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Screening for Abnormal Glucose Tolerance in Adolescents with Polycystic Ovary Syndrome

Divisions of Endocrinology (M.R.P., C.M.G.) and Adolescent Medicine (C.M.G., S.J.E.), Department of Medicine, and Clinical Research Program (A.I.K.), Children’s Hospital, Boston, Massachusetts 02115; Reproductive Endocrine Unit, Massachusetts General Hospital (M.R.P.), Boston, Massachusetts 02114; Department of Obstetrics and Gynecology, Pennsylvania State University College of Medicine (R.S.L.), Hershey, Pennsylvania 17003; and Division of Women’s Health, Brigham and Women’s Hospital (A.D.), Boston, Massachusetts 02115

Address all correspondence and requests for reprints to: Mark R. Palmert, M.D., Ph.D., Division of Pediatric Endocrinology and Metabolism, Rainbow Babies and Children’s Hospital, 11100 Euclid Avenue, Cleveland, Ohio 44106. E-mail: . mrp13{at}po.cwru.edu

Abstract

Insulin resistance is common in adults with polycystic ovary syndrome (PCOS). Although recent data demonstrate that insulin resistance is present in the early stages of PCOS, the prevalence of insulin resistance in adolescents with PCOS has not been determined. Likewise, the prevalence of impaired glucose tolerance (IGT) or type 2 diabetes mellitus (DM) in adolescent cohorts has not been established. In this study we sought to obtain preliminary data regarding the prevalence of IGT and DM in adolescents with PCOS and to assess the ability of screening tests to predict these abnormalities within this population.

Twenty-seven adolescents with PCOS underwent oral glucose tolerance tests. Plasma glucose and insulin levels were obtained at baseline, and glucose was measured 2 h after a 75-g glucose challenge. The 2-h plasma glucose level was used to categorize subjects as having IGT or the provisional diagnosis of DM. Eight of our 27 subjects had IGT, and 1 had previously undiagnosed DM. These abnormalities were seen among lean and obese subjects. Fasting plasma glucose levels and simple measures of insulin resistance were suboptimal predictors of IGT and DM within our cohort.

As in adults, our results indicate that adolescents with PCOS are at increased risk for IGT and DM and that the 2-h plasma glucose level after an oral glucose challenge appears to be the most reliable screening test for these abnormalities. Our results need to be corroborated by future studies that determine the prevalence of abnormalities in glucose tolerance among large populations of adolescents, both with and without PCOS. However, as DM may be preventable by lifestyle modifications, we would recommend that adolescents with PCOS undergo periodic screening for abnormal glucose tolerance using 2-h postchallenge plasma glucose levels.

POLYCYSTIC OVARY syndrome (PCOS), characterized by hyperandrogenism and chronic anovulation, is among the most common endocrine disorders affecting women of reproductive age (1, 2, 3, 4, 5). The etiology of PCOS remains elusive and may be multifactorial, involving a variable combination of ovarian and adrenal hyperandrogenism, insulin resistance, obesity, and alterations in gonadotropin secretion (1, 6, 7, 8, 9, 10, 11). The role of insulin resistance in the etiology of PCOS has recently received much attention because medications that decrease insulin resistance/hyperinsulinemia in women with PCOS often attenuate the hyperandrogenism and metabolic abnormalities present in these women (11, 12, 13, 14).

Abnormal glucose tolerance [impaired glucose tolerance (IGT) and diabetes mellitus (DM)], at least in part due to insulin resistance, is present among approximately 30–40% of adult women with PCOS (15, 16), including both obese and lean women (15, 17). These data have important health implications, as they suggest a significant risk for the development of diabetes and possibly for subsequent cardiovascular disease within this population (3, 5, 15, 18, 19).

Although recent work by Arslanian and colleagues (20, 21) demonstrates that insulin resistance is present in adolescents in the early stages of PCOS, we know of no published studies that have determined the prevalence of insulin resistance in adolescents with PCOS, nor do we know of any studies that have determined the prevalence of the IGT and DM in adolescent PCOS cohorts. A high prevalence of abnormal glucose tolerance would provide a strong rationale for aggressive counseling of these young women regarding healthy lifestyle changes, because data indicate that diabetes is preventable with early intervention (22). For routine screening for abnormal glucose tolerance among adolescents with PCOS to be practical in clinical practice, a rapid, simple method is needed. We report the results of a study designed to obtain preliminary data regarding the prevalence of IGT and DM in adolescents with PCOS and to assess the ability of rapid screening tests to detect these abnormalities in this population.

Subjects and Methods

Subjects

We studied 27 adolescents with PCOS. Sixteen were recruited from the Adolescent Medicine Division at Children’s Hospital and studied at the Brigham and Women’s Hospital (both in Boston, MA); 11 were studied at Pennsylvania State University College of Medicine (Hershey, PA). The research protocol was approved by the institutional review boards of the three participating institutions. Informed written consent (or assent) was obtained from all participants (and at least 1 parent if the subject was <18 yr of age).

The diagnosis of PCOS was based on previously reported criteria (15, 23). All subjects had chronic oligomenorrhea (6 menses/yr) and biochemical evidence of hyperandrogenism (elevated levels of either total or biologically active T) in the absence of other causes of hyperandrogenism, such as nonclassical 21-hydroxylase deficiency, hyperprolactinemia, and androgen-secreting tumors. All women were in good health and euthyroid. Most of the young women were studied before initiation of any therapy for their PCOS. In all cases, any medications known to affect sex hormone or carbohydrate metabolism were discontinued for at least month before the study (except oral contraceptives, which were stopped 3 months before study entry).

Protocol

An oral glucose tolerance test was performed after a 3-d 300-g carbohydrate diet and an overnight fast of at least 10 h. A fasting blood sample was obtained at time zero (between 0800–1000 h) for measurement of androgen, glucose, and insulin levels. Two hours after oral administration of 75 g glucose, another blood sample was obtained for the measurement of plasma glucose concentration. Assays for total T, non-SHBG-bound (bioavailable) uT, plasma glucose, and insulin were performed as previously reported (15, 23). Hirsutism was assessed using the Ferriman and Gallwey score (24); waist/hip ratios were calculated as previously reported (15, 23). SD scores for body mass index (BMI) were calculated using the method and standard curves released by the Centers for Disease Control in 2000 (http://www.cdc.gov/growthcharts/). Ethnicity data were obtained by self-report and included data from grandparents when available. Some of the data from four of the subjects studied at Penn State were reported as part of the study of prevalence and prediction of type 2 diabetes among women with PCOS (15); none of the data from the other 7 subjects in the Penn State cohort or from any of the subjects in the Boston cohort have been previously reported.

Data analysis

Determinations of glucose tolerance were made as follows: normal fasting glucose = fasting plasma glucose (FPG) <110 mg/dl (6.1 mmol/liter); impaired fasting glucose (IFG) = FPG 110 mg/dl (6.1 mmol/liter) but <126 mg/dl (7.0 mmol/liter); provisional diagnosis of diabetes = FPG 126 mg/dl (7.0 mmol/liter); normal glucose tolerance = 2-h post-oral glucose load (2-h PG) <140 mg/dl (7.8 mmol/liter); impaired glucose tolerance (IGT) = 2-h PG 140 mg/dl (7.8 mmol/liter) but <200 mg/dl (11.1 mmol/liter); and provisional diagnosis of diabetes = 2-h PG 200 mg/dl (11.1 mmol/liter) (25). Fasting glucose to insulin ratios (G:I) were calculated with glucose expressed as milligrams per dl, and insulin was expressed as microunits per ml as previously described (23). Insulin resistance (R_HOMA) was calculated according to the formula [plasma glucose (mmol/liter) x insulin (µU/ml)] ÷ 22.5 (26, 27). Results of the screening tests were compared with the designations of impaired glucose tolerance and provisional diagnosis of DM derived from applying the WHO criteria to the 2-h post-75 g plasma glucose levels (25).

Given the small sample size in the comparison groups, a nonparametric test for independent samples (Mann-Whitney U test) was used to determine statistical significance of clinical characteristics between groups. Fisher’s exact test was used to compare the results of fasting plasma glucose levels with those of the 2-h post-oral glucose load values. These statistical analyses were performed using the Complete Statistical System: Statistica from StatSoft, Inc. (Tulsa, OK). Receiver operator curves (ROC) were generated, and statistical comparisons between the curves were performed using the MedCalc statistical package (Mariakerke, Belgium). Confidence intervals for areas under ROC curves, sensitivity and specificity, and significance of differences between ROC curves were calculated using the nonparametric method (28). Values are reported as the mean ± SD; statistical significance was attributed to two-tailed P < 0.05.

Results

The clinical and laboratory characteristics of the study population as well as the subsets with normal and abnormal glucose tolerance are shown in Table 1. The ages of the 27 subjects ranged from 13.9–19.1 yr. Eight subjects had IGT, and 1 was provisionally diagnosed with type 2 diabetes (later confirmed) based on abnormal 2-h plasma glucose values. Thus, 33% of the study population had abnormal glucose tolerance. The subjects with and without normal glucose tolerance came from similar ethnic backgrounds, and no statistically significant differences were observed between the subjects in these 2 groups. Family histories of diabetes mellitus were also comparable in the 2 groups. Four of 18 of the subjects with normal glucose tolerance had a first degree relative with diabetes, and 2 of 9 of the subjects with abnormal glucose tolerance had a positive family history. There was no significant relationship between BMI and 2-h plasma glucose levels (Fig. 1). As a group, our subjects were obese, but BMIs ranged from 20.4–54.4 kg/m², and BMI SD scores for age (SD scores) ranged from 0.0–2.8. The leanest subject was among those with IGT.

View larger version (13K): [in this window] [in a new window]   Figure 1. Relationship between 2-h PG levels and BMI. Cut-off points for diagnosis of IGT (140 mg/dl or 7.8 mmol/liter) and the provisional diagnosis of DM (200 mg/dl or 11.1 mmol/liter) during oral glucose tolerance testing are noted (25 ).

View larger version (14K): [in this window] [in a new window]   Figure 2. Relationship between 2-h PG levels and screening tests of glucose intolerance. Top, FPG levels are depicted with cut-off points, along the x-axis, for diagnosis of IFG (110 mg/dl or 6.1 mmol/liter) and the provisional diagnosis of DM (126 mg/dl or 7.0 mmol/liter) (25 ). Middle, G:I ratios. Bottom, Insulin resistance measured by the homeostasis model assessment (RHOMA). In each panel, cut-off points for diagnosis of IGT (140 mg/dl or 7.8 mmol/liter) and the provisional diagnosis of DM (200 mg/dl or 11.1 mmol/liter) during oral glucose tolerance testing are noted along the y-axis (25 ).

ROC were used to analyze further the characteristics of the three screening tests (Fig. 3). A quantitative measure of the comparative utility of different tests is comparison of the area under the ROC curve for each test. In our study the area under the ROC curve for fasting plasma glucose was 0.796 [95% confidence interval (CI), 0.598–0.925], that for the fasting G:I ratio was 0.750 (95% CI, 0.547–0.895), and that for R_HOMA was 0.836 (95% CI, 0.644–0.949). None of these areas was significantly greater than another.

View larger version (19K): [in this window] [in a new window]   Figure 3. ROC. For each screening test, sensitivity is plotted against 100-specificity. The ideal test would have 100% sensitivity and 100% specificity and reach the upper left corner of the graph; a test with no predictive value would lie along the diagonal between the lower left corner and the upper right corner. To facilitate comparison, the lower right panel of the figure contains the three individual ROC curves superimposed on each other. These curves, along with Fig. 2, facilitate assessment of the sensitivity (Sens) and specificity (Spec) of every value obtained from the screening tests. For each test, examples of data points with associated Sens and Spec are displayed to illustrate the characteristics of the test; these data points are not proposed as cut-offs between normal and abnormal results. To convert milligrams per dl to millimoles per liter, divide by 18.

Discussion

Our data indicate that the high prevalence (30–40%) of glucose intolerance and type 2 diabetes in adults with PCOS (15, 16) is also present in adolescents with this disorder. Moreover, as in adult series (15, 17), these abnormalities are present in both lean and obese subjects. Even though impaired glucose tolerance and type 2 diabetes are becoming more common in adolescents (30), the prevalence of abnormal glucose tolerance in this population is striking and probably exceeds estimates of background prevalence that can be gleaned from past population studies (30, 31). Based on our results, prospective, controlled studies are clearly warranted to determine the prevalence of abnormal glucose tolerance in adolescents, both with and without PCOS, and to establish the PCOS-specific prevalence of IGT and DM in adolescents. Although we did not find ethnic differences between the adolescents with and without abnormal glucose tolerance, such future studies will also permit further investigation of ethnicity-specific prevalence rates and of the utility of the various screening tests within specific ethnic groups.

As IGT and DM in adolescents probably stem at least in part from insulin resistance, our prevalence data are consistent with the finding that insulin resistance is present at the early stages of PCOS (20, 21). Important insights regarding the role that insulin resistance plays in the pathogenesis of PCOS will derive from future studies that establish the PCOS-related prevalence of insulin resistance among adolescents at the time of diagnosis. Even more insight may derive from the assessment of insulin resistance before a diagnosis of PCOS is established within a predisposed population, such as younger siblings of adolescents with PCOS or in young women with premature adrenarche (11, 32, 33, 34).

The American Diabetes Association has recommended that practitioners consider screening adolescents with PCOS for IGT and/or type 2 DM (30). Our data and those of others (20, 21) indicate that such widespread screening is indeed warranted. This is especially important because recent data suggest that effects of insulin resistance and attendant cardiovascular risk factors can be mitigated (34) and that DM may be preventable (22) by early intervention in affected individuals. However, for screening to be practical in clinical practice, one must identify a simple technique that can be used for the screening of large populations of adolescents with PCOS for IGT and/or DM.

We assessed the utility of FPG levels as a simple and convenient screen for abnormal glucose tolerance in adolescents with PCOS. In our study population, FPG levels did not reliably predict IGT or DM. The accepted cut-off values for fasting plasma glucose (110 mg/dl or 6.1 mmol/liter) (25) were too insensitive. Although our goal was not to define cut-off points, inspection of Figs. 2 and 3 reveals that no other candidate cut-off values are apparent. A lower value of 86 mg/dl (4.8 mmol/liter) or more, for example, provided only 78% sensitivity and 72% specificity (Fig. 3). Although FPG levels have been recommended for initial screening (25, 30), other groups have also found that FPG is a poor predictor of abnormal glucose tolerance in women with PCOS (15, 16, 20).

Although these tests were not designed to screen for IGT or DM, we also assessed the ability of simple measures of insulin resistance (G:I ratio and R_HOMA) to predict IGT and/or DM in our population. The results were similarly disappointing. A value of 4.5 for the G:I ratio, which has been proposed for adults with PCOS (23), had too little specificity, and no other values emerged as good candidate cut-offs. As shown in Fig. 3, ROC analysis suggests a value of 2.3, but this provided only 67% sensitivity and 78% specificity for the prediction of abnormal glucose tolerance. These results are not surprising, because IGT and type 2 DM are the result of a variable combination of insulin resistance and ß-cell dysfunction (20, 29, 35, 36), and not all individuals with insulin resistance have IGT or DM. It is also possible that different values of the G:I ratio may serve as better predictors of IGT or DM among distinct ethnic groups. For all of these reasons, measures of insulin resistance may well be poor predictors of IGT and DM in the general population of adolescents with PCOS.

Use of the G:I ratio in adolescents may also be confounded by the physiological insulin resistance that occurs during puberty (37, 38, 39). We do not have direct measurements of insulin resistance in our cohort. However, using the adult G:I cut-off of 4.5 in our subjects, 24 of the 27 young women met criteria for insulin resistance. This is an exceedingly high rate of insulin resistance and may well be an incorrect estimate, which suggests that one may need to apply different screening tests and/or cut-offs when assessing insulin resistance in adolescents with PCOS compared with adults (23).

The R_HOMA was the most promising predictor of IGT and DM in our subjects. The number of subjects in our study was not large enough to optimally characterize each test or for detailed statistical comparison among them (40). Nevertheless, in the ROC analysis, the curves from FPG values and the G:I ratio overlapped and would probably not be distinguishable even with a larger number of subjects. The R_HOMA may have proven to be statistically superior had our sample size been larger (see Fig. 3). Nonetheless, even this test was not ideal. In using possible cut-off points as a means of evaluating the test, a value of 8.2, for example, yielded only a 78% sensitivity and 89% specificity among adolescents with PCOS.

Our results suggest that adolescents with PCOS have an increased risk of IGT and DM. However, fasting screening tests may not reliably detect these abnormalities. Thus, as has been found for adults with PCOS (15, 16), our data indicate that the 2-h plasma glucose level obtained during an oral glucose challenge is the most reliable screening test. We, therefore, recommend that adolescents with PCOS undergo periodic screening for abnormal glucose tolerance using 2-h PG levels.

Acknowledgments

We thank the clinical and laboratory staff of the participating General Clinical Research Centers for their expert care of our research subjects and samples. We also thank the adolescents and their families who participated in this study, and Dr. Joseph I. Wolfsdorf, who provided helpful suggestions and critical review of the manuscript.

Footnotes

This work was supported by the NIH and the Maternal and Child Health Bureau (Grants K23-RR-15544, M01-RR-2172, M01-RR-02635, M01-RR-10732, R01-DK-40605, U54-HD-34449, K24-HD-01476, and T71-MC00009-09-S1-RO).

¹ Present address: Division of Pediatric Endocrinology and Metabolism, Rainbow Babies and Children’s Hospital, Cleveland, Ohio 44106.

² Present address: Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Medical School, Chicago, Illinois 66011.

Abbreviations: BMI, Body mass index; CI, confidence interval; DM, diabetes mellitus; FPG, fasting plasma glucose; G:I, fasting glucose to insulin ratios; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; PCOS, polycystic ovary syndrome; 2-h PG, 2-h post-oral glucose load; R_HOMA, insulin resistance; ROC, receiver operator curves.

Received September 10, 2001.

Accepted November 8, 2001.

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