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Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Oct 16, 2025; 13(29): 108380
Published online Oct 16, 2025. doi: 10.12998/wjcc.v13.i29.108380
Mini-review on insulin resistance assessment: Advances in surrogate indices and clinical applications
Kengo Moriyama
Kengo Moriyama, Department of Clinical Health Science, Tokai University School of Medicine, Hachioji 1920032, Tokyo, Japan
Author contributions: Moriyama K conceived the review topic, conducted the literature search, synthesized the findings, and wrote the manuscript.
Conflict-of-interest statement: There are no conflicts of interest to declare.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Kengo Moriyama, MD, PhD, Professor, Department of Clinical Health Science, Tokai University School of Medicine, 1838 Ishikawa-machi, Hachioji 1920032, Tokyo, Japan. kengomoriyama@tokai.ac.jp
Received: April 13, 2025
Revised: May 24, 2025
Accepted: August 8, 2025
Published online: October 16, 2025
Processing time: 137 Days and 23.9 Hours
Core Tip

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.