Mini-review on insulin resistance assessment: Advances in surrogate indices and clinical applications

Abstract

Insulin resistance (IR) is widely recognized as a key contributor to metabolic disorders, and various surrogate indices have been developed to estimate IR in clinical and research settings. The hyperinsulinemic-euglycemic clamp is considered the gold standard method for assessing insulin resistance due to its precision; however, its complexity limits its widespread clinical application. Consequently, surrogate indices derived from fasting and post-load glucose and insulin levels have been developed to estimate IR, facilitating early detection and risk stratification in metabolic disorders. This mini-review discusses the clinical utility, strengths, and limitations of key IR indices, including the homeostasis model assessment of IR, quantitative insulin sensitivity check index, Matsuda index, and triglyceride-glucose index. Overall, the evidence presented to date suggests that these indices provide valuable estimates of IR in various populations. Yet, their applicability varies depending on ethnic background, disease status, and clinical setting. Integrating these indices into routine clinical practice and research could improve metabolic risk assessment and guide preventive interventions. Further investigations are necessary to refine their accuracy and determine optimal cut-off values for various populations.

Keywords: Insulin resistance; Homeostasis model assessment of insulin resistance; Quantitative insulin sensitivity check index; Matsuda index; Triglyceride-glucose index; Surrogate markers; Metabolic disorders; Diabetes; Cardiovascular disease; Risk assessment

Core Tip: Surrogate indices for insulin resistance (IR) are receiving growing validation in the international scientific literature. While gold standard methods remain the most accurate, their complexity limits clinical applicability. Indices such as the homeostasis model assessment of IR, the quantitative insulin sensitivity check index, and the Matsuda index offer valuable estimates of IR, while emerging indices like the triglyceride-glucose index are gaining attention. Further validation across diverse populations is required. Integrating these indices into routine practice may enhance metabolic risk assessment and preventive strategies.