PLoS ONE (Jan 2021)

A clinical diabetes risk prediction model for prediabetic women with prior gestational diabetes.

  • Bernice Man,
  • Alan Schwartz,
  • Oksana Pugach,
  • Yinglin Xia,
  • Ben Gerber

DOI
https://doi.org/10.1371/journal.pone.0252501
Journal volume & issue
Vol. 16, no. 6
p. e0252501

Abstract

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IntroductionWithout treatment, prediabetic women with a history of gestational diabetes mellitus (GDM) are at greater risk for developing type 2 diabetes compared with women without a history of GDM. Both intensive lifestyle intervention and metformin can reduce risk. To predict risk and treatment response, we developed a risk prediction model specifically for women with prior GDM.MethodsThe Diabetes Prevention Program was a randomized controlled trial to evaluate the effectiveness of intensive lifestyle intervention, metformin (850mg twice daily), and placebo in preventing diabetes. Data from the Diabetes Prevention Program (DPP) was used to conduct a secondary analysis to evaluate 11 baseline clinical variables of 317 women with prediabetes and a self-reported history of GDM to develop a 3-year diabetes risk prediction model using Cox proportional hazards regression. Reduced models were explored and compared with the main model.ResultsWithin three years, 82 (25.9%) women developed diabetes. In our parsimonious model using 4 of 11 clinical variables, higher fasting glucose and hemoglobin A1C were each associated with greater risk for diabetes (each hazard ratio approximately 1.4), and there was an interaction between treatment arm and BMI suggesting that metformin was more effective relative to no treatment for BMI ≥ 35kg/m2 than BMI ConclusionsA clinical prediction model was developed for individualized decision making for prediabetes treatment in women with prior GDM.