Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study

DOI Web Site PubMed 42 References
  • Xu Juan
    Department of Endocrinology and Metabolism, Graduate School of Medicine, Yokohama City University
  • Goto Atsushi
    Department of Health Data Science, Graduate School of Data Science, Yokohama City University
  • Konishi Maki
    Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
  • Kato Masayuki
    Health Management Center and Diagnostic Imaging Center, Toranomon Hospital
  • Mizoue Tetsuya
    Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
  • Terauchi Yasuo
    Department of Endocrinology and Metabolism, Graduate School of Medicine, Yokohama City University
  • Tsugane Shoichiro
    Division of Cohort Research, National Cancer Center Institute for Cancer Control National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition
  • Sawada Norie
    Division of Cohort Research, National Cancer Center Institute for Cancer Control
  • Noda Mitsuhiko
    Department of Diabetes, Metabolism and Endocrinology, Ichikawa Hospital, International University of Health and Welfare

Abstract

<p>Background: This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population.</p><p>Methods: Data from 10,986 participants (aged 46–75 years) in the development cohort of the Japan Public Health Center-based Prospective Diabetes Study and 11,345 participants (aged 46–75 years) in the validation cohort of the Japan Epidemiology Collaboration on Occupational Health Study were used to develop and validate the risk scores in logistic regression models.</p><p>Results: We considered non-invasive (sex, body mass index, family history of diabetes mellitus, and diastolic blood pressure) and invasive (glycated hemoglobin [HbA1c] and fasting plasma glucose [FPG]) predictors to predict the 5-year probability of incident diabetes. The area under the receiver operating characteristic curve was 0.643 for the non-invasive risk model, 0.786 for the invasive risk model with HbA1c but not FPG, and 0.845 for the invasive risk model with HbA1c and FPG. The optimism for the performance of all models was small by internal validation. In the internal-external cross-validation, these models tended to show similar discriminative ability across different areas. The discriminative ability of each model was confirmed using external validation datasets. The invasive risk model with only HbA1c was well-calibrated in the validation cohort.</p><p>Conclusion: Our invasive risk models are expected to discriminate between high- and low-risk individuals with T2DM in a Japanese population.</p>

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