OBJECTIVE -Type 2 diabetes is a serious disease that is commonly undetected and for which screening is sometimes advocated. A number of risk factors are associated with prevalent undiagnosed diabetes. The use of routinely available information on these factors has been proposed as a simple and effective way of identifying individuals at high risk for having the disease. The objective of this study was to assess the effectiveness of the Cambridge risk score in a large and representative population. RESEARCH DESIGN AND METHODS-A risk score derived from data in a previous study was tested for its ability to detect prevalent undiagnosed hyperglycemia as measured by a GHb Ն6.0, 6.5, or 7% in 6,567 subjects aged 39 -78 years in the European Prospective Investigation of CancerϪNorfolk cohort.RESULTS -For a specificity of 78%, the risk score predicted a GHb of Ն7.0% in subjects aged 39 -78 years, with a sensitivity of 51% (95% CI 40 -62). The areas under the receiveroperating characteristic (ROC) curve for GHb Ն6.0, 6.5, and 7% were 65.7% (63.8 -67.6), 71.2% (68.4 -75.2), and 74.2% (69.5-79.0), respectively. The area under the ROC curve was not significantly reduced if data on family and smoking history were unavailable for any of the cut-offs for GHb.CONCLUSIONS -The risk score performed as well as other previously reported models in all age groups. We concluded that a simple risk score using data routinely available in primary care can identify people with an elevated GHb with reasonable sensitivity and specificity, and it could therefore form part of a strategy for early detection of type 2 diabetes. Diabetes Care 25:984 -988, 2002

Objectives-The aims of this study were to quantify the proportion of people diagnosed as having type 2 diabetes by standard 75 g oral glucose tolerance test, in a hypothetical screening programme, who would actually be false positives (false positive percentage), and the eVect on the false positive percentage of varying the time between repeat screens. We also calculated the duration in person years of exposure to undiagnosed disease in the population for each screening interval. Setting-Ely, Cambridgeshire, UK. Methods-We used the glucose tolerance data from 965 participants of the Ely Diabetes Project, who were tested 4.5 years apart, to calculate the population's between and within person variance for 2 hour plasma glucose, and constructed a probability matrix of observed v true glucose tolerance categories. The progression of the population between glucose tolerance categories was modelled assuming exponential times to progression. Results-After one year, 47.5% of test positives were disease free: almost half of those labelled with diabetes would not have the disease. For a 5 year interval, the false positive percentage was 27.6%, but the population would have been exposed to undiagnosed diabetes for 144 person years. Conclusions-Screening can be associated with both benefit and harm; the balance is dependent on characteristics of the disease and the screening programme. This study has quantified the trade oV between exposure to undiagnosed diabetes and false positive results to inform the debate about screening for type 2 diabetes. (J Med Screen 2000;7:91-96)