Your browser doesn't support javascript.
loading
Precision subclassification of type 2 diabetes: a systematic review.
Misra, Shivani; Wagner, Robert; Ozkan, Bige; Schön, Martin; Sevilla-Gonzalez, Magdalena; Prystupa, Katsiaryna; Wang, Caroline C; Kreienkamp, Raymond J; Cromer, Sara J; Rooney, Mary R; Duan, Daisy; Thuesen, Anne Cathrine Baun; Wallace, Amelia S; Leong, Aaron; Deutsch, Aaron J; Andersen, Mette K; Billings, Liana K; Eckel, Robert H; Sheu, Wayne Huey-Herng; Hansen, Torben; Stefan, Norbert; Goodarzi, Mark O; Ray, Debashree; Selvin, Elizabeth; Florez, Jose C; Meigs, James B; Udler, Miriam S.
Afiliação
  • Misra S; Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK. s.misra@imperial.ac.uk.
  • Wagner R; Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK. s.misra@imperial.ac.uk.
  • Ozkan B; Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
  • Schön M; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.
  • Sevilla-Gonzalez M; German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
  • Prystupa K; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Wang CC; Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Kreienkamp RJ; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.
  • Cromer SJ; German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
  • Rooney MR; Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia.
  • Duan D; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Thuesen ACB; Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Wallace AS; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Leong A; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.
  • Deutsch AJ; German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
  • Andersen MK; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Billings LK; Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Eckel RH; Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA.
  • Sheu WH; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Hansen T; Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA.
  • Stefan N; Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Goodarzi MO; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Ray D; Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA.
  • Selvin E; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Florez JC; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Meigs JB; Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Udler MS; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Commun Med (Lond) ; 3(1): 138, 2023 Oct 05.
Article em En | MEDLINE | ID: mdl-37798471
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.
In people with type 2 diabetes there may be differences in the way people present, including for example, their symptoms, body weight or how much insulin they make. We looked at recent publications describing research in this area to see whether it is possible to separate people with type 2 diabetes into different subgroups and, if so, whether these groupings were useful for patients. We found that it is possible to group people with type 2 diabetes into different subgroups and being in one subgroup can be more strongly linked to the likelihood of developing complications over others. This might mean that in the future we can treat people in different subgroups differently in ways that improves their treatment and their health but it requires further study.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article