Scientific Reports (Apr 2018)

Discordance in glycemic categories and regression to normality at baseline in 10,000 people in a Type 2 diabetes prevention trial

  • Mike Sampson,
  • Tim Elwell-Sutton,
  • Max O. Bachmann,
  • Allan Clark,
  • Ketan K. Dhatariya,
  • Clare Ferns,
  • Amanda Howe,
  • W. Garry John,
  • Gerry Rayman,
  • Leyla Swafe,
  • Jeremy Turner,
  • Melanie Pascale

DOI
https://doi.org/10.1038/s41598-018-24662-y
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 11

Abstract

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Abstract The world diabetes population quadrupled between 1980 and 2014 to 422 million and the enormous impact of Type 2 diabetes is recognised by the recent creation of national Type 2 diabetes prevention programmes. There is uncertainty about how to correctly risk stratify people for entry into prevention programmes, how combinations of multiple ‘at high risk’ glycemic categories predict outcome, and how the large recently defined ‘at risk’ population based on an elevated glycosylated haemoglobin (HbA1c) should be managed. We identified all 141,973 people at highest risk of diabetes in our population, and screened 10,000 of these with paired fasting plasma glucose and HbA1c for randomisation into a very large Type 2 diabetes prevention trial. Baseline discordance rate between highest risk categories was 45.6%, and 21.3–37.0% of highest risk glycaemic categories regressed to normality between paired baseline measurements (median 40 days apart). Accurate risk stratification using both fasting plasma glucose and HbA1c data, the use of paired baseline data, and awareness of diagnostic imprecision at diagnostic thresholds would avoid substantial overestimation of the true risk of Type 2 diabetes and the potential benefits (or otherwise) of intervention, in high risk subjects entering prevention trials and programmes.