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)
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.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Hypertriglyceridemic Waist Phenotype; Insulin-resistance; Cardiovascular-disease; Cluster-analysis; Glycemic Control; Risk; Subgroups; Mellitus; Onset; Association
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2023
Prepublished im Jahr
0
HGF-Berichtsjahr
2023
ISSN (print) / ISBN
2730-664X
e-ISSN
2730-664X
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 3,
Heft: 1,
Seiten: ,
Artikelnummer: 138
Supplement: ,
Reihe
Verlag
Springer
Verlagsort
Campus, 4 Crinan St, London, N1 9xw, England
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
90000 - German Center for Diabetes Research
Forschungsfeld(er)
Helmholtz Diabetes Center
PSP-Element(e)
G-502400-001
Förderungen
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
Copyright
Erfassungsdatum
2023-11-28