New online tool to predict major depression

Dec 2 2008

A new universal test to predict the risk of someone succumbing to major depression has been developed by UCL (University College London) researchers. The online tool, predictD, could eventually be used by family doctors and local clinics to identify those at risk of depression for whom prevention might be most useful.

The risk algorithm, developed by a team led by UCL Professors Michael King and Irwin Nazareth, was tested in 6,000 people visiting their family doctor in six countries in Europe (UK, Spain, Portugal, the Netherlands, Slovenia and Estonia). Its accuracy was also tested in nearly 3,000 GP attendees in a further country, Chile, in South America. The study, published in the Archives of General Psychiatry, followed-up the participants at six and 12 months. The team modelled their approach on risk indices for heart disease, which provide a percentage risk estimate over a given time period. The algorithm was as accurate at predicting future episodes of depression as similar instruments developed in Europe to predict future risk of heart problems.

A website has been set up for the risk algorithm, at www.ucl.ac.uk/predict-depression/.

Further testing of the tool as an early detector of depression is planned in randomised trials of prevention in Europe. The team are also exploring the feasibility of using the instrument in China, with plans to set up a study on the prediction of depression in a Chinese community setting. This would be the first ever research initiative of its kind within Asia.

Professor Michael King, UCL Department of Mental Health Sciences, says: "Depression is a common problem throughout the world, but although we know how to treat it, we know very little about how to prevent its onset. We have ways of predicting the onset of heart disease or stroke, but none for predicting people's risk of major depression. Our study is one of the first to develop a risk algorithm for just this purpose."

"Risk tools such as ours are needed to focus more effort on preventing depression. For example, people identified as at risk by an online tool could be flagged on a GP's computer. Recognition of those at risk could help with watchful waiting or active support, such as restarting treatment in patients with a history of depression. Patients could also be advised on the nature of depression or on cognitive behaviour therapies to help reduce their risk of developing major depression."

"Major depression is now a leading cause of illness and disability world-wide and reducing its prevalence is one of the greatest public health challenges of the twenty-first century. Depression will rank second to cardiovascular disease as a global cause of disability by 2020. Up to a quarter of people who visit their doctor experience major depression, with relapses frequently occurring for up to 10 years."

"The next stage of our research will be to establish how GPs could use our tool to help prevent the onset of depression. We are hoping to run a large-scale trial to explore the tool's use in prevention."

http://www.ucl.ac.uk/media/library/depressiontest