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Leif Groop

Leif Groop

Principal investigator

Leif Groop

HAPT2D : high accuracy of prediction of T2D with a model combining basic and advanced data depending on availability

Author

  • Barbara Di Camillo
  • Liisa Hakaste
  • Francesco Sambo
  • Rafael Gabriel
  • Jasmina Kravic
  • Bo Isomaa
  • Jaakko Tuomilehto
  • Margarita Alonso
  • Enrico Longato
  • Andrea Facchinetti
  • Leif C. Groop
  • Claudio Cobelli
  • Tiinamaija Tuomi

Summary, in English

OBJECTIVE: Type 2 diabetes arises from the interaction of physiological and lifestyle risk factors. Our objective was to develop a model for predicting the risk of T2D, which could use various amounts of background information.

RESEARCH DESIGN AND METHODS: We trained a survival analysis model on 8483 people from three large Finnish and Spanish data sets, to predict the time until incident T2D. All studies included anthropometric data, fasting laboratory values, an oral glucose tolerance test (OGTT) and information on co-morbidities and lifestyle habits. The variables were grouped into three sets reflecting different degrees of information availability. Scenario 1 included background and anthropometric information; Scenario 2 added routine laboratory tests; Scenario 3 also added results from an OGTT. Predictive performance of these models was compared with FINDRISC and Framingham risk scores.

RESULTS: The three models predicted T2D risk with an average integrated area under the ROC curve equal to 0.83, 0.87 and 0.90, respectively, compared with 0.80 and 0.75 obtained using the FINDRISC and Framingham risk scores. The results were validated on two independent cohorts. Glucose values and particularly 2-h glucose during OGTT (2h-PG) had highest predictive value. Smoking, marital and professional status, waist circumference, blood pressure, age and gender were also predictive.

CONCLUSIONS: Our models provide an estimation of patient's risk over time and outweigh FINDRISC and Framingham traditional scores for prediction of T2D risk. Of note, the models developed in Scenarios 1 and 2, only exploited variables easily available at general patient visits.

Department/s

  • Diabetic Complications
  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence of Diabetes Research in Sweden

Publishing year

2018-04-01

Language

English

Pages

331-341

Publication/Series

European Journal of Endocrinology

Volume

178

Issue

4

Document type

Journal article

Publisher

Society of the European Journal of Endocrinology

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Diabetic Complications
  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 1479-683X