Risk Scores for Type 2 Diabetes Can Be Applied in Some Populations but Not All

Steno Diabetes Center, Niels Steensens Vej 2, 2820 Gentofte, Denmark.
Diabetes Care (Impact Factor: 8.42). 03/2006; 29(2):410-4. DOI: 10.2337/diacare.29.02.06.dc05-0945
Source: PubMed


Risk scores based on phenotypic characteristics to identify individuals at high risk of having undiagnosed diabetes have been developed in Caucasian populations. The impact of known risk factors on having undiagnosed type 2 diabetes differs between populations from different ethnic origin, and risk scores developed in Caucasians may not be applicable to other ethnic groups. This study evaluated the performance of one risk score in nine populations of diverse ethnic origin.
Data provided by centers from around the world to the DETECT-2 project were used. The database includes population-based surveys with information on at least 500 people without known diabetes having a 75-g oral glucose tolerance test. To date, 52 centers have contributed data on 190,000 individuals from 34 countries. In this analysis, nine cross-sectional studies were selected representing diverse ethnic and regional backgrounds. The risk score assessed uses information on age, sex, blood pressure treatment, and BMI.
This analysis included 29,758 individuals; 1,805 individuals had undiagnosed diabetes. The performance of the risk score varied widely, with sensitivity, specificity, and percentage needing further testing ranging between 12 and 57%, 72 and 93%, and 2 and 25%, respectively, with the worse performance in non-Caucasian populations. This variation in performance was related to differences in the association between prevalence of undiagnosed diabetes and components of the risk score.
A typical risk score developed in Caucasian populations cannot be applied to other populations of diverse ethnic origins.

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Available from: Dorte Vistisen, Jul 04, 2014
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    • "A number of prognostic models have been developed for predicting the risk of diabetes in Caucasians, but few are available for Asian populations [10] [11] [12] [13]. It is not clear whether these models can be applied to different populations where prevalence and risk factors might be different from the populations where the tools were developed. "
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