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We compared progression across these subtypes, and evaluated the benefit of adding insulin secretion and sensitivity to risk stratification.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analysed 7186 Korean adults aged 40\u201369 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\n                      <jats:sub>1c<\/jats:sub>\n                      . Prediabetes was classified as IFG, IGT or HbA\n                      <jats:sub>1c<\/jats:sub>\n                      -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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      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\n                      <jats:sub>1c<\/jats:sub>\n                      -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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-026-06866-4","type":"journal-article","created":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T21:07:55Z","timestamp":1792271275000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediabetes subtype-based stratification reveals distinct long-term risks for type 2 diabetes"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5318-0859","authenticated-orcid":false,"given":"Hun Jee","family":"Choe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0523-0839","authenticated-orcid":false,"given":"Wonsuk","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6316-1640","authenticated-orcid":false,"given":"Howard H.","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1417-9510","authenticated-orcid":false,"given":"Dimple","family":"Kondal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8621-5405","authenticated-orcid":false,"given":"K. 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Parts of this study were presented in oral form at the 15th International Congress of Diabetes and Metabolism, Seoul, Korea, 25\u201327 September 2025.","order":1,"name":"Ethics","label":"Acknowledgements","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"The data underlying this study were obtained from the Korean Genome and Epidemiology Study (KoGES), managed by the Korea Disease Control and Prevention Agency (KDCA). The data are not publicly available due to access restrictions imposed by the KDCA, but are currently available to qualified researchers through the National Biobank of Korea following submission of a research proposal and approval by the KDCA. Access is limited to the approved analyses and period, and the data may not be redistributed or used beyond the scope of the approved research.","order":2,"name":"Ethics","label":"Data availability","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"Open Access funding enabled and organized by Seoul National University. This work was supported by grants from the National Research Foundation of Korea (RS-2022-NR071807 to WC and RS-2023-00222910 and RS-2023-00262002 to JHM), the Korea Health Industry Development Institute (RS-2024-00404132 and RS-2026-25514796 to JHM), the SNU-SNUH Physician Scientist Training Program (800-20240637, 800-20240632, 800-20250594, 800-20250591 to JHM), and the Research Program funded by the Korea Centers for Disease Control and Prevention (2001-347-6111-221, 2002-347-6111-221, 2003-347-6111-221, 2004-E71001-00, 2005-E71001-00, 2006-E71005-00, 2006-E71006-00, 2007-E71001-00, 2007-E71003-00, 2008-E71001-00, 2008-E71005-00, 2009-E71002-00, 2009-E71007-00, 2010-E71001-00, 2010-E71004-00, 2011-E71004-00, 2011-E71008-00, 2012-E71008-00, 2012-E71005-00, 2013-E71007-00, 2013-E71005-00, 2014-E71005-00, 2014-E71003-00, 2015-P71002-00, 2015-P71001-00, 2016-E71002-00, 2016-E71003-00, 2017-E71002-00, 2017-E71001-00, 2018-E7102-00, 2018-E7101-00, 2019-E7104-00, 2019-E7105-00, 2019-E7104-01, 2019-E7105-01, 2021-E0603-00, 2021-E0603-01) to NHC.","order":3,"name":"Ethics","label":"Funding","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.","order":4,"name":"Ethics","label":"Authors\u2019 relationships and activities","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"HJC wrote the first draft with input from WC and JHM. HJC and WC contributed equally to the manuscript. All authors contributed to data interpretation, critically revised the manuscript, and had final responsibility for the decision to submit for publication. NHC and JHM are the guarantors of this work, and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.","order":5,"name":"Ethics","label":"Contribution statement","group":{"name":"EthicsHeading","label":"Ethics"}}]}}