Predicting diabetes - clinical, biological and genetic approaches: the D.E.S.I.R. Study.
2008
Balkau, Beverley | Lange, Céline | Fezeu, Leopold | Tichet, Jean | de Lauzon-Guillain, Blandine | Czernichow, Sébastien | Fumeron, Frédéric | Froguel, Philippe | Vaxillaire, Martine | Cauchi, Stéphane | Ducimetière, Pierre | Eschwège, Eveline | Recherche en épidémiologie et biostatistique ; Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Institut inter-Régional pour la SAnté (IRSA) | Nutrition, hormones et cancer: épidémiologie et prévention (E3N) ; Epidémiologie, sciences sociales, santé publique (IFR 69) ; Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Institut Gustave Roussy (IGR)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Unité de Recherche en Epidémiologie Nutritionnelle (UREN) ; Université Paris 13 (UP13)-Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [Cnam] (Cnam)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Déterminants génétiques du diabète de type 2 et de ses complications vasculaires ((U 695)) ; Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM) | Génétique des maladies multifactorielles (GMM) ; Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS) | The D.E.S.I.R. study has been supported by INSERM contracts with CNAMTS, Lilly, Novartis Pharma and Sanofi-Aventis; by INSERM (Réseaux en Santé Publique, Interactions entre les déterminants de la santé), the Association Diabète Risque Vasculaire, the Fédération Française de Cardiologie, La Fondation de France, ALFEDIAM, ONIVINS, Ardix Medical, Bayer Diagnostics, Becton Dickinson, Cardionics, Merck Santé, Novo Nordisk, Pierre Fabre, Roche, Topcon.
International audience
Afficher plus [+] Moins [-]anglais. Objectives- To provide a simple clinical diabetes risk score; to identify characteristics which predict later diabetes using variables available in clinic, then additionally biological variables and polymorphisms. Research design and methods- Incident diabetes was studied in 1863 men and 1954 women, 30-65 years at baseline, by treatment or by fasting plasma glucose >/= 7.0 mmol/l at 3-yearly examinations over nine years. Sex-specific logistic regression equations were used to select variables for prediction. Results- 140 men, 63 women developed diabetes. The predictive clinical variables were: waist circumference and hypertension in both sexes; for men: smoking, for women: diabetes in the family. Discrimination, as measured by the areas under the receiver operating curves (AROC), were 0.713 for men and 0.827 for women, a little higher than for the FINDRISC score, with fewer variables in the score. Combining clinical and biological variables, the predictive equation included for men: fasting glucose, waist circumference, smoking, square-glutamyltransferase; for women fasting glucose, BMI, triglycerides, diabetes in family. The number of TCF7L2 and IL6 deleterious alleles was predictive in both sexes, but after including the above clinical and biological variables, this variable was only predictive in women (p < 0.03) and the AROC statistics increased only marginally. Conclusions- The best clinical predictor of diabetes is adiposity, and baseline glucose is the best biological predictor. Clinical and biological predictors differed marginally between men and women. The genetic polymorphisms added little to the prediction of diabetes.
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