Key result
Prediabetes is linked to ~3.9-fold higher type 2 diabetes risk versus normoglycaemia.
Why the study?
Prediabetes is heterogeneous across subtypes defined by impaired fasting glucose, impaired glucose tolerance, or HbA1c, each carrying different risks of progression to type 2 diabetes. The benefit of adding insulin secretion and sensitivity indices to risk stratification across these subtypes warranted evaluation.
Does integrating insulin secretion (IGI) and insulin sensitivity (ISI) indices with conventional glycaemic subtypes (IFG, IGT, HbA1c) improve long-term type 2 diabetes risk stratification in Korean adults with normoglycaemia and prediabetes?
Cohort (n=7,186)
Yes
Does integrating insulin secretion (IGI) and insulin sensitivity (ISI) indices with conventional glycaemic subtypes (IFG, IGT, HbA1c) improve long-term type 2 diabetes risk stratification in Korean adults with normoglycaemia and prediabetes?
Answers are grounded in this paper and cite their sources.
Integrating OGTT-derived insulin secretion and sensitivity indices with conventional IFG, IGT, and HbA1c prediabetes criteria reveals marked heterogeneity in diabetes progression and regression, identifying individuals meeting multiple criteria or with dual physiological impairment as highest priority for early preventive intervention.
Aims/hypothesis Prediabetes is heterogeneous, with subtypes defined by impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or HbA 1c , each with different risks of progression to type 2 diabetes. We compared progression across these subtypes, and evaluated the benefit of adding insulin secretion and sensitivity to risk stratification. Methods We analysed 7186 Korean adults aged 40–69 years from the community-based Korean Genome and Epidemiology Study, who were followed for up to 20 years with biennial (every 2 years) oral glucose tolerance tests and HbA 1c . Prediabetes was classified as IFG, IGT or HbA 1c -defined, and further stratified by insulinogenic index (IGI) and insulin sensitivity index (ISI). Cox regression was used to estimate diabetes risk, and multistate Markov models were used to assess annual transition probabilities and time spent in each state. Results Compared with normoglycaemia, the adjusted hazard ratios (aHRs) were 5.84 (95% CI 5.03, 6.79) for IFG, 4.60 (95% CI 4.17, 5.07) for IGT, and 4.68 (95% CI 4.22, 5.19) for HbA 1c -defined prediabetes. The risk increased stepwise with the number of criteria met: the aHRs were 3.10 (95% CI 2.81, 3.41) for one criterion, 7.33 (95% CI 6.50, 8.28) for two criteria, and 15.3 (95% CI 12.2, 19.3) for all three. Markov models showed the shortest prediabetes duration (1.7 years) and lowest regression probability (5.4%) in those meeting all three criteria. Low IGI or ISI predicted higher diabetes risk, and dual impairment conferred greatest risk (aHR 4.06; 95% CI 3.37, 4.90). Even normoglycaemic individuals with low IGI or ISI had an elevated risk of diabetes compared to those with high IGI or ISI. Conclusions/interpretation Diabetes progression differs based on both glycaemic subtype and physiological subtype. Integrating IGI and ISI with conventional definitions enhances risk stratification and may help to identify high-risk individuals for earlier targeted intervention.
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Choe et al. (2026) conducted a cohort in Prediabetes and normoglycaemia (progression to type 2 diabetes) (n=7,186). Prediabetes (defined by IFG, IGT, or HbA1c criteria) stratified by insulin secretion and sensitivity vs. Normoglycaemia was evaluated on Progression to incident type 2 diabetes (aHR 3.94, 95% CI 3.61, 4.31). Prediabetes subtypes conferred distinct type 2 diabetes risks compared to normoglycaemia, escalating to aHR 15.3 when meeting all three glycaemic criteria.
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