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Misra, S.* ; Wagner, R.* ; Ozkan, B.* ; Schön, M.* ; Sevilla-Gonzalez, M.* ; Prystupa, K.* ; Wang, C.C.* ; Kreienkamp, R.J.* ; Cromer, S.J.* ; Rooney, M.R.* ; Duan, D.* ; Thuesen, A.C.B.* ; Wallace, A.S.* ; Leong, A.* ; Deutsch, A.J.* ; Andersen, M.K.* ; Billings, L.K.* ; Eckel, R.H.* ; Sheu, W.H.* ; Hansen, T.* ; Stefan, N. ; Goodarzi, M.O.* ; Ray, D.* ; Selvin, E.* ; Florez, J.C.* ; Meigs, J.B.* ; Udler, M.S.*

Precision subclassification of type 2 diabetes: A systematic review.

Commun. Med. 3:138 (2023)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Hypertriglyceridemic Waist Phenotype; Insulin-resistance; Cardiovascular-disease; Cluster-analysis; Glycemic Control; Risk; Subgroups; Mellitus; Onset; Association
Language english
Publication Year 2023
HGF-reported in Year 2023
ISSN (print) / ISBN 2730-664X
e-ISSN 2730-664X
Journal Communications Medicine
Quellenangaben Volume: 3, Issue: 1, Pages: , Article Number: 138 Supplement: ,
Publisher Springer
Publishing Place Campus, 4 Crinan St, London, N1 9xw, England
Reviewing status Peer reviewed
Institute(s) Institute of Diabetes Research and Metabolic Diseases (IDM)
POF-Topic(s) 90000 - German Center for Diabetes Research
Research field(s) Helmholtz Diabetes Center
PSP Element(s) G-502400-001
Grants NIHR Biomedical Research Centre Funding Scheme
American Heart Association
American Diabetes Association
NIH
Wellcome Trust Career Development scheme
Pediatric Endocrine Society Rising Star Award
Novo Nordisk Foundation
NIH/NHLBI
Doris Duke Foundation
NIH/NIDDK
MOST, Taiwan
Eris M. Field Chair in Diabetes Research
Lund University (Sweden)
Novo Nordisk Foundation (Hellerup, Denmark)
NIGMS
DOI 10.1038/s43856-023-00360-3
WOS ID 001162595300001
PubMed ID 37798471
Erfassungsdatum 2023-11-28
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