Evidence map›Paper›PMID 32666226›Full record

ReviewDiabetologia2020

Real-world evidence: the devil is in the detail.

Mugdha Gokhale, Til Stürmer, John B Buse

Abstract readReview
In one paragraph

Review in Diabetologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
–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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Real-World Evidence of Automated Insulin Delivery System Use.Diabetes technology & therapeutics · 2024
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

3 authors.

Mugdha GokhalePharmacoepidemiology, Center for Observational & Real-World Evidence, Merck, 770 Sumneytown Pike, West Point, PA, 19486, USA. mugdha.gokhale@merck.com.
Til StürmerDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
John B BuseDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.

Funding

Glycemia Reduction Approaches in Diabetes: A comparative effectiveness studyU01DK098246 · NIDDK · GEORGE WASHINGTON UNIVERSITY · PI KRAUSE-STEINRAUF, HEIDI, LACHIN, JOHN M · 2012 to 2022
$238.9M
Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
RADIANT Clinic and Data Coordinating CenterU54DK118612 · NIDDK · UNIVERSITY OF CHICAGO · PI Louis H. Philipson · 2018 to 2026
$21.9M
Final clinical studies for submission of a pre-market approval application to the FDA for a Bionic Pancreas that automates type 1 diabetes managementUC4DK108612 · NIDDK · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI BECK, ROY W., DAMIANO, EDWARD · 2015 to 2016
$13.5M
Pilot & Feasibility ProgramP30DK124723 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI P Darrell Neufer · 2020 to 2026
$11.0M
Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
Methods for Estimating Sex Differences in Safety and Effectiveness of DrugsR01HL118255 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JONSSON FUNK, MICHELE LAURA · 2014 to 2017
$1.7M
PROMIS Validation in Prospective Population-based Prostate Cancer Research StudyR01CA174453 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHEN, RONALD, REEVE, BRYCE B · 2012 to 2016
$1.4M
Patterns of use, comparative effectiveness, and safety of rotavirus vaccinesR21HD080214 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROOKHART, MAURICE ALAN · 2014 to 2015
$413k
NCATS NIH HHS UL1 TR002489NCI NIH HHS R01 CA174453NHLBI NIH HHS R01 HL118255NIA NIH HHS R01 AG056479NICHD NIH HHS R21 HD080214NIDDK NIH HHS P30 DK124723NIDDK NIH HHS U01 DK098246NIDDK NIH HHS U54 DK118612NIDDK NIH HHS UC4 DK108612
6 · The paper itself

Abstract

Much has been written about real-world evidence (RWE), a concept that offers an understanding of the effects of healthcare interventions using routine clinical data. The reflection of diverse real-world practices is a double-edged sword that makes RWE attractive but also opens doors to several biases that need to be minimised both in the design and analytical phases of non-experimental studies. Additionally, it is critical to ensure that researchers who conduct these studies possess adequate methodological expertise and ability to accurately implement these methods. Critical design elements to be considered should include a clearly defined research question using a causal inference framework, choice of a fit-for-purpose data source, inclusion of new users of a treatment with comparators that are as similar as possible to that group, accurately classifying person-time and deciding censoring approaches. Having taken measures to minimise bias 'by design', the next step is to implement appropriate analytical techniques (for example propensity scores) to minimise the remnant potential biases. A clear protocol should be provided at the beginning of the study and a report of the results after, including caveats to consider. We also point the readers to readings on some novel analytical methods as well as newer areas of application of RWE. While there is no one-size-fits-all solution to evaluating RWE studies, we have focused our discussion on key methods and issues commonly encountered in comparative observational cohort studies with the hope that readers are better equipped to evaluate non-experimental studies that they encounter in the future. Graphical abstract.

Indexed as

Evidence-Based MedicineObservational Studies as TopicComparative Effectiveness ResearchDiabetes MellitusHumansResearch DesignActive comparatorBiasDataEvidenceHealthcareNew-userPharmacoepidemiologyReal-worldReviewStudy design

Identifiers

PMID32666226
PMCPMC7448554

What Socratic holds

Textmetadata
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.