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Prediction of Insulin Sensitivity in Nonobese Women with Polycystic Ovary Syndrome

D. Cibula, J. krha, M. Hill, M. Fanta, L. Haaková, J. VrbÍková and J. ivn

Department of Obstetrics and Gynecology (D.C., M.F., L.H., J.Z.), Charles University, Praha 2, 120 00, Czech Republic; Department of Internal Medicine (J.S.), Charles University, Praha 2, 120 00, Czech Republic; and Institute of Endocrinology (M.H., J.V.), Prague, Praha 1, 100 00, Czech Republic

Address all correspondence and requests for reprints to: David Cibula, M.D., Ph.D., Department of Obstetrics and Gynecology, Charles University, Apolináská 18, Praha 2, 120 00, Czech Republic. E-mail: david.cibula{at}iol.cz.

Abstract

Insulin resistance is a frequent (although not constant) abnormality in both obese and nonobese women with polycystic ovary syndrome (PCOS). It plays a key role in the predisposition to type 2 diabetes, which is the most important health consequence of the syndrome. Identification of patients with insulin resistance is significant both for follow-up and for therapeutic reasons. The aim of the study was to evaluate the relationships between insulin sensitivity, measured by euglycemic clamp, and both endocrine and metabolic indices and to identify the best model for predicting insulin sensitivity. A total of 41 nonobese women fulfilling the diagnostic criteria for PCOS were enrolled in the study. None of the androgens correlated with the insulin sensitivity index. All clamp parameters correlated with SHBG, triglycerides, and body mass index, although no correlation was found with waist to hip ratio or waist circumference. The close relationship between insulin sensitivity and SHBG was documented by factor analysis and by its presence in all prediction models as the most significant (or even the single) predictor of the insulin sensitivity index. In conclusion: 1) a decreased level of SHBG can be used as a single reliable parameter in the prediction of insulin sensitivity in nonobese women with PCOS; and 2) waist to hip ratio, waist circumference, and androgen concentrations have no predictive value.

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