Evidence map›Paper›PMID 31908797›Full record

SynthesisBMJ open diabetes research & care2019

Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes.

Crystal Man Ying Lee, Stephen Colagiuri, Mark Woodward, Edward W Gregg, Robert Adams, Fereidoun Azizi, Rafael Gabriel, Tiffany K Gill, Clicerio Gonzalez, Allison Hodge and 16 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMJ open diabetes research & care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
5.6field-weighted citation impact, top 3% 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.

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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 82 citations in OpenAlex.

  1. Pooled it
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  7. Review
  8. Article
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  13. Prediabetes.Nature reviews. Disease primers · 2025
    Review
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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

26 authors at 20 institutions in 8 countries.

Crystal Man Ying LeeSchool of Psychology and Public Health, La Trobe University, Bundoora, Victoria, Australia.ORCID 0000-0001-6613-5491
Stephen ColagiuriBoden Collaboration for Obesity, Nutrition and Exercise & Eating Disorders, University of Sydney, Sydney, New South Wales, Australia.
Mark WoodwardThe George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.
Edward W GreggDepartment of Epidemiology and Statistics, School of Public Health, Imperial College London, London, UK.
Robert AdamsAdelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
Fereidoun AziziEndocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Rafael GabrielNational School of Public Health, National Institute of Health Carlos III, Madrid, Spain.
Tiffany K GillFaculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
Clicerio GonzalezUnidad de Investigación en Diabetes y Riesgo Cardiovascular, Instituto Nacional de Salud Publica, Cuernavaca, Morelos, Mexico.
Allison HodgeCancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
David R Jacobs JrDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
Joshua J JosephDivision of Endocrinology, Diabetes and Metabolism, Department of Medicine, Ohio State University Wexner Medical Center, Columbus, Ohio, USA.ORCID 0000-0001-9169-8261
Davood KhaliliPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0003-4956-1039
Dianna J MaglianoDiabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.ORCID 0000-0002-9507-6096
Kirsten MehligDepartment of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Goteborg, Sweden.
Roger MilneCancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
Gita MishraSchool of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
Morgana Mongraw-ChaffinDepartment of Epidemiology & Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.ORCID 0000-0001-6541-7198
Julie A PascoDepartment of Clinical and Biomedical Sciences, Barwon Health, The University of Melbourne, Geelong, Victoria, Australia.
Masaru SakuraiDepartment of Social and Environmental Medicine, Kanazawa Medical University, Uchinada, Ishikawa, Japan.
Pamela J SchreinerDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
Elizabeth SelvinDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0001-6923-7151
Jonathan E ShawClinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.ORCID 0000-0002-6187-2203
Gary WittertDiscipline of Medicine, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
Hiroshi YatsuyaDepartment of Public Health, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan.
Rachel R HuxleyThe George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.ORCID 0000-0002-2705-6616
Baker Heart and Diabetes Institute · AUJohns Hopkins University · USResearch Institute for Endocrine Sciences · IRThe University of Adelaide · AUThe University of Sydney · AUUniversity of Minnesota · USBarwon Health · AUCancer Council Victoria · AUFlinders University · AUFujita Health University · JPImperial College London · GBInstituto de Salud Carlos III · ESInstituto Nacional de Salud Pública · MXKanazawa Medical University · JPLa Trobe University · AUThe Ohio State University Wexner Medical Center · USThe University of Melbourne · AUThe University of Queensland · AUUniversity of Gothenburg · SEWake Forest University · US

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
The Role of The Renin-Angiotensin-Aldosterone System, ARMC5, and Neprilysin in Glucose Metabolism among African AmericansK23DK117041 · NIDDK · OHIO STATE UNIVERSITY · PI JOSEPH, JOSHUA J · 2018 to 2022
$1.0M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095166 · HC · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI TRACY, RUSSELL P · 1999 to 2001
$758k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC095162 · HC · JOHNS HOPKINS UNIVERSITY · PI SZKLO, MOYSES A · 1999 to 2000
$694k
Research and Mentoring in the Clinical Epidemiology of Type 2 DiabetesK24DK106414 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2015 to 2019
$654k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095161 · HC · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEA, STEVEN · 1999 to 2001
$642k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095165 · HC · WAKE FOREST UNIVERSITY · PI BURKE, GREGORY L · 1999 to 2001
$616k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095160 · HC · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SAAD, MOHAMMED F · 1999 to 2001
$592k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC095164 · HC · NORTHWESTERN UNIVERSITY · PI LIU, KIANG JOHN · 1999 to 2001
$511k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095163 · HC · UNIVERSITY OF MINNESOTA TWIN CITIES · PI FOLSOM, AARON R · 1999 to 2001
$443k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095168 · HC · JOHNS HOPKINS UNIVERSITY · PI BLUEMKE, DAVID A. · 1999 to 2000
$375k
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCI NIH HHS HHSN261201800010INHLBI NIH HHS HHSN268201000031CNHLBI NIH HHS HHSN268201000041CNHLBI NIH HHS HHSN268201000051CNHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS HHSN268201700001CNHLBI NIH HHS HHSN268201700001INHLBI NIH HHS HHSN268201700002CNHLBI NIH HHS HHSN268201700002INHLBI NIH HHS HHSN268201700003CNHLBI NIH HHS HHSN268201700003INHLBI NIH HHS HHSN268201700004CNHLBI NIH HHS HHSN268201700004INHLBI NIH HHS HHSN268201700005CNHLBI NIH HHS HHSN268201700005INHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS HHSN268201800003INHLBI NIH HHS HHSN268201800004INHLBI NIH HHS HHSN268201800005INHLBI NIH HHS HHSN268201800006INHLBI NIH HHS HHSN268201800007INHLBI NIH HHS HHSN268201800010INHLBI NIH HHS HHSN268201800011CNHLBI NIH HHS HHSN268201800011INHLBI NIH HHS HHSN268201800012CNHLBI NIH HHS HHSN268201800012INHLBI NIH HHS HHSN268201800014CNHLBI NIH HHS HHSN268201800014INHLBI NIH HHS HHSN268201800015INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NIDDK NIH HHS K23 DK117041NIDDK NIH HHS K24 DK106414NIMHD NIH HHS HHSN268201800013I
6 · The paper itself

Abstract

Objective: There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful. Research design and methods: We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points. Results: Sixteen studies, with 76 513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1 mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6 mmol/L, 2-hour postload glucose 7.0 mmol/L and HbA1c 5.6% (38 mmol/mol). Conclusions: In terms of identifying individuals at greatest risk of developing diabetes within 5 years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.

Indexed as

BiomarkersDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Disease ProgressionHumansIncidencePrediabetic StatePrognosisRisk FactorsBiomarkersfasting blood glucoseglycated hemoglobinincidencepre-diabetes

Identifiers

PMID31908797
PMCPMC6936411
OpenAlexW2998279878

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.