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  • Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models.

Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models.

The lancet. Diabetes & endocrinology (2014-03-14)
Andre Pascal Kengne, Joline W J Beulens, Linda M Peelen, Karel G M Moons, Yvonne T van der Schouw, Matthias B Schulze, Annemieke M W Spijkerman, Simon J Griffin, Diederick E Grobbee, Luigi Palla, Maria-Jose Tormo, Larraitz Arriola, Noël C Barengo, Aurelio Barricarte, Heiner Boeing, Catalina Bonet, Françoise Clavel-Chapelon, Laureen Dartois, Guy Fagherazzi, Paul W Franks, José María Huerta, Rudolf Kaaks, Timothy J Key, Kay Tee Khaw, Kuanrong Li, Kristin Mühlenbruch, Peter M Nilsson, Kim Overvad, Thure F Overvad, Domenico Palli, Salvatore Panico, J Ramón Quirós, Olov Rolandsson, Nina Roswall, Carlotta Sacerdote, María-José Sánchez, Nadia Slimani, Giovanna Tagliabue, Anne Tjønneland, Rosario Tumino, Daphne L van der A, Nita G Forouhi, Stephen J Sharp, Claudia Langenberg, Elio Riboli, Nicholas J Wareham
ABSTRACT

The comparative performance of existing models for prediction of type 2 diabetes across populations has not been investigated. We validated existing non-laboratory-based models and assessed variability in predictive performance in European populations. We selected non-invasive prediction models for incident diabetes developed in populations of European ancestry and validated them using data from the EPIC-InterAct case-cohort sample (27,779 individuals from eight European countries, of whom 12,403 had incident diabetes). We assessed model discrimination and calibration for the first 10 years of follow-up. The models were first adjusted to the country-specific diabetes incidence. We did the main analyses for each country and for subgroups defined by sex, age (<60 years vs ≥60 years), BMI (<25 kg/m(2)vs ≥25 kg/m(2)), and waist circumference (men <102 cm vs ≥102 cm; women <88 cm vs ≥88 cm). We validated 12 prediction models. Discrimination was acceptable to good: C statistics ranged from 0·76 (95% CI 0·72-0·80) to 0·81 (0·77-0·84) overall, from 0·73 (0·70-0·76) to 0·79 (0·74-0·83) in men, and from 0·78 (0·74-0·82) to 0·81 (0·80-0·82) in women. We noted significant heterogeneity in discrimination (pheterogeneity<0·0001) in all but one model. Calibration was good for most models, and consistent across countries (pheterogeneity>0·05) except for three models. However, two models overestimated risk, DPoRT by 34% (95% CI 29-39%) and Cambridge by 40% (28-52%). Discrimination was always better in individuals younger than 60 years or with a low waist circumference than in those aged at least 60 years or with a large waist circumference. Patterns were inconsistent for BMI. All models overestimated risks for individuals with a BMI of <25 kg/m(2). Calibration patterns were inconsistent for age and waist-circumference subgroups. Existing diabetes prediction models can be used to identify individuals at high risk of type 2 diabetes in the general population. However, the performance of each model varies with country, age, sex, and adiposity. The European Union.

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Glycocholic acid hydrate, synthetic, ≥97% (HPLC)
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