Evidence mapPaperPMID 37131814Full record

ArticlemedRxiv : the preprint server for health sciences2023

Precision medicine in type 2 diabetes: A systematic review of treatment effect heterogeneity for GLP1-receptor agonists and SGLT2-inhibitors.

Katherine G Young, Eram Haider McInnes, Robert J Massey, Anna R Kahkohska, Scott J Pilla, Sridharan Raghaven, Maggie A Stanislawski, Deirdre K Tobias, Andrew P McGovern, Adem Y Dawed and 4 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 2 countries.

Katherine G YoungExeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, UK.
Eram Haider McInnesDivision of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
Robert J MasseyDivision of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
Anna R KahkohskaDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Scott J PillaDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Sridharan RaghavenSection of Academic Primary Care, US Department of Veterans Affairs Eastern Colorado Health Care System, Aurora, CO, USA.
Maggie A StanislawskiDepartment of Biomedical Informatics, School of Medicine, University of Colorado, Aurora, USA, 80045.
Deirdre K TobiasDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Andrew P McGovernExeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, UK.
Adem Y DawedDivision of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
Angus G JonesExeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, UK.
Ewan R PearsonDivision of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
John M DennisExeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, UK.
ADA/EASD Precision Medicine in Diabetes Initiative Consortium
University of Dundee · GBUniversity of Exeter · GBBrigham and Women's Hospital · USJohns Hopkins University · USUniversity of Colorado Anschutz Medical Campus · USUniversity of North Carolina at Chapel Hill · USVA Eastern Colorado Health Care System · US

Funding

CSRD VA IK2 CX001907NCATS NIH HHS KL2 TR002490
6 · The paper itself

Abstract

Background: A precision medicine approach in type 2 diabetes requires identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy. Methods: We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. Results: After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. The majority of papers had methodological limitations precluding robust assessment of treatment effect heterogeneity. For glycaemic outcomes, most cohorts were observational, with multiple analyses identifying lower renal function as a predictor of lesser glycaemic response with SGLT2-inhibitors and markers of reduced insulin secretion as predictors of lesser response with GLP1-receptor agonists. For cardiovascular and renal outcomes, the majority of included studies were post-hoc analyses of randomized control trials (including meta-analysis studies) which identified limited clinically relevant treatment effect heterogeneity. Conclusions: Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care. Plain language summary: This review identifies research that helps understand which clinical and biological factors that are associated with different outcomes for specific type 2 diabetes treatments. This information could help clinical providers and patients make better informed personalized decisions about type 2 diabetes treatments. We focused on two common type 2 diabetes treatments: SGLT2-inhibitors and GLP1-receptor agonists, and three outcomes: blood glucose control, heart disease, and kidney disease. We identified some potential factors that are likely to lessen blood glucose control including lower kidney function for SGLT2-inhibitors and lower insulin secretion for GLP1-receptor agonists. We did not identify clear factors that alter heart and renal disease outcomes for either treatment. Most of the studies had limitations, meaning more research is needed to fully understand the factors that influence treatment outcomes in type 2 diabetes.

Identifiers

PMID37131814
PMCPMC10153311
OpenAlexW4366769781

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.