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Context Insulin resistance (IR) and abnormal insulin secretion play a key role for the development of type 2 diabetes mellitus (DM). Aims We investigated the surrogate markers of IR, i.e., Homeostasis Model Assessment (HOMA), Quantitative Insulin Sensitivity Check Index (QUICKI), McAuley, and Fasting Insulin Resistance Index (FIRI) in type 2 DM patients. Also, fasting insulin (FI) levels were estimated in type 2 diabetics. Further, the correlation of FI with other surrogate markers of IR in type 2 DM was done. Settings and Design A hundred newly diagnosed patients with type 2 DM from Malwa population, Punjab, were considered for evaluation. Another 100 healthy individuals (age and sex-matched) were examined as controls. Methods and Material Fasting blood glucose, FI, and lipid profile were estimated, and IR was calculated using McAuley index (McA), HOMA, QUICKI, and FIRI. Statistical Analysis Used The statistical analysis was performed on the above-mentioned clinical interpretations. The Cohen’s kappa test was used to affirm the agreement. Results FI levels in patients with type 2 diabetes were significantly higher (20.8 ± 9.05 µIU/L) than controls (7.93 ± 1.01 µIU/L). IR by surrogate markers was found significant in the study group. The 76% patients with type 2 diabetes ended up as resistant to insulin by FI measurement, almost equivalent to McA, 80%; HOMA, 88%; FIRI, 88%; and QUICKI, 90%. A notable correlation was highlighted between FI and McA manifesting IR (p < 0.01, r = −0.85). We calculated the statistical correlation of FI with HOMA, QUICKI, and FIRI indices (p < 0.01, r = 0.93; p < 0.01 r = −0.92; and p < 0.01, r = +0.93, respectively). The agreement visible from Cohen’s kappa test also affirms the same (k = 0.9 for McA). Conclusion We concluded that all the surrogate markers for IR were specific when compared with FI, but in terms of sensitivity McA was found to be more sensitive as it includes markers of dyslipidemia, which is the precipitating factor of metabolic derangements so as the IR in type 2 DM.

The use of tacrolimus (Tac) may be involved in the development of new-onset diabetes after transplantation (NODAT) in a dose-related manner. This study aimed to evaluate the effects of a standard twice-daily formulation of Tac (TacBID) vs. the once-daily slow-release formulation (TacOD) on the basal insulin resistance indexes (Homa and McAuley), and related metabolic parameters, in a cohort of kidney transplant patients. We retrospectively evaluated 20 stable renal transplant recipients who were switched from TacBID to TacOD. Blood levels of Tac were analyzed at one-month intervals from 6 months before to 8 months after conversion. Moreover, Homa and McAuley indexes, C-peptide, insulin, HbA1c, uric acid, triglycerides, low-density lipoprotein (LDL) and high-density lipoprotein (HDL)-cholesterol serum levels and their associations with Tac levels were evaluated. We observed a significant decrease in Tac exposure (8.5 ± 2 ng/mL, CV 0.23 vs. 6.1 ± 1.9 ng/mL, CV 0.31, TacBID vs. TacOD periods, p < 0.001) and no significant changes in Homa (1.42 ± 0.4 vs. 1.8 ± 0.7, p > 0.05) and McAuley indexes (7.12 ± 1 vs. 7.58 ± 1.4, p > 0.05). Similarly, blood levels of glucose, insulin, HbA1c, lipids, and uric acid were unchanged between the two periods, while C-peptide resulted significantly lower after conversion to TacOD. These data suggest that in kidney transplant recipients, reduced Tac exposure has no significant effects on basal insulin sensitivity indexes and metabolic parameters.

Background : Insulin resistance (IR) is a collective clinical entity that exacerbates metabolic syndrome (MetS). As the gold-standard test to quantify IR involves intravenous insulin loading and repeated blood glucose monitoring, many indices have been developed for IR assessment for convenience. This study tested the ideal cut-off values and clinical utility of IR indices in identifying MetS. Methods : We recruited 150 subjects, 75 MetS patients and 75 healthy controls, then obtained written informed consent to participate in this study. We collected fasting blood samples for glucose and lipid profiles and calculated nineteen indices of IR and insulin secretion using validated formulae. We determined the precision of these IR indices using the area under the curve (AUC) in a receiver operating characteristic analysis. Results : Subjects with MetS have significantly higher IR coupled with lower insulin sensitivity and beta-cell function than controls. Among the surrogate markers of IR tested, the homeostatic model assessment of insulin resistance (HOMA-IR), HOMA-adiponectin (HOMA-AD), triglyceride-glucose (TyG) index, HOMA-1%S (insulin sensitivity), quantitative insulin sensitivity check index (QUICKI), McAuley index, single-point insulin sensitivity estimator (SPISE), and HOMA-2%B (beta-cell function) showed the highest AUC values for detecting MetS. Conclusion : Our study results suggest that the ideal cut-off and AUC values identified for HOMA-IR, HOMA-AD, the TyG index, HOMA-1%S, QUICKI, the McAuley index, SPISE, and HOMA-2%B offer a clinical approach to the early detection and risk stratification for MetS among people in southern India.

BackgroundMetabolic syndrome (MS) is known to increase the risk of various cardiometabolic diseases and in-sulin resistance (IR) has known to have central role in the development of MS. Many surrogate indices of IR have been proposed and the detection of MS might be a suitable model for assessing the accuracy of surrogate indices. The aims of our study are to invest the most appropriate index by assessment of the diagnostic capacity of IR among each surrogate index and identifying cut-off values for discriminating uncomplicated MS in Korean adults.MethodsA cross-sectional study was performed, assessing 294 Korean adults, 85 of whom were diagnosed with uncomplicated MS. The sensitivities and specificities of five surrogate IR indices were compared to discriminate MS from healthy subjects; these included fasting serum insulin, homeostasis model assessment-insulin resistance index, quantitative insulin sensitivity check index, McAuley index, and Disse index. Correlations between each index value were assessed using Pearson's and Spearman's correlation methods.ResultsThe McAuley index showed the highest area under the curve (0.85), specificity (86.12%), accuracy (82.31%), positive predictive value (68.13%), and negative predictive value (88.67%) to distinguish MS, with a cut-off point of 5.3 defined. Correlation coefficients of the five indices showed that the McAuley index had the strongest correlation with IR.ConclusionThe McAuley index showed the best accuracy in the detection of MS as a surrogate marker of IR. To establish more effective and accurate standards of measuring IR, comprehensive and multi-scaled studies are required.

Background: Insulin resistance (IR) is a collective clinical entity that exacerbates metabolic syndrome (MetS). As the gold-standard test to quantify IR involves intravenous insulin loading and repeated blood glucose monitoring, many indices have been developed for IR assessment for convenience. This study tested the ideal cut-off values and clinical utility of IR indices in identifying MetS. Methods: We recruited 150 subjects, 75 MetS patients and 75 healthy controls, then obtained written informed consent to participate in this study. We collected fasting blood samples for glucose and lipid profiles and calculated nineteen indices of IR and insulin secretion using validated formulae. We determined the precision of these IR indices using the area under the curve (AUC) in a receiver operating characteristic analysis. Results: Subjects with MetS have significantly higher IR coupled with lower insulin sensitivity and beta-cell function than controls. Among the surrogate markers of IR tested, the homeostatic model assessment of insulin resistance (HOMA-IR), HOMA-adiponectin (HOMA-AD), triglyceride-glucose (TyG) index, HOMA-1%S (insulin sensitivity), quantitative insulin sensitivity check index (QUICKI), McAuley index, single-point insulin sensitivity estimator (SPISE), and HOMA-2%B (beta-cell function) showed the highest AUC values for detecting MetS. Conclusion: Our study results suggest that the ideal cut-off and AUC values identified for HOMA-IR, HOMA-AD, the TyG index, HOMA-1%S, QUICKI, the McAuley index, SPISE, and HOMA-2%B offer a clinical approach to the early detection and risk stratification for MetS among people in southern India. [ABSTRACT FROM AUTHOR]

Background: Though insulin resistance (IR) is common in polycystic ovary syndrome (PCOS), there is no agreement as to what surrogate method of assessment of IR is most reliable. Subjects and methods: In 478 women with PCOS, we compared methods based on fasting insulin and either fasting glucose (HOMA-IR and QUICKI) or triglycerides (McAuley Index) with IR indices derived from glucose and insulin during OGTT (Belfiore, Matsuda and Stumvoll indices). Results: There was a strong correlation between IR indices derived from fasting values HOMA-IR/QUICKI, r = −0.999, HOMA-IR/McAuley index, r = −0.849 and between all OGTT-derived IR indices (e.g. r = −0.876, for IRI/Matsuda, r = −0.808, for IRI/Stumvoll, and r = 0.947, for Matsuda/Stumvoll index, P < 0.001 for all), contrasting with a significant (P < 0.001), but highly variable correlation between IR indices derived from fasting vs OGTT-derived variables, ranging from r = −0.881 (HOMA-IR/Matsuda), through r = 0.58, or r = −0.58 (IRI/HOMA-IR, IRI/QUICKI, respectively) to r = 0.41 (QUICKI/Stumvoll), and r = 0.386 for QUICKI/Matsuda indices. Detailed comparison between HOMA-IR and IRI revealed that concordance between HOMA and IRI was poor for HOMA-IR/IRI values above 75th and 90th percentile. For instance, only 53% (70/132) women with HOMA-IR >75th percentile had IRI value also above 75th percentile. There was a significant, but weak correlation of all IR indices with testosterone concentrations. Conclusions: Significant number of women with PCOS can be classified as being either insulin sensitive or insulin resistant depending on the method applied, as correlation between various IR indices is highly variable. Clinical application of surrogate indices for assessment of IR in PCOS must be therefore viewed with an extreme caution.

Background: Hyperinsulinaemia is emerging as an independent risk factor for metabolic disease, but diagnostic measures are limited. It is plausible that insulin resistance measures, such as homeostatic model assessment (HOMA) type 2 variants, may model hyperinsulinaemia, but repeatability data are limited. Kraft and Hayashi insulin response patterns may not only add value in diagnosing hyperinsulinaemia, but also lack suitable repeatability data. Aim: The aim of this study was to investigate the repeatability of insulin response patterns, and fasting and dynamic measures of insulin resistance, and to determine whether these latter measures can predict the insulin response pattern. Setting: This study was conducted at Auckland University of Technology Millennium Institute’s sports performance laboratories. Methods: Oral glucose (100 g) tolerance tests were conducted weekly on eight people. Six people completed four tests, while two completed at least two tests. Each test assessed insulin resistance and response patterns. Insulin resistance measures included fasting tests (HOMA2, McAuley Index) and a dynamic test (oral glucose insulin sensitivity [OGIS]). The insulin response patterns were assessed with both Kraft and Hayashi methodologies. Repeatability characteristics of ordinal variables were assessed by Bland and Altman methods, while Fleiss’ κ was applied to categorical variables. Results: Fasting measures of insulin resistance recorded poor repeatability (HOMA2) or poor sensitivity (McAuley Index) compared to the dynamic measure (OGIS). Kraft insulin response patterns were more repeatable compared to Hayashi patterns, based on a combination of Fleiss’ κ (0.290 vs. 0.186,) p-value (0.15 vs. 0.798) and 95% confidence intervals. Conclusions: Both hyperinsulinaemia and insulin resistance should be dynamically assessed with a multi-sampled oral glucose tolerance test. Further investigations are required to confirm a preferred methodology.

Aims The study aim was to determine the correlation of several surrogate estimates of insulin resistance with a direct measure of insulin action and the ability of these estimates to identify insulin resistant persons. Methods Retrospective analysis of 454 apparently healthy individuals studied in a clinical research center. The correlations between 11 surrogate estimates of insulin resistance, using either fasting or post-oral glucose challenge values, and a direct measure of insulin-mediated glucose uptake (SSPG concentration during the Insulin Suppression Test) were determined as well as the ability of the surrogate estimates to identify insulin resistant individuals. Results All surrogate estimates were significantly (P < .001) correlated with SSPG concentrations and successfully identified insulin resistant persons. These relationships were of lesser magnitude when estimates were based on fasting data, with the exception of the McAuley index—derived from fasting data, but resembling post-glucose challenge estimates. Moreover, correlation with SSPG concentration, and positive identification of insulin resistance, varied considerably among estimates. Conclusion All 11 surrogate estimates of insulin resistance significantly correlated with insulin-mediated glucose disposal and identified insulin resistant persons with a reasonable degree of sensitivity and specificity. For identification of insulin resistant individuals, indices based on post-glucose challenge measurements performed better than those based on fasting measurements, with the exception of McAuley index. The quantitative information derived from this analysis should help investigators select the surrogate marker of insulin resistance best suited for their study. [ABSTRACT FROM AUTHOR]

Background: Fasting indices of glucose-insulin-metabolism are an easy and affordable tool to assess insulin resistance. We aimed to establish reference ranges for fasting insulin indices that reflect age-dependent variation over the entire life span and subsequently test their clinical application regarding the prediction of glycemic deterioration in children., Methods: We calculated age- and puberty-dependent reference values for HOMA-IR, HOMA2-IR, HOMA-β, McAuley index, fasting insulin, and fasting glucose from 6994 observations of 5512 non-obese healthy subjects aged 5-80 years. Applying those references, we determined the prevalence of insulin resistance among 2538 subjects with obesity. Furthermore, we investigated the intraindividual stability and the predictive values for future dysglycemia of these fasting indices in 516 children and adolescents with obesity up to 19 years of follow-up. We validated the results in three independent cohorts., Findings: There was a strong age-dependent variation of all indices throughout the life span, including prolonged recovery of pubertal insulin resistance and a subsequent continuous increase throughout adulthood. Already from age 5 years onwards, >40% of children with obesity presented with elevated parameters of insulin resistance. Applying newly developed reference ranges, insulin resistance among children with obesity doubled the risk for future glycemic deterioration (HOMA-IR HR 1.88 (95% CI 1.1-3.21)), fasting insulin HR 1.89 (95% CI 1.11-3.23). In contrast, fasting glucose alone was not predictive for emerging dysglycemia in children with obesity (HR 1.03 (95% CI 0.62-1.71)). The new insulin-based thresholds were superior to fasting glucose and HbA1c in detecting children eventually manifesting with dysglycemia in prospective analyses., Interpretation: The variation of fasting glucose-insulin-metabolism across the life span necessitates age-specific reference ranges. The improved prediction of future glycemic deterioration by indices based on fasting insulin beyond simple glucose measures alone could help to stratify risk characteristics of children with obesity in order to guide patient-tailored prevention and intervention approaches., Funding: German Research Foundation (DFG)-through SFB 1052, project number 209933838, subproject C5; Federal Ministry of Education and Research, Germany; European Union-European Regional Development Fund; Free State of Saxony. The German Diabetes Association, the CarbHealth consortium (01EA1908B). EU-IMI2-Consortium SOPHIA (grant agreement No 875534), German Center for Diabetes Research (DZD), grant number 82DZD14E03., Competing Interests: MB received honoraria and consulting fees from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis and Sanofi and is part of the advisory board from Boehringer-Ingelheim. All other authors have no conflicts of interest relevant to this article to disclose., (© 2023 The Author(s).)

Background: To investigate importance of fasting insulin (FI) as a diagnostic test for insulin resistance (IR) and to compare with other standard methods McAuley (McA), HOMA and QUICKI indices in Diabetes Mellitus (DM). Method: 42 diabetic patients who have been already diagnosed were used in our study. They were investigated for fasting blood glucose (FBS), FI, LDL, Triglycerides (TG), total cholesterol (TC) and HDL levels. IR was calculated by McA, HOMA, QUICKI indices and by FI. Results: 81% of patients were insulin resistant by McA and FI in our study group. 93% were detected as insulin resistant by HOMA and QUICKI. IR by FI was further compared with HOMA and QUICKI and 81% of patients were found to be insulin resistant by FI, HOMA and QUICKI. Results showed that there was a significant correlation between FI and McA in expressing IR in our study group (p

We investigated the degree of genetic association between insulin resistance (IR) with type 2 diabetes mellitus (DM) and abnormalities in lipid metabolism in 42 patients. IR was assessed by fasting insulin test (FI), McAuley (McA), HOMA and QUICKI methods. IR was detected in 34 (81%) patients by FI, McA and in 39 (93%) patients by HOMA and QUICKI. 26 (62%) patients had family history of DM and 23 (89%) of them displayed IR by FI & McA. 24 of them (92%) displayed IR by HOMA and QUICKI. Our results suggest that association between the family history of DM and IR were statistically significant by chi-square test (P

Objective: To estimate the prevalence of insulin resistant syndrome (IRS) among newly diagnosed patients with type 2 diabetes and to test their validity against two indices of insulin resistance (IR). Materials and Methods: Prevalence of IRS was estimated according to the criteria used by ATP III in newly diagnosed type 2 diabetic patients. Sensitivity and specifi city of the ACE criteria were calculated against two indices of IR namely fasting insulin (FI) level > 12 mU/l and McAuley index (McA) < 5.8. [McA= exp [2.63--0.28 ln(insulin in mU/l) -- 0.31 ln(triglycerides in mmol/l)]. Results: 35.7% of patients had IRS by ATP III criteria. 64.3% of patients were insulin resistant by FI and McA in each index. In patients who had IRS with ATP criteria, 80% and 86.6% were found to have McA and FI in the insulin resistant range. Out of the patients who were resistant by McA, only 40.6% had IR by ACE criteria and 93% had shown IR by FI. Out of all patients who did not fulfi ll the ATP III for IR, 74% and 59% were detected as having IR by fasting insulin and McA respectively. Sensitivity of the ACE criteria when tested against the FI and McA were 37.5% and 40.6%, specifi city were 70% and 80%, respectively. Conclusions: IRS was common among the newly diagnosed patients with type 2 diabetes. ACE criteria showed an acceptable specifi city but lack adequate sensitivity when compared with the two Indices of insulin resistance. More valid and clinically useful criteria should be available for the accurate diagnosis of IRS in clinical practice. [ABSTRACT FROM AUTHOR]

Objective To observe the accuracy of several indices in assessing insulin resistance (IR) in the overweight/ obesity population and to find more desirable cut-off point of IR. Methods This study involved 406 overweight obesity participants without overt diabetes. Homeostasis model assessment of insulin resistance ( HOMA-IR) index, Quantitative insulin sensitivity check index (QUICKI) and McAuley index ( McA index) were calculated and compared with fasting insulin levels (FINS) (⩾ 12 mIU/L, which was the reference criteria for determined IR) . Results Of the 406 participants, 114 cases of IR and 292 cases of non-IR were found. When using HOMA-IR⩾2.6 as the cut-off point of IR, there were 138 cases of IR and 268 cases of non-IR. The sensitivity was 94. 74% and the specificity was 89. 73%. Youden index was 0. 84. When using HOMA-IR⩾2.68 as the cut-off point, the sensitivity and specificity was 93.3% and 92.9% , respectively. Youden index was elevated to 0. 86. When using QUICKI⩽0.339 as the cut-off point of IR, there were 210 cases of IR and 196 cases of non-IR. The sensitivity was 100% and the specificity was 67.12%. Youden index was 0.67. When using QUICKI⩽0.335 as the cut-off point, the sensitivity and specificity was 79. 8% and 99. 0%, respectively. Youden index was increased to 0. 79. When using McA⩽5.8 as the cut-off point of IR, there were 403 cases of IR and 3 cases of non-IR. The sensitivity was 98.25% and the specificity was only 0.34% . Youden index was -1.41. When using McA⩽4.29 as the cut-off point, the sensitivity and specificity was 78.0% and 82.9%, respectively. Youden index was ｉｎｃｒｅａｓｅｄ ｔｏ ０．６１． Ｃｏｎｃｌｕｓｉｏｎｓ　ＨＯＭＡ-ＩＲ ｉｓ ｍｏｒｅ ａｃｃｕｒａｔｅ ｉｎ ｄｅｔｅｃｔｉｎｇ ＩＲ ｉｎ ｏｖｅｒｗｅｉｇｈｔ／ｏｂｅｓｅ ｐｏｐｕｌａｔｉｏｎ. Ｔｈｅ ｔｈｒｅｓｈｏｌｄｓ ｏｆ ｔｈｅｓｅ ｔｈｒｅｅ ｉｎｄｉｃｅｓ ｉｎ ｏｖｅｒｗｅｉｇｈｔ／ｏｂｅｓｅ ｐｏｐｕｌａｔｉｏｎ ｓｈｏｕｌｄ ｂｅ ａｄｊｕｓｔｅｄ ａｐｐｒｏｐｒｉａｔｅｌｙ ｃｏｎｓｉｄｅｒｉｎｇ ｔｈｅ ｉｎｆｌｕｅｎｃｅ ｏｆ ｏｂｅｓｉｔｙ ａｎｄ ｌｉｐｉｄ ｍｅｔａｂｏｌｉsｍ ｏｎ ｉｎｓｕｌｉｎ ｌｅｖｅｌｓ ｔｏ ｉｎｃｒｅａｓｅ ｔｈｅ ａｃｃｕｒａｃｙ ｉｎ ｅｖａｌｕａｔｉｎｇ ＩＲ. [ABSTRACT FROM AUTHOR]

Context Insulin resistance (IR) and abnormal insulin secretion play a key role for the development of type 2 diabetes mellitus (DM). Aims We investigated the surrogate markers of IR, i.e., Homeostasis Model Assessment (HOMA), Quantitative Insulin Sensitivity Check Index (QUICKI), McAuley, and Fasting Insulin Resistance Index (FIRI) in type 2 DM patients. Also, fasting insulin (FI) levels were estimated in type 2 diabetics. Further, the correlation of FI with other surrogate markers of IR in type 2 DM was done. Settings and Design A hundred newly diagnosed patients with type 2 DM from Malwa population, Punjab, were considered for evaluation. Another 100 healthy individuals (age and sex-matched) were examined as controls. Methods and Material Fasting blood glucose, FI, and lipid profile were estimated, and IR was calculated using McAuley index (McA), HOMA, QUICKI, and FIRI. Statistical Analysis Used The statistical analysis was performed on the above-mentioned clinical interpretations. The Cohen's kappa test was used to affirm the agreement. Results FI levels in patients with type 2 diabetes were significantly higher (20.8 ± 9.05 µIU/L) than controls (7.93 ± 1.01 µIU/L). IR by surrogate markers was found significant in the study group. The 76% patients with type 2 diabetes ended up as resistant to insulin by FI measurement, almost equivalent to McA, 80%; HOMA, 88%; FIRI, 88%; and QUICKI, 90%. A notable correlation was highlighted between FI and McA manifesting IR ( p < 0.01, r = -0.85). We calculated the statistical correlation of FI with HOMA, QUICKI, and FIRI indices ( p < 0.01, r = 0.93; p < 0.01 r = -0.92; and p < 0.01, r = +0.93, respectively). The agreement visible from Cohen's kappa test also affirms the same ( k = 0.9 for McA). Conclusion We concluded that all the surrogate markers for IR were specific when compared with FI, but in terms of sensitivity McA was found to be more sensitive as it includes markers of dyslipidemia, which is the precipitating factor of metabolic derangements so as the IR in type 2 DM., Competing Interests: Conflict of Interest None declared. Ethical Approval The approval from the Ethical Committee of the Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, India, was taken before conducting the present study. Source(s) of Financial Support None., (The Indian Association of Laboratory Physicians. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: This study aimed to identify the gender-specific characteristics of the surrogate measures of insulin resistance and to establish valid cut-off values for metabolic abnormalities in a representative sample in Korea., Methods: Data were collected from the datasets of the Korean National Health and Nutrition Examination Survey between 2007 and 2010. The total number of eligible participants was 10,997. We used three measures of insulin resistance: the homeostasis model assessment-insulin resistance (HOMA-IR), McAuley index, and triglyceride and glucose (TyG) index. The estimated cut-off values were determined using the highest score of the Youden index., Results: The area under the curve (AUC) of the HOMA-IR, McAuley index, and TyG index were 0.737 (95% confidence interval [CI], 0.725-0.750), 0.861 (95% CI, 0.853-0.870), and 0.877 (95% CI, 0.868-0.885), respectively. The cut-off values of the HOMA-IR were 2.20 in men, 2.55 in premenopausal women, and 2.03 in postmenopausal women, and those of the McAuley index were 6.4 in men and 6.6 in premenopausal and postmenopausal women. For the TyG index, the cut-off values were 4.76 in men and 4.71 in premenopausal and postmenopausal women., Conclusion: In conclusion, the present study provides the valid cut-off values of the indirect surrogate measures of insulin sensitivity. These values may be used as reference for insulin sensitivity in a clinical setting and may provide a simple and supplementary method for identifying populations at risk of insulin resistance., Competing Interests: Disclosure: The authors have no potential conflicts of interest to disclose.

Background: Though insulin resistance (IR) is common in polycystic ovary syndrome (PCOS), there is no agreement as to what surrogate method of assessment of IR is most reliable., Subjects and Methods: In 478 women with PCOS, we compared methods based on fasting insulin and either fasting glucose (HOMA-IR and QUICKI) or triglycerides (McAuley Index) with IR indices derived from glucose and insulin during OGTT (Belfiore, Matsuda and Stumvoll indices)., Results: There was a strong correlation between IR indices derived from fasting values HOMA-IR/QUICKI, r  = -0.999, HOMA-IR/McAuley index, r  = -0.849 and between all OGTT-derived IR indices (e.g. r  = -0.876, for IRI/Matsuda, r  = -0.808, for IRI/Stumvoll, and r  = 0.947, for Matsuda/Stumvoll index, P  < 0.001 for all), contrasting with a significant ( P  < 0.001), but highly variable correlation between IR indices derived from fasting vs OGTT-derived variables, ranging from r  = -0.881 (HOMA-IR/Matsuda), through r  = 0.58, or r  = -0.58 (IRI/HOMA-IR, IRI/QUICKI, respectively) to r  = 0.41 (QUICKI/Stumvoll), and r  = 0.386 for QUICKI/Matsuda indices. Detailed comparison between HOMA-IR and IRI revealed that concordance between HOMA and IRI was poor for HOMA-IR/IRI values above 75th and 90th percentile. For instance, only 53% (70/132) women with HOMA-IR >75th percentile had IRI value also above 75th percentile. There was a significant, but weak correlation of all IR indices with testosterone concentrations., Conclusions: Significant number of women with PCOS can be classified as being either insulin sensitive or insulin resistant depending on the method applied, as correlation between various IR indices is highly variable. Clinical application of surrogate indices for assessment of IR in PCOS must be therefore viewed with an extreme caution., (© 2018 The authors.)