Diabetes predictor based on QResearch

A simple new score that could help to identify those at most risk of developing type 2 diabetes has been developed using the QResearch database, researchers have announced.

A study published on BMJ.com reveals details of QDScore, the new diabetes risk algorithm. The researchers say this can identify people at high risk of diabetes, enabling proactive intervention before the disease is developed.

They say the score uses information that is available in electronic health records or that patients themselves would be likely to know. It does not require laboratory tests, so it could be used in routine clinical practice, by national screening programmes or by the public themselves.

The researchers from Nottingham, Edinburgh and Queen Mary’s universities and NHS Bristol developed and validated the score using the QResearch database, which contains anonymised data from around 10m patients registered at EMIS practices across the UK.

They analysed the records of more than 2.5m patients registered at 355 GP practices across England and Wales over a period of 10 years to March 2008. All participants were aged between 25 and 79 and were free of diabetes at the start of the study.

Patients who were diagnosed with type 2 diabetes during the study period were identified from GP computer records.

After adjusting for all other variables, the risk of being diagnosed as having type 2 diabetes in both men and women was significantly associated with age, sex, ethnicity, body mass index, smoking status, family history of diabetes, social deprivation, treated high blood pressure, heart disease and use of corticosteroids.

The researchers found large variations in the risk of type 2 diabetes between different ethnic groups and also a marked difference by social deprivation.

The team then tested the performance of the QDScore by comparing the predicted risk and the observed risk at 10 years in a further 1.2m patients from a separate sample of practices. This showed the score to be highly accurate, the researchers said.

It also performed well when compared with another risk algorithm, known as the Cambridge risk score. The researchers say it is the first risk prediction algorithm to estimate the 10 year risk of diabetes using both ethnicity and social deprivation.

The QResearch database has already been used to produce the QRisk and QRisk2 formulaes which identify patients most at risk of developing cardiovascular disease.

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