ArticleDiabetologia2015
Surrogate measures of insulin resistance: does one size fit all?
Article in Diabetologia, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Investigating the prediction potential of cholesterol, high-density lipoprotein, and glucose index surpasses TyG, AIP, and METS-IR for type 2 diabetes: a longitudinal cohort study.Frontiers in endocrinology · 2026Article
- Integrative regression modeling of insulin sensitivity, resistance, and beta-cell dysfunction in predicting female infertility: a cross-sectional NHANES study.Clinical and experimental medicine · 2025Article
- Heart Rate, Autonomic Function, and Future Changes in Glucose Metabolism in Individuals Without Diabetes: The Whitehall II Cohort Study.Diabetes care · 2019Article
- Interferon-alpha 2 but not Interferon-gamma serum levels are associated with intramuscular fat in obese patients with nonalcoholic fatty liver disease.Journal of translational medicine · 2019Article
- InsuTAG: A novel physiologically relevant predictor for insulin resistance and metabolic syndrome.Scientific reports · 2017Article
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Abstract
Insulin resistance and a relative deficiency in insulin secretion are the major pathophysiological features of impaired glucose tolerance and type 2 diabetes. Although the euglycaemic-hyperinsulinaemic clamp and the hyperglycaemic clamp are the 'gold standards', respectively, for measuring these metabolic defects, there has been an active search during the past few decades for simpler and less expensive surrogate measures of insulin resistance that can be applied more globally in epidemiological studies or large clinical trials. These surrogate markers primarily rely on plasma insulin and glucose levels measured either in the fasting state or after an oral glucose challenge. Although many of these surrogate measures correlate well with the clamp (with r values frequently as high as 0.60-0.70) within racially and ethnically homogeneous populations, it is not clear how well they can be used to compare insulin action across different groups. In this issue of Diabetologia, Ahuja et al (DOI: 10.1007/s00125-014-3414-6 ) have used these methods to compare insulin resistance in a white population in the USA with a Japanese population in Japan. The relative merits and drawbacks of applying these techniques in different populations are discussed.
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