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Mori, T.* ; Zaharia, O.P.* ; Straßburger, K.* ; Dennis, J.M.* ; Mai, K.* ; Kabisch, S.* ; Bornstein, S.* ; Szendroedi, J.* ; Blüher, M. ; Meyhöfer, S.* ; Seissler, J.* ; Birkenfeld, A.L.* ; Stefan, N.* ; Roden, M.* ; Wagner, R.* ; Kuß, O.*

Recognising, quantifying and accounting for classification uncertainty in type 2 diabetes subtypes.

Diabetologia 68, 2139-2150 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
AIMS/HYPOTHESIS: Despite continued interest in precision diagnostics and type 2 diabetes subtypes, the challenge of uncertainty in the classification of individuals into subtypes remains. This study introduces a novel method for quantifying and accounting for classification uncertainty in type 2 diabetes subtypes. METHODS: Building on recommendations from the ADA/EASD Precision Medicine in Diabetes Initiative, we quantified classification uncertainty using the normalised relative entropy (NRE), computed from distances to cluster centroids. A lower NRE value indicates greater uncertainty in an individual's cluster assignment. We examined the NRE in a cohort of 859 individuals with recent-onset type 2 diabetes from the prospective, observational German Diabetes Study (GDS) and compared it across previously identified diabetes subtypes, defined by age, BMI, HbA1c, HOMA-IR and HOMA-B. Predicted 10 year CVD risk (SCORE2-Diabetes) of the subtypes was evaluated with and without accounting for classification uncertainty. RESULTS: Individuals with mild age-related diabetes (n=395) and mild obesity-related diabetes (n=316) had a median NRE of 0.155 (95% CI 0.142, 0.177) and 0.119 (95% CI 0.107, 0.131), respectively. By contrast, individuals with severe insulin-resistant diabetes (n=130) and severe insulin-deficient diabetes (n=18) had a lower median NRE of 0.086 (95% CI 0.075, 0.108) and 0.082 (95% CI 0.071, 0.109), respectively. After weighting individuals by classification certainty, the proportion of variation in SCORE2-Diabetes explained by the subtypes (R2) increased from 17.4% (95% CI 12.8, 23.0) to 31.5% (95% CI 26.4, 37.1). The predicted 10 year CVD risk of the mild age-related diabetes subtype increased from 10.3% (95% CI 9.8, 10.7) to 11.6% (95% CI 11.2, 12.0). CONCLUSIONS/INTERPRETATION: The NRE provides a means to quantify and compare individual classification uncertainty in type 2 diabetes subtypes. Classification uncertainty varied between subtypes and individuals with type 2 diabetes, and accounting for it improved the ability of the subtypes to predict 10 year CVD risk.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Classification Uncertainty ; Clusters ; German Diabetes Study ; Precision Medicine ; Relative Entropy ; Subtypes ; Type 2 Diabetes Mellitus; Precision Medicine; Risk
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 0012-186X
e-ISSN 1432-0428
Zeitschrift Diabetologia
Quellenangaben Band: 68, Heft: 10, Seiten: 2139-2150 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin ; Heidelberg [u.a.]
Begutachtungsstatus Peer reviewed
Institut(e) Helmholtz Institute for Metabolism, Obesity and Vascular Research (HI-MAG)
POF Topic(s) 30201 - Metabolic Health
Forschungsfeld(er) Helmholtz Diabetes Center
PSP-Element(e) G-506501-001
Förderungen EASD mentorship programme
European Community
NIHR Exeter Bio-medical Research Centre
Wellcome Trust
Schmutzler Stiftung
German Federal Ministry of Education and Research
German Diabetes Association
Ministry of Culture and Science of the state of North Rhine-Westphalia
German Federal Ministry of Health
German Science Foundation (DFG)
University of Luebeck
Almond Board of California (Modesto, USA)
Wilhelm-Doerenkamp-Foundation (Chur, Switzerland)
J. Rettenmaier & Soehne (Rosenberg, Germany)
German Diabetes Association (DDG Adam Heller Prize)
European Foundation for the Study of Diabetes (EFSD Rising Star Award)
German Center for Diabetes Research, DZD
Projekt DEAL
DOI 10.1007/s00125-025-06486-4
WOS ID 001536033400001
Scopus ID 105015612914
PubMed ID 40715719
Erfassungsdatum 2025-07-29
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