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Failure of Mathematical Indices to Accurately Assess Insulin Resistance in Lean, Overweight, or Obese Women with Polycystic Ovary Syndrome

Endocrine Section of the First Department of Internal Medicine, Athens University School of Medicine, Laiko General Hospital, Athens 115 27, Greece

Address all correspondence and requests for reprints to: Evanthia Diamanti-Kandarakis, M.D., Ph.D., Athens University School of Medicine, Laiko General Hospital, 1A Zefyrou str, Athens 145 78, Greece. E-mail: akandara{at}otenet.gr.

	Abstract

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Insulin resistance is a common metabolic feature of polycystic ovary syndrome (PCOS). In this study, we examined the validity of the mathematical indices [the quantitative insulin sensitivity check index (QUICKI) and the homeostasis model of assessment (HOMA)] that calculate insulin sensitivity and their correlation to glucose utilization with the insulin infusion rate in 40 mU/m²·min by the euglycemic clamp (M) in women with PCOS.

We studied 59 women with PCOS (20 lean, 16 overweight, and 23 obese subjects). Euglycemic clamp testing was performed, and QUICKI, HOMA, total testosterone, fasting insulin, fasting glucose, and glucose-to-insulin ratio were estimated.

No difference was found in testosterone and glucose levels among the three groups. Lean or overweight women compared with obese women differed in insulin levels, glucose-to-insulin ratio, QUICKI, and HOMA (P < 0.01). No statistical difference was found between lean and overweight women in the above parameters. M differed when lean women were compared with overweight (P < 0.002) or obese women (P < 0.0001); however, no statistical difference was observed between overweight and obese women. No significant correlation was found between M and QUICKI or HOMA.

We conclude that mathematical indices should be applied with caution in different insulin-resistant populations and should not be considered a priori equivalent to the euglycemic clamp technique.

	Introduction

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ACCORDING TO THE National Institute of Child Health and Human Development conference, polycystic ovary syndrome (PCOS) is defined by the presence of hyperandrogenism and chronic anovulation. It is considered to be the most common endocrinopathy among women of reproductive age (4–6%) (1, 2). The heterogeneous clinical picture of PCOS includes hirsutism, acne, menstrual abnormalities, and subfertility. In addition, important metabolic aberrations (like insulin resistance) have been found to be linked to the syndrome (1, 3).

For the past 20 yr, the gold standard method for quantifying insulin sensitivity has been the hyperinsulinemic-euglycemic clamp technique; this remains the case today. This method directly measures the effects of insulin to promote glucose utilization under steady-state conditions. It is an accurate in vivo assessment of insulin action (4), but is difficult to perform in large, population-based studies because it is expensive, invasive, uncomfortable for the patient, and time consuming. Because of the need to study the impact of insulin resistance in various diseases in large epidemiological studies, simple and accurate methods are required to assess insulin sensitivity. For this purpose, different mathematical formulas have been calculated. These formulas, however, carry a risk of extrapolating conclusions from calculations to in vivo phenomena.

The quantitative insulin sensitivity check index (QUICKI) is a new mathematical index proposed by Katz et al. (5) for assessing insulin sensitivity. QUICKI is defined as 1/(log I₀ + log G₀), where I₀ is the fasting insulin, and G₀ is the fasting glucose. It was proposed for estimating basal insulin sensitivity in large-scale populations, based on a single blood sample. It was shown to be well correlated when compared with the insulin sensitivity index derived from glucose clamp studies (SI clamp) and the minimal model analysis (SI_MM) in nonobese, obese, and type 2 diabetic patients (6). However, when each group was analyzed separately, the correlation coefficient was low (r = 0.48) in nonobese patients, which suggested that perhaps QUICKI may not be a reliable method to accurately include the wide spectrum of insulin sensitivity in different insulin-resistant populations.

Additionally, the results presented by Abassi and Reaven (7) in a group of 490 nondiabetic, healthy subjects suggest that QUICKI seems to be less efficient when applied in cases of mild insulin resistance and in subjects with borderline normal fasting glucose and insulin. As expected, the homeostasis model assessment (HOMA) index appears to have a good correlation with QUICKI, according to Katz et al. (5) (r = 0.77) and Abassi and Reaven (7) (r = 0.99). It should be mentioned that both approaches estimate insulin resistance using the values of fasting glucose and insulin.

The aim of this study was to investigate the correlation of these mathematical indices with the M values of the euglycemic clamp in lean, overweight, and obese women with PCOS.

	Subjects and Methods

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Subjects

Fifty-nine young women with PCOS were enrolled in the study; of these, 20 were lean, 16 were overweight, and 23 were obese. Each patient met the diagnostic criteria for PCOS presented at the 1990 National Institutes of Health Conference on PCOS and at the 1995 Serono Symposium on PCOS. These criteria include hyperandrogenism and chronic anovulation, with the exclusion of secondary causes such as nonclassical adrenal 21-hydroxylase deficiency, hyperprolactinemia, and androgen-secreting neoplasms.

In these women, oligomenorrhea was defined as fewer than six cycles per year and hyperandrogenism as total testosterone (TT) levels above the 95th percentile of the levels detected in a group of women with normal cycles; in addition, they had hirsutism and acne. All women studied were clinically healthy, not suffering from any chronic or acute diseases, and were also studied during their follicular phase, either during the spontaneous menstrual cycle or with postprogesterone withdrawal bleeding. None were taking any medication that could interfere with the hormonal and metabolic profile or oral contraceptives (oral contraceptive therapy was interrupted at least 3 months before the study). To be eligible for the study, body weight had to have remained stable for at least the 2 prior months (subjects participating in any exercise or weight-reducing programs were excluded). All participating women had normal fasting glucose levels, and an oral glucose tolerance test was performed if fasting glucose was found to be between 100 and 120 mg/dl to exclude diabetes mellitus or impaired glucose tolerance.

We also calculated the body mass index (BMI) to assess obesity. We classified women who had a BMI of 16–24.9 kg/m² as normal weight, those who had a BMI of 25–29.9 kg/m² as overweight, and those who had a BMI over 30 kg/m² as obese.

All participants were recruited from the Endocrine Section of the First Department of Medicine, Athens University School of Medicine, at the Laiko Athens General Hospital. The protocol was approved by the Institutional Review Committee of the "Laiko" General Hospital of Athens, and written informed consent was obtained from each subject before entry into the study.

Experimental protocol

After a 10- to 12-h overnight fast, blood samples were collected from each subject.

Soon afterward, insulin sensitivity of the whole PCOS group (n = 59) was assessed using the hyperinsulinemic-euglycemic clamp (4).

Euglycemic-hyperinsulinemic clamp

An iv catheter was inserted retrogradely into a dorsal vein in the left arm and kept warm at 65 C via a heated blanket for intermittent sampling of arterialized venous blood. A second catheter was inserted into an antecubital vein in the contralateral arm for the administration of glucose and insulin. Insulin was started at a rate of 40 mU/m²·min (287.2 pmol) via an infusion pump for 120 min, to increase plasma insulin level to approximately 80 µU/ml (574 pmol/liter), while maintaining plasma glucose at the basal level. Plasma glucose was maintained between 84.3 ± 1.2 mg/dl (5 ± 0.07 mmol/liter) in the lean group, 87.3 ± 1.3 mg/dl (5.23 ± 0.07 mmol/liter) in the overweight group, and 88.3 ± 1.3 mg/dl (5.29 ± 0.07 mmol/liter) in the obese group by blood sampling every 5 min and was clamped at this level by periodically adjusting a variable infusion of 20% dextrose via an Abbott LifeCare infusion pump (Abbott Laboratories, Abbott Park, IL). The coefficient of variation in steady-state plasma glucose was less than 4% in all three groups. Mean steady-state plasma insulin levels were not statistically significant in all three groups: 84.2 ± 11.5 µU/ml (604.5 ± 82.5 pmol/liter) in the lean group, 67.3 ± 6.7 µU/ml (483.2 ± 48.1 pmol/liter) in the overweight group, and 77.3 ± 7.3 µU/ml (555 ± 124.2 pmol/liter) in the obese group.

It has been demonstrated previously that hepatic glucose production is suppressed by 90% at an insulin concentration of approximately 300 pmol/liter (8). Under these conditions, peripheral glucose utilization (M, mg/kg·min, mmol/kg·min) is equal to the rate of glucose infusion to maintain euglycemia. The final 30 min of the infusion period was used for the determination of peripheral glucose utilization. During the steady state, when euglycemia is reached, the assumption is made that glucose disposal reflects glucose utilization by the peripheral tissues.

QUICKI

QUICKI was calculated using the following formula: 1/[log (I₀)] + [log (G₀)] (Ref. 5).

HOMA

HOMA was calculated using the following formula: HOMA = [I₀ (µU/ml) x G₀ (mmol/liter)]/22.5.

Assays

Serum TT (nanograms per deciliter, nanomoles per liter), serum fasting insulin (micro-International Units per liter, picomoles per liter), and serum fasting glucose (milligrams per deciliter, millimoles per liter) were measured, and the G₀/I₀ was estimated in all subjects. Blood samples were centrifuged immediately, and serum was stored at -20 C until assayed. Plasma glucose was determined by the glucose oxidase method (Beckman Glucose Analyser, Palo Alto, CA). Serum insulin levels were determined using the RIA Insulin-CT Kits by CIS Bio International (Gif-sur-Yvette, Cedex, France). Duplicate plasma samples were analyzed for TT measured using the DSL-4000 RIA Kit by Diagnostic Systems Laboratories, Inc. (Webster, TX). The intra- and interassay coefficients of variance for insulin were 8.2 and 8.8% and 5.4 and 6.4%, respectively; for TT, they were 9.6 and 8.6% and 8.1 and 9.1%, respectively.

Statistical analysis

Results are reported as mean value ± SE; BMI and age are reported as mean value ± SD. Statistical analysis of differences in QUICKI, M, TT, fasting insulin, fasting glucose, and G₀/I₀ were assessed using ANOVA. Normal distribution of continuous variables was assessed by applying the nonparametric Kolmogorov-Smirnov test. All variables were normally distributed except for the HOMA results, which were log-transformed. Correlations between variables were evaluated by Pearson’s coefficient. Correlation of HOMA with the other normally distributed variables was also evaluated with the nonparametric procedure (Spearman’s coefficient), but no difference was observed when compared with the parametric testing (Pearson’s coefficient).

	Results

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The women studied in each group (lean, overweight, and obese) did not differ in age (23.0 ± 3.8 yr vs. 24.2 ± 5.1 yr vs. 23.2 ± 4.2 yr, respectively), but differed in BMI (21.8 ± 2.3 kg/m² vs. 26.9 ± 1.5 kg/m² vs. 36.5 ± 4.4 kg/m²; P < 0.0001). TT levels did not differ among the groups [84.9 ± 7.2 ng/dl (2.94 ± 0.4 nmol/liter) vs. 95.6 ± 8.6 ng/dl (3.29 ± 0.9 nmol/liter) vs. 100.2 ± 9.1 ng/dl (3.47 ± 0.1 nmol/liter), respectively]. Fasting glucose also did not differ among the groups [84.9 ± 1.8 mg/dl (5.09 ± 0.1 mmol/liter) vs. 88.0 ± 1.5 mg/dl (5.28 ± 0.09 mmol/liter) vs. 87.3 ± 2.5 mg/dl (5.23 ± 0.15 mmol/liter)]. Insulin levels, QUICKI, G₀/I₀, and HOMA did not differ between lean and overweight PCOS women: 18.5 ± 1.6 µU/ml (132.83 ± 11.48 pmol/liter) vs. 17.5 ± 1.3 µU/ml (125.65 ± 9.3 pmol/liter), 0.316 ± 0.003 vs. 0.315 ± 0.003, 5.0 ± 0.3 vs. 5.3 ± 0.3, and 3.9 ± 0.4 vs. 3.8 ± 0.2, respectively; but differed when lean women were compared with obese women: 18.5 ± 1.6 µU/ml (132.83 ± 11.48 pmol/liter) vs. 26.1 ± 2.6 µU/ml (187.39 ± 18.66 pmol/liter), P < 0.01; 0.316 ± 0.003 vs. 0.302 ± 0.003, P < 0.008; 5.0 ± 0.3 vs. 3.9 ± 0.2, P < 0.01; and 3.9 ± 0.4 vs. 5.6 ± 0.5, P < 0.01, respectively, and when the overweight women were compared with the obese women: 17.5 ± 1.3 µU/ml (125.65 ± 9.3 pmol/liter) vs. 26.1 ± 2.6 µU/ml (187.39 ± 18.66 pmol/liter), P < 0.009; 0.315 ± 0.003 vs. 0.302 ± 0.003, P < 0.01; 5.3 ± 0.3 vs. 3.9 ± 0.2, P < 0.004; and 3.8 ± 0.2 vs. 5.6 ± 0.5, P < 0.01, respectively. Glucose utilization (M) during the clamp did not differ when the overweight women were compared with obese women (2.7 ± 0.3 vs. 2.4 ± 0.1 mg/kg·min; 1.49 ± 0.16 vs. 1.33 ± 0.05 mmol/kg·min), but did differ when lean women were compared with the overweight (4.1 ± 0.3 vs. 2.7 ± 0.3 mg/kg·min; 2.27 ± 0.16 vs. 1.49 ± 0.16 mmol.kg·min; P < 0.002) and with the obese women (4.1 ± 0.3 vs. 2.4 ± 0.1 mg/kg·min; 2.27 ± 0.16 vs. 1.33 ± 0.05 mmol/kg·min; P < 0.0001).

Correlations

No significant correlation was found between M and QUICKI [r = 0.1; P = not significant (ns)] or M and HOMA (r = -0.1; P = ns) in the total population or in each subgroup as depicted in the Figs. 1 and 2. The other studied parameters also did not correlate with M except for BMI (r = -0.4; P = 0.0001).

View larger version (14K): [in this window] [in a new window]   FIG. 1. The lack of correlation between the M and QUICKI in the three groups of PCOS women. OB, Obese; OW, overweight; L, lean.

View larger version (14K): [in this window] [in a new window]   FIG. 2. The lack of correlation between the M and HOMA index in the three groups of PCOS women. OB, Obese; OW, overweight; L, lean.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
In the present study, the data of the PCOS population, which covered a broad spectrum of BMI, did not show any significant correlation between the estimated mathematical indices of QUICKI plus HOMA and the levels of glucose utilization as assessed by the hyperinsulinemic-euglycemic clamp technique. These findings in patients with PCOS stand in contrast to recent studies that demonstrated a significant correlation of QUICKI to insulin sensitivity. This lack of correlation is reported for the first time in this type of insulin-resistant population, and it contradicts recent studies that demonstrated a significant correlation of QUICKI to insulin sensitivity in other insulin-resistant groups like obese patients, diabetics, and patients with coronary heart disease or hyperlipidemia (5, 6, 9).

Because insulin resistance is a heterogeneous entity, it is likely to be influenced by several factors in different insulin-resistant states and, therefore, the calculated indices may not accurately reflect the in vivo situation. PCOS is characterized by an apparently unique form of insulin resistance, and it is unknown whether either the QUICKI or HOMA indices accurately express this type of insulin resistance. The present study was conducted to evaluate the validity of these mathematical indices in assessing insulin sensitivity and its correlation to glucose utilization by the euglycemic clamp technique in lean, overweight, and obese women with PCOS.

Because the PCOS subgroups did not differ in age, TT, or fasting glucose levels, these parameters could not be considered responsible for this lack of correlation. Even in the absence of changes in fasting glucose and fasting insulin levels, the results of the insulin clamp studies (M) indicate that glucose utilization is variable in lean and overweight women with PCOS. These abnormalities are not detected using the QUICKI or HOMA indices that are calculated from fasting glucose and insulin levels. Furthermore, this finding is in accordance with the data reported by Abassi and Reaven (7), where the QUICKI is less accurate when applied to cases of mild insulin resistance or in subjects with borderline normal fasting glucose and insulin.

In this study, as expected, the comparison between the lean and obese subgroups showed statistically significant differences with all the methods used.

Insulin resistance estimated from glucose utilization (M) during the clamp technique did not differ between overweight and obese women; however, other estimates of insulin resistance (fasting insulin, QUICKI, and G₀/I₀) were different between overweight and obese women. This may be due to the use, in the present study, of a low insulin infusion rate (40 mU/m²·min), which is probably not enough to overcome the insulin resistance in more resistant states of PCOS patients as is the case in overweight or obese women. On the other hand, the high correlation between these methods found by Katz et al. (5) in non-PCOS insulin-resistant patients may be due to the higher rate of insulin infusion (120 mU/m²·min) used.

Possibly, other factors could affect insulin resistance in PCOS, such as free fatty acid and androgen levels, which are not included in these mathematical formulas. Perseghin et al. (10) found that including free fatty acid in their mathematical formula enhanced the sensitivity of QUICKI.

Ethnicity should also be considered as a contributing factor to the contradicting results of other studies.

In conclusion, the correlation of the QUICKI or HOMA indices to the results obtained by the euglycemic-hyperinsulinemic clamp technique should not be considered equivalent a priori in every insulin-resistant population because metabolic or hormonal factors as well as ethnicity may influence this correlation, and the results may not correctly represent the degree of insulin resistance.

	Footnotes

 
Abbreviations: BMI, Body mass index; G₀/I₀, fasting glucose/fasting insulin ratio; HOMA, homeostasis model of assessment; M, glucose utilization; ns, not significant; PCOS, polycystic ovary syndrome; QUICKI, quantitative insulin sensitivity check index; TT, total testosterone.

Received July 11, 2003.

Accepted December 11, 2003.

	References

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