AIMS/HYPOTHESIS: Precise estimates of progression rates from 'prediabetes' to type 2 diabetes are needed to optimise prevention strategies for high-risk individuals. There is acceptance of prediabetes defined by impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), but there is some controversy surrounding HbA1c-defined prediabetes ranges, with some favouring 6.0-6.4% (42-46 mmol/mol). Comparing progression rates between groups might aid this issue, thus we aimed to accurately estimate progression rates to diabetes from different prediabetes categories. METHODS: Meta-analysis of prospective observational studies in which participants had prediabetes at baseline (ADA-defined IFG [5.6-6.9 mmol/l], WHO-defined IFG [6.1-6.9 mmol/l], IGT (7.8-11.0 mmol/l) or raised HbA1c [6.0-6.4%/42-46 mmol/mol]) and were followed up for incident diabetes. Incidence rates were combined using Bayesian random effects models. RESULTS: Overall, 70 studies met the inclusion criteria. In the six studies that used raised HbA1c, the pooled incidence rate (95% credible interval) of diabetes was 35.6 (15.1, 83.0) per 1,000 person-years. This rate was most similar to that for ADA-defined IFG (11 studies; 35.5 [26.6, 48.0]) and was non-significantly lower than WHO-defined IFG (34 studies; 47.4 [37.4, 59.8]), IGT (46 studies, 45.5 [37.8, 54.5]) and IFG plus IGT (15 studies, 70.4 [53.8, 89.7]). Similar results were seen when the data were analysed by the criteria used to diagnose diabetes. CONCLUSIONS/ INTERPRETATION: This study provides evidence that progression rates differ by prediabetes definition, which has implications for the planning and implementation of diabetes prevention programmes. HbA1c 6.0-6.4% might identify people at a lower diabetes risk than other prediabetes definitions, but further research is needed.
AIMS/HYPOTHESIS: Precise estimates of progression rates from 'prediabetes' to type 2 diabetes are needed to optimise prevention strategies for high-risk individuals. There is acceptance of prediabetes defined by impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), but there is some controversy surrounding HbA1c-defined prediabetes ranges, with some favouring 6.0-6.4% (42-46 mmol/mol). Comparing progression rates between groups might aid this issue, thus we aimed to accurately estimate progression rates to diabetes from different prediabetes categories. METHODS: Meta-analysis of prospective observational studies in which participants had prediabetes at baseline (ADA-defined IFG [5.6-6.9 mmol/l], WHO-defined IFG [6.1-6.9 mmol/l], IGT (7.8-11.0 mmol/l) or raised HbA1c [6.0-6.4%/42-46 mmol/mol]) and were followed up for incident diabetes. Incidence rates were combined using Bayesian random effects models. RESULTS: Overall, 70 studies met the inclusion criteria. In the six studies that used raised HbA1c, the pooled incidence rate (95% credible interval) of diabetes was 35.6 (15.1, 83.0) per 1,000 person-years. This rate was most similar to that for ADA-defined IFG (11 studies; 35.5 [26.6, 48.0]) and was non-significantly lower than WHO-defined IFG (34 studies; 47.4 [37.4, 59.8]), IGT (46 studies, 45.5 [37.8, 54.5]) and IFG plus IGT (15 studies, 70.4 [53.8, 89.7]). Similar results were seen when the data were analysed by the criteria used to diagnose diabetes. CONCLUSIONS/ INTERPRETATION: This study provides evidence that progression rates differ by prediabetes definition, which has implications for the planning and implementation of diabetes prevention programmes. HbA1c 6.0-6.4% might identify people at a lower diabetes risk than other prediabetes definitions, but further research is needed.
Authors: Saul Genuth; K G M M Alberti; Peter Bennett; John Buse; Ralph Defronzo; Richard Kahn; John Kitzmiller; William C Knowler; Harold Lebovitz; Ake Lernmark; David Nathan; Jerry Palmer; Robert Rizza; Christopher Saudek; Jonathan Shaw; Michael Steffes; Michael Stern; Jaako Tuomilehto; Paul Zimmet Journal: Diabetes Care Date: 2003-11 Impact factor: 19.112
Authors: Dan Ziegler; Andreas Voss; Wolfgang Rathmann; Alexander Strom; Siegfried Perz; Michael Roden; Annette Peters; Christa Meisinger Journal: Diabetologia Date: 2015-02-28 Impact factor: 10.122
Authors: Joshua J Joseph; Justin B Echouffo-Tcheugui; Mercedes R Carnethon; Alain G Bertoni; Christina M Shay; Haitham M Ahmed; Roger S Blumenthal; Mary Cushman; Sherita H Golden Journal: Diabetologia Date: 2016-06-08 Impact factor: 10.122
Authors: Jeff Cobb; Andrea Eckhart; Regis Perichon; Jacob Wulff; Matthew Mitchell; Klaus-Peter Adam; Robert Wolfert; Eric Button; Kay Lawton; Robert Elverson; Bernadette Carr; Margaret Sinnott; Ele Ferrannini Journal: J Diabetes Sci Technol Date: 2014-09-26
Authors: J David Spence; Catherine M Viscoli; Silvio E Inzucchi; Jennifer Dearborn-Tomazos; Gary A Ford; Mark Gorman; Karen L Furie; Anne M Lovejoy; Lawrence H Young; Walter N Kernan Journal: JAMA Neurol Date: 2019-05-01 Impact factor: 18.302