resistance may benefit from participation in weight reduction programs, exercise instruction, and possibly treatment with insulin-sensitizing drugs as part of their individual treatment regimens (26).

The Androgen Excess Society recently suggested that the syndrome should be defined as a predominantly hyperandrogenic syndrome. The task force considered that PCOS was defined by all of the component phenotypes that potentially signal an increased risk for insulin resistance and the resulting metabolic abnormalities, and consideration of the following four features was suggested: ovulatory dysfunction, hirsutism, hyperandrogenemia, and PCOs (3). In the population included in this study, the clinical features of hirsutism and PCOs were not associated with significant changes in the metabolic variables used. PCO was only associated with an alteration in lipoproteins as described previously by Chen et al. (39). However, it is questionable whether these features can serve as predictive markers of metabolic abnormalities in hyperandrogenic women. If these features are useful at all, then perhaps only when they are together with other clinical symptoms. However, ovulatory dysfunction appearing as amenorrhea was associated with the most severe metabolic abnormalities and may serve as a predictive marker of metabolic abnormalities. In our opinion, the BMI needs to be incorporated into any definition if the aim is to identify hyperandrogenic women with metabolic abnormalities.

In summary, women with hyperandrogenic syndrome can be classified in relation to their clinical characteristics into subgroups with different endocrine and metabolic profiles and associated metabolic risks. These subgroups require different treatment approaches and ovarian function, and increased BMI associated with hyperinsulinemic insulin resistance, in particular, should be given special consideration.


   Acknowledgements
 
Research for this paper was supported by a grant from the Katholischer Akademischer Austauschdienst (KAAD). We thank Mrs H Niggemann for her independent statistical review of the data and the statistical analysis.


   References
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 References
 

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Received 31 January 2008
Accepted 1 February 2008





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