Trial reportDiabetologia2019

Non-traditional biomarkers and incident diabetes in the Diabetes Prevention Program: comparative effects of lifestyle and metformin interventions.

Ronald B Goldberg, George A Bray, Santica M Marcovina, Kieren J Mather, Trevor J Orchard, Leigh Perreault, Marinella Temprosa, Diabetes Prevention Program Research Group

Open access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Diabetologia, 2019. The graph read 1 number from its abstract, feeding 1 cell of the map: it supports the treatment in 1. Cited by 15 papers, 3 of them syntheses that pooled it.

1number the graph read from it
1cell of the map it votes in
15citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 9% of its field
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.

← favours the comparatorfavours the treatment →
1 · no effect
Lipidsfavours the treatment · against placebo · t2dfeeds one cell of the map
HR 1.191.06 to 1.34
Traditional diabetes risk factors were defined as family history, HDL-cholesterol, triacylglycerol, BMI, fasting and 2 h glucose, HbA RESULTS: E-selectin, (HR 1.19 [95% CI 1.06, 1.34]), adiponectin (0.84 [0.71, 0.99]) and tissue plasminogen activator (1.13 [1.03, 1.24]) were associated with incident diabetes in the placebo group, independent of diabetes risk factors.

clause the extractor read what became the number

2 · Its place on the map

Where it lands on the map

Rows are treatments, columns are outcomes. The coloured squares are the cells this paper feeds, coloured by the vote it casts there. Click one to jump to what this paper adds to it.

supports the treatmentfavours the comparatorno clear differenceread, but no usable result
3 · What it changes

What it adds to each cell

For every cell the paper feeds: the belief in the claim with and without this paper, and this paper's estimate drawn against every other readable study in the cell. The ringed dot is this paper.

Diet, exercise & lifestyle×lipids

SupportsOpen on the map →What to test next →

2 readable studies in this cell: 1 favour the treatment, 0 find no difference, 1 favour the comparator.

Belief with this paper
0.40contested · 1 family supports, 1 contradict · against placebo
Without it
0.00This paper moves it by +0.40.
← favours the comparatorfavours the treatment →
1 · no effect
This paper · 2019
HR 1.191.06 to 1.34
4 · 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.

5 · Its place in the literature

Who cites it

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Meta-Analysis of the Effect of Metformin on the Progression of Different Types of Prediabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    Review
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6 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

7 · Who and what money

Authors and funding

8 authors at 7 institutions in 1 country.

Ronald B GoldbergDivision of Endocrinology, Diabetes and Metabolism, Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
George A BrayClinical Obesity, Pennington Biomedical Research Center, Louisiana State University Medical Center, Baton Rouge, LA, USA.
Santica M MarcovinaNorthwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Northwest Lipid Research Labs, Seattle, WA, USA.
Kieren J MatherDepartment of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Trevor J OrchardDepartment of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA.
Leigh PerreaultDepartment of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Marinella TemprosaDepartment of Epidemiology and Biostatistics, Biostatistics Center and Milken Institute School of Public Health, George Washington University, Rockville, MD, USA.
Diabetes Prevention Program Research Group
George Washington University · USIndiana University School of MedicineLouisiana State University · USUniversity of Colorado Anschutz Medical Campus · USUniversity of Miami · USUniversity of Pittsburgh · USUniversity of Washington · US

Funding

PRIMARY PREVENTION TRIAL--DATA COORDINATING CENTERU01DK048489 · GEORGE WASHINGTON UNIVERSITY · 1994 to 2005
$23.7M
Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · 1986 to 2025
$12.6M
Post-DDP Follow-up StudyU01DK048413 · UNIVERSITY OF WASHINGTON · 1994 to 2005
$4.4M
PRIMARY PREVENTION TRIALU01DK048443 · UNIVERSITY OF SOUTHERN CALIFORNIA · 1994 to 2005
$4.0M
PRIMARY PREVENTION TRIAL (DPT-2)U01DK048397 · MASSACHUSETTS GENERAL HOSPITAL · 1994 to 2005
$3.8M
Post-DPP Follow-up StudyU01DK048485 · JOHNS HOPKINS UNIVERSITY · 1994 to 2005
$3.7M
NIDDM PRIMARY PREVENTION TRIALU01DK048412 · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 1994 to 2005
$3.6M
PRIMARY PREVENTION TRIAL (DPT-2)U01DK048339 · UNIVERSITY OF CALIFORNIA SAN DIEGO · 1994 to 2005
$3.6M
NIDDM PRIMARY PREVENTION TRIAL (DPT 2)U01DK048404 · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · 1994 to 2005
$3.5M
Post-DPP Followup StudiesU01DK048411 · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · 1994 to 2005
$3.4M
PRIMARY PREVENTION TRIALU01DK048387 · MEDSTAR RESEARCH INSTITUTE · 1994 to 2005
$3.3M
Post-DPP Follow-up StudyU01DK048375 · UNIVERSITY OF COLORADO DENVER · 1994 to 2005
$3.3M
NIDDK NIH HHS P30 DK017047NIDDK NIH HHS P30 DK097512NIDDK NIH HHS R01 DK078907NIDDK NIH HHS U01 DK048339NIDDK NIH HHS U01 DK048375NIDDK NIH HHS U01 DK048377NIDDK NIH HHS U01 DK048381NIDDK NIH HHS U01 DK048387NIDDK NIH HHS U01 DK048397NIDDK NIH HHS U01 DK048404NIDDK NIH HHS U01 DK048406NIDDK NIH HHS U01 DK048407NIDDK NIH HHS U01 DK048411NIDDK NIH HHS U01 DK048412NIDDK NIH HHS U01 DK048413NIDDK NIH HHS U01 DK048434NIDDK NIH HHS U01 DK048443NIDDK NIH HHS U01 DK048468NIDDK NIH HHS U01 DK048485NIDDK NIH HHS U01 DK048489NIDDK NIH HHS U01 DK048514
8 · The paper itself

Abstract

The marked sentences are the ones the graph read a number from.

aims/hypothesisWe compared the associations of circulating biomarkers of inflammation, endothelial and adipocyte dysfunction and coagulation with incident diabetes in the placebo, lifestyle and metformin intervention arms of the Diabetes Prevention Program, a randomised clinical trial, to determine whether reported associations in general populations are reproduced in individuals with impaired glucose tolerance, and whether these associations are independent of traditional diabetes risk factors. We further investigated whether biomarker-incident diabetes associations are influenced by interventions that alter pathophysiology, biomarker concentrations and rates of incident diabetes.

methodsThe Diabetes Prevention Program randomised 3234 individuals with impaired glucose tolerance into placebo, metformin (850 mg twice daily) and intensive lifestyle groups and showed that metformin and lifestyle reduced incident diabetes by 31% and 58%, respectively compared with placebo over an average follow-up period of 3.2 years. For this study, we measured adiponectin, leptin, tissue plasminogen activator (as a surrogate for plasminogen activator inhibitor 1), high-sensitivity C-reactive protein, IL-6, monocyte chemotactic protein 1, fibrinogen, E-selectin and intercellular adhesion molecule 1 at baseline and at 1 year by specific immunoassays. Traditional diabetes risk factors were defined as family history, HDL-cholesterol, triacylglycerol, BMI, fasting and 2 h glucose, HbA

resultsE-selectin, (HR 1.19 [95% CI 1.06, 1.34]), adiponectin (0.84 [0.71, 0.99]) and tissue plasminogen activator (1.13 [1.03, 1.24]) were associated with incident diabetes in the placebo group, independent of diabetes risk factors. Only the association between adiponectin and diabetes was maintained in the lifestyle (0.69 [0.52, 0.92]) and metformin groups (0.79 [0.66, 0.94]). E-selectin was not related to diabetes development in either lifestyle or metformin groups. A novel association appeared for change in IL-6 in the metformin group (1.09 [1.021, 1.173]) and for baseline leptin in the lifestyle groups (1.31 [1.06, 1.63]). CONCLUSIONS/

interpretationThese findings clarify associations between an extensive group of biomarkers and incident diabetes in a multi-ethnic cohort with impaired glucose tolerance, the effects of diabetes risk factors on these, and demonstrate differential modification of associations by interventions. They strengthen evidence linking adiponectin to diabetes development, and argue against a central role for endothelial dysfunction. The findings have implications for the pathophysiology of diabetes development and its prevention.

Indexed as

Life StyleAdiponectinBiomarkersChemokine CCL2Diabetes MellitusE-SelectinFibrinogenHumansHypoglycemic AgentsIntercellular Adhesion Molecule-1Interleukin-6LeptinMetforminTissue Plasminogen ActivatorAdiponectinBiomarkersChemokine CCL2E-SelectinFibrinogenHypoglycemic AgentsIntercellular Adhesion Molecule-1Interleukin-6LeptinMetforminTissue Plasminogen ActivatorAdiponectinBiomarkersC-reactive proteinDiabetes preventionE-selectinInterleukin 6LeptinLifestyle changeMetforminTissue plasminogen activator

Identifiers

PMID30334082
PMCPMC6456055
OpenAlexW2896916348

What Socratic holds

Texttitle and abstract
LicenceTDM
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.