Prediabetes subtype-based stratification reveals distinct long-term risks for type 2 diabetes.

Authors

Hun Jee Choe, Wonsuk Choi, Howard H Chang, Dimple Kondal, K M Venkat Narayan, Joon Ho Moon, Nam H Cho

Published in

Diabetologia. Oct 17, 2026. Epub Oct 17, 2026.

Abstract

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.
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.
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.
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.

PMID:
42892651
Bibliographic data and abstract were imported from PubMed on 18 Oct 2026.

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