Evidence map›Paper›PMID 37339346›Full record

ReviewDiabetes care2023

Use of Real-World Data in Population Science to Improve the Prevention and Care of Diabetes-Related Outcomes.

Edward W Gregg, Elisabetta Patorno, Andrew J Karter, Roopa Mehta, Elbert S Huang, Martin White, Chirag J Patel, Allison T McElvaine, William T Cefalu, Joseph Selby and 2 more

Abstract readReview
In one paragraph

Review in Diabetes care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. A cohort description and comparison of four European national diabetes registries for the REDDIE project.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. ROCKET T1D Remote Patient Monitoring Program: Launching Diabetes Management Habits in New-Onset Diabetes.Clinical diabetes : a publication of the American Diabetes Association · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

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

5 · Who and what money

Authors and funding

12 authors.

Edward W Gregg1School of Population Health, RRCSI University of Medicine and Health Sciences, Dublin, Ireland.ORCID 0000-0003-2381-6822
Elisabetta Patorno3Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Andrew J Karter4Division of Research, Kaiser Permanente, Oakland, CA.
Roopa Mehta6Metabolic Research Unit (UIEM), Department of Endocrinology and Metabolism, Instituto Nacional de Ciencias Medicas y Nutricion, Salvador Zubiran (INCMNSZ), Mexico City, Mexico.
Elbert S Huang7Section of General Internal Medicine, Center for Chronic Disease Research and Policy (CDRP), The University of Chicago, Chicago, IL.
Martin White8Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, U.K.
Chirag J Patel9Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
Allison T McElvaine10Research and Scientific Programs, American Diabetes Association, Arlington, VA.
William T Cefalu11Division of Diabetes, Endocrinology, and Metabolic Diseases, National Institute of Diabetes, Digestive, and Kidney Diseases, National Institutes of Health, Bethesda, MD.
Joseph Selby12Patient-Centered Outcomes Institute, Washington, DC.
Matthew C Riddle13Division of Endocrinology, Diabetes, and Clinical Nutrition, Oregon Health & Science University, Portland, OR.
Kamlesh Khunti14Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, U.K.

Funding

Pilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI RONALD N COHEN · 2013 to 2026
$20.9M
Research Design, Data, and Analytics CoreP30DK092949 · NIDDK · UNIVERSITY OF CHICAGO · PI MILDA Renne SAUNDERS · 2011 to 2026
$10.0M
Translational Research Core - Health Engagement & Action Translational (HEAT)P30DK092924 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI Alyce Sophia Adams, HILARY Kessler SELIGMAN · 2011 to 2026
$9.2M
Enhancing evidence generation by linking randomized clinical trials (RCTs) to real world data (RWD)U01FD007213 · FDA · BRIGHAM AND WOMEN'S HOSPITAL · PI PATORNO, ELISABETTA · 2020 to 2022
$4.2M
Optimizing Medical Decision Making for Older Patients with Type 2 DiabetesR01AG063391 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI HUANG, ELBERT S., KARTER, ANDREW JOHN · 2019 to 2023
$3.2M
Novel Approaches to Monitor the Safety and Effectiveness of Newly Marketed Diabetes Medications in Older Adults Considering Frailty and MultimorbidityK08AG055670 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI PATORNO, ELISABETTA · 2018 to 2021
$661k
Research and Mentorship in Medical Decision Making for Chronic Diseases of Older AdultsK24AG069080 · NIA · UNIVERSITY OF CHICAGO · PI HUANG, ELBERT S. · 2020 to 2024
$583k
Relaxed Glycemic Control and the Risk of Infections in Older Adults with Type 2 DiabetesR56AG074986 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI KARTER, ANDREW JOHN, LIPSKA, KASIA JOANNA · 2022 to 2022
$400k
Biotechnology and Biological Sciences Research CouncilDepartment of HealthFDA HHS U01 FD007213Medical Research Council MC/UU/00006/7Medical Research Council MC_UU_00006/7NIA NIH HHS K08 AG055670NIA NIH HHS K24 AG069080NIA NIH HHS R01 AG063391NIA NIH HHS R56 AG074986NIDDK NIH HHS P30 DK020595NIDDK NIH HHS P30 DK092924NIDDK NIH HHS P30 DK092949
6 · The paper itself

Abstract

The past decade of population research for diabetes has seen a dramatic proliferation of the use of real-world data (RWD) and real-world evidence (RWE) generation from non-research settings, including both health and non-health sources, to influence decisions related to optimal diabetes care. A common attribute of these new data is that they were not collected for research purposes yet have the potential to enrich the information around the characteristics of individuals, risk factors, interventions, and health effects. This has expanded the role of subdisciplines like comparative effectiveness research and precision medicine, new quasi-experimental study designs, new research platforms like distributed data networks, and new analytic approaches for clinical prediction of prognosis or treatment response. The result of these developments is a greater potential to progress diabetes treatment and prevention through the increasing range of populations, interventions, outcomes, and settings that can be efficiently examined. However, this proliferation also carries an increased threat of bias and misleading findings. The level of evidence that may be derived from RWD is ultimately a function of the data quality and the rigorous application of study design and analysis. This report reviews the current landscape and applications of RWD in clinical effectiveness and population health research for diabetes and summarizes opportunities and best practices in the conduct, reporting, and dissemination of RWD to optimize its value and limit its drawbacks.

Indexed as

Data AccuracyDiabetes MellitusComparative Effectiveness ResearchHumansResearch DesignRisk Factors

Identifiers

PMID37339346
PMCPMC10300521

What Socratic holds

Textmetadata
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.