Friday, June 19, 2009

QDScore Helps Estimate 10-Year Risk for Diabetes

by Laurie Barclay & Charles Vega
Medscape News

March 19, 2009 — The QDScore, which includes both social deprivation and ethnicity, is the first risk prediction algorithm to estimate the 10-year risk for diabetes, according to the results of a prospective open cohort study reported in the March 18 Online First issue of the BMJ.

"Although several algorithms for predicting the risk of type 2 diabetes have been developed, no widely accepted diabetes risk prediction score has been developed and validated for use in routine clinical practice," write Julia Hippisley-Cox, from University Park, Nottingham, United Kingdom, and colleagues. "Previous studies have been limited by size, and some have performed inadequately when tested in ethnically diverse populations. A new diabetes risk prediction tool with appropriate weightings for both social deprivation and ethnicity is needed given the prevalence of type 2 diabetes, particularly among minority ethnic communities, appreciable numbers of whom remain without a diagnosis for long periods of time."

The goal of this study was to develop and validate the QDScore for estimating 10-year risk of acquiring diagnosed type 2 diabetes during a 10-year period, with use of routinely collected data from an ethnically and socioeconomically diverse population

Obesity has been a growing problem in Western countries for decades, and a study by Christakis and Fowler suggests that social networks play a prominent role in the risk for obesity. Their research, which was published in the July 26, 2007, issue of the New England Journal of Medicine, demonstrated that an individual's risk of becoming obese increased by 57% if he or she had a friend who became obese in a given interval. Moreover, incident obesity among siblings and spouses also increased subjects' risk for obesity. However, the development of obesity in a neighbor had no significant effect on the personal risk for obesity.

The epidemic of obesity has led to a sharp increase in the prevalence of type 2 diabetes. The current study examines a tool to predict the risk for incident type 2 diabetes without the use of laboratory data

The risk tool, the QDScore, (www.qdscore.org) was calculated from the following variables, all of which were found to independently affect the risk for incident type 2 diabetes:
◦Age
◦Body mass index
◦Family history of diabetes
◦Smoking status
◦Treated hypertension
◦Use of corticosteroids
◦Diagnosed cardiovascular disease
◦Social deprivation, as measured by the Townsend deprivation scale
◦Ethnicity

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