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, David R. Jacobs, Joshua J. Joseph, Davood Khalili, Dianna J. Magliano, Kirsten Mehlig, Roger Milne, Gita Mishra, Morgana Mongraw-Chaffin, Julie A. Pasco, Masaru SakuraiPamela J. Schreiner, Elizabeth Selvin, Jonathan E. Shaw, Gary Wittert, Hiroshi Yatsuya, Rachel R. Huxley

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Article numbere000794
JournalBMJ Open Diabetes Research and Care
Volume7
Issue number1
DOIs
StatePublished - Dec 29 2019

Bibliographical note

Funding Information:
Competing interests CMYL, JAP, GW and RRH received grants from the National Health and Medical Research Council of Australia (NHMRC) during the conduct of the study; MW received person fees from Amgen and Hyowa Hakko Kirin outside the submitted work; RA received grants from NHMRC and the Hospital Research Foundation during the conduct of the study; JJJ received grants from National Institute of Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases (K23DK117041) during the conduct of the study; DJM and JES received grants from Commonwealth Department of Health and Aged Care, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, AstraZeneca, Aventis Pharmaceutical, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly (Aust) Pty Ltd, GlaxoSmithKline, Janssen-Cilag (Aust) Pty Ltd, Merck Lipha s.a., Merck Sharp & Dohme (Aust), Novartis Pharmaceutical (Aust) Pty Ltd, Novo Nordisk Pharmaceutical Pty Ltd, Pharmacia and Upjohn Pty Ltd, Pfizer Pty Ltd, Sanofi Synthelabo, Servier Laboratories (Aust) Pty Ltd, the Australian Kidney Foundation and Diabetes Australia during the conduct of the study, and personal fees from AstraZeneca, Mylan, Boehringer Ingelheim, Sanofi, Merck Sharp and Dohme, Novo Nordisk and Eli Lilly outside the submitted work; PJS received grants from National Heart, Lung and Blood Institute during the conduct of the study; ES received grants from NIH during the conduct of the study.

Funding Information:
Funding This work was supported by the National Health and Medical Research Council of Australia (grant number 1103242). The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under contract nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I. ES was supported by NIH/NIDDK grant K24DK106414. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN2682018000031, HHSN2682018000041, HHSN2682018000051, HHSN2682018000061 and HHSN2682018000071 from the National Heart, Lung, and Blood Institute (NHLBI). The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further augmented by Australian National Health and Medical Research Council grants 209057, 396414 and 1074383 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The Multi-Ethnic Study of Atherosclerosis was supported by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from NCRR. The Population Study of Women in Gothenburg (PSWG) was financed in part by grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement ALFGBG-720201. VIVA Study received grants 95/0029 and 06/90270 from the Instituto de Salud Carlos III, Spain.

Publisher Copyright:
© © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.

Keywords

  • fasting blood glucose
  • glycated hemoglobin
  • incidence
  • pre-diabetes

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