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BACKGROUND: Type 2 diabetes is common, costly and often goes unrecognised for many years. When patients are diagnosed, the majority exhibit associated tissue damage or established cardiovascular risk. Evidence is accumulating that earlier detection and management of diabetes and related metabolic abnormalities may be beneficial. We aimed to develop and evaluate a score based on routinely collected information to identify people at risk of having undetected diabetes. METHODS: A population-based sample of 1077 people, aged 40 to 64 years, without known diabetes, from a single Cambridgeshire general practice, underwent clinical assessment including an oral glucose tolerance test. In a separate 12-month study, 41 practices in southern England reported clinical details of patients aged 40 to 64 years with newly diagnosed Type 2 diabetes. A notional population was created by random selection and pooling of half of each dataset. Data were entered into a regression model to produce a formula predicting the risk of diabetes. The performance of this risk score in detecting diabetes was tested in an independent, randomly selected, population-based sample. RESULTS: Age, gender, body mass index, steroid and antihypertensive medication, family and smoking history contributed to the score. In the test population at 72% specificity, the sensitivity of the score was 77% and likelihood ratio 2.76. The area under the receiver-operating characteristic curve was 80%. CONCLUSIONS: A simple score, using only data that are routinely collected in general practice, can help identify those at risk of diabetes. This score could contribute to efficient earlier detection through case-finding or targeted screening.
Griffin et al. (Sat,) studied this question.