Diabetes mellitus (DM) has been considered recently as a heterogeneous metabolic disorder. Numerous intricate etiological processes that can differ between people can contribute to hyperglycemia. Clinical traits, treatment response, and the emergence of complications are all impacted by these mechanisms. Unfortunately, current diabetes guidelines of treatment are unable to foretell which patients will need intensified or specialized treatment before the incidence of poor metabolic control and subsequent complications. As a result, the division of T2DM (Type 2 DM) patients into different unique subgroups (clusters) can aid in the development of our approach to precision diabetes, the planning of appropriate therapies based on their pathophysiology, and the prognosis of complications with methods of their prevention. Insulin resistance state (IR) is considered essential in new clustering system, however, using fasting C-peptide or fasting insulin to calculate HOMA-IR and HOMA-B is costly. Searching for alternative methods for assessing the level of insulin resistance or beta-cell activity is important for clustering of different populations.

A metabolic risk score called “The Metabolic Score for Insulin Resistance (METS-IR)" was prescribed to measure peripheral insulin sensitivity in mankind. In 2018, Bello-Chavolla et al. reported that METS-IR is a new score that combines anthropometric measurements that can be performed easily with non-insulin fasting laboratory studies to assess insulin sensitivity and identify states of insulin resistance. In this paper we will try to give an overview on the use of METS-IR as an indicator for insulin resistance state and its importance in novel classification of diabetes in the adults