The derivation and validation of a new prediction algorithm for assessing the risk of developing type 2 diabetes in a very large and unselected population with appropriate weightings for ethnicity and social deprivation were performed with the help of two large cohorts (n=2,540,753 patients in the derivation cohort and n=1,232,832 patients in the validation cohort). The QDScore that was developed is the first risk prediction algorithm to estimate 10-year risk of diabetes, which included social deprivation and ethnicity. Moreover, the algorithm does not require laboratory tests and therefore can be used in clinical settings and for self assessment. On this basis, the QDScore could be used to identify individuals at high-risk of developing diabetes and who might benefit from interventions to reduce their risk. In the editorial discussing the paper, the authors underline the strength of the QDScore, which is that the algorithm was derived and validated in millions of individuals who were prospectively followed for 10 years. The incorporation of the QDScore into practice computer programs is not likely to increase doctor workload but would rather help physicians identify individuals at high risk of diabetes. However, because it requires a computer, the use of the QDScore may be difficult for individuals in most developing countries.
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