4.6 Article

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

Journal

PLOS ONE
Volume 16, Issue 6, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0252501

Keywords

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Funding

  1. UIC Center for Research on Women and Gender
  2. UIC Department of Medicine and Division of Academic Internal Medicine Geriatrics
  3. UIC College of Medicine

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A clinical prediction model was developed for personalized treatment decisions for prediabetes in women with a history of gestational diabetes mellitus. The study found that higher levels of fasting glucose and hemoglobin A1C were associated with an increased risk of developing diabetes, and metformin was more effective for individuals with higher BMI.
Introduction Without 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. Methods The 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. Results Within 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/m(2) than BMI < 30kg/m(2). The model had fair discrimination (bias corrected C index = 0.68) and was not significantly different from our main model using 11 clinical variables. The estimated incidence of diabetes without treatment was 37.4%, compared to 20.0% with intensive lifestyle intervention or metformin treatment for women with a prior GDM. Conclusions A clinical prediction model was developed for individualized decision making for prediabetes treatment in women with prior GDM.

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