Insulin Sensitivity Indices: a Proposal of Cut-Off Points for Simple Identification of Insulin-Resistant Subjects

Abstract

Demanding measurement of insulin sensitivity using clamp methods does not simplify the identification of insulin resistant subjects in the general population. Other approaches such as fasting- or oral glucose tolerance test-derived insulin sensitivity indices were proposed and validated with the euglycemic clamp. Nevertheless, a lack of reference values for these indices prevents their wider use in epidemiological studies and clinical practice. The aim of our study was therefore to define the cut-off points of insulin resistance indices as well as the ranges of the most frequently obtained values for selected indices. A standard 75 g oral glucose tolerance test was carried out in 1156 subjects from a Caucasian rural population with no previous evidence of diabetes or other dysglycemias. Insulin resistance/sensitivity indices (HOMA-IR, HOMA-IR2, ISI Cederholm, and ISI Matsuda) were calculated. The 75th percentile value as the cut-off point to define IR corresponded with a HOMA-IR of 2.29, a HOMA-IR2 of 1.21, a 25th percentile for ISI Cederholm, and ISI Matsuda of 57 and 5.0, respectively. For the first time, the cut-off points for selected indices and their most frequently obtained values were established for groups of subjects as defined by glucose homeostasis and BMI. Thus, insulin-resistant subjects can be identified using this simple approach.

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“…The biochemical marker of this dysfunctional state was reflected by an increased HOMA-IR, a validated index of insulin sensitivity. 18 To our knowledge, no data on the relationship between cannabis use and ED with documented vascular (penile) and endothelial (brachial) arterial damage have been reported earlier.…”

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“…However, Moltz showed recently that it is possible to determine IR using defined cut off points for glucose (102 mg/dl) and insulin (13 mU/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 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).…”

“…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 BMI, body mass index; Ch, cholesterol; DHEAS, dehydroepiandrosterone sulfate; E, estrogen; FAI, free androgen index; FG, fasting plasma glucose; FI, fasting plasma insulin; FSH, follicle-stimulating hormone; G 1 h, mean plasma glucose concentration after 1 h; G 2 h, mean plasma glucose concentration after 2 h; GIR, glucose to insulin ratio; HDL, high-density lipoprotein; HOMA-B, homeostatic model for assessment of B-cell function; HOMA-IR, homeostatic model for assessment of insulin resistance; I 1 h, mean plasma insulin after 1 h; I 2 h, mean plasma insulin after 2 h; ISI, insulin sensitivity index; LDL, low-density lipoprotein; LH, lutinizing hormone; PRL, prolactin; QUICKI, quantitative insulin sensitivity check index; SHBG, sex hormonebinding globulin; TG, triglycerides; TT, total testosterone; NS, not significant.…”

“…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 R25 kg/m 2 and was also significantly altered in patients with amenorrhea or BMI R25 kg/m 2 .…”