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Precision subclassification of type 2 diabetes: a systematic review

Shivani Misra, Róbert Wágner, Bige Özkan, Martin Schön, Magdalena Sevilla-González, Katsiaryna Prystupa, Caroline C. Wang, Raymond J. Kreienkamp, Sara J. Cromer, Mary R. Rooney, Daisy Duan, Anne Cathrine B. Thuesen, Amelia S. Wallace, Aaron Leong, Aaron J. Deutsch, Mette K. Andersen, Liana K. Billings, Robert H. Eckel, Wayne Huey‐Herng Sheu, Torben Hansen, Norbert Stefan, Mark O. Goodarzi, Debashree Ray, Elizabeth Selvin, José C. Florez, ADA/EASD PMDI, Deirdre K. Tobias, Jordi Merino, Abrar Ahmad, Catherine Aiken, Jamie L. Benham, Dhanasekaran Bodhini, Amy L. Clark, Kevin Colclough, Rosa Corcoy, Sara J. Cromer, Jamie L. Felton, Ellen C. Francis, Pieter Gillard, Véronique Gingras, Romy Gaillard, Eram Haider, Alice E. Hughes, Jennifer M. Iklé, Laura M. Jacobsen, Anna R. Kahkoska, Jarno L. T. Kettunen, Raymond J. Kreienkamp, Lee‐Ling Lim, Jonna M. E. Männistö, Robert Massey, Niamh‐Maire Mclennan, Rachel G. Miller, Mario Luca Morieri, Jasper Most, Rochelle N. Naylor, Bige Ozkan, Kashyap Patel, Scott J. Pilla, Sridaran Raghaven, Martin Schön, Zhila Semnani‐Azad, Magdalena Sevilla-González, Pernille Svalastoga, Wubet Worku Takele, Claudia H.T. Tam, Anne Cathrine B. Thuesen, Mustafa Tosur, Caroline C. Wang, Jessie J. Wong, Jennifer M. Yamamoto, Katherine Young, Chloé Amouyal, Maxine P. Bonham, Mingling Chen, Feifei Cheng, Tinashe Chikowore, Sian C. Chivers, Christoffer Clemmensen, Dana Dabelea, Adem Y. Dawed, Aaron J. Deutsch, Laura T. Dickens, Linda A. DiMeglio, Monika Dudenhöffer‐Pfeifer, Carmella Evans‐Molina, María Mercè Fernández-Balsells, Hugo Fitipaldi, Stephanie L. Fitzpatrick, Stephen E. Gitelman, Mark O. Goodarzi, Jessica A. Grieger, Marta Guasch‐Ferré, Nahal Habibi, Chuiguo Huang, Arianna Harris-Kawano, Heba M. Ismail, Benjamin Hoag, Randi K. Johnson, Angus G. Jones

2023Communications Medicine97 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Type 2 diabetesSystematic reviewMedicineDiabetes mellitusMEDLINEPolitical scienceEndocrinologyLawDiabetes, Cardiovascular Risks, and LipoproteinsBariatric Surgery and OutcomesDiabetes Treatment and Management