It may be possible to assess the risk of developing dementia by analyzing information gathered during routine visits to the family doctor, according to research published in the open access journal BMC Medicine.
Researchers from University College London developed an algorithm that uses routinely collected data to predict a five-year risk of dementia as part of an NIHR-funded study. The team identified 930,395 patients without previous records of dementia, cognitive impairment or memory problems. Using these patients’ records, the researchers built a simple computer algorithm that predicts the risk of future dementia diagnoses within five years. This algorithm, the Dementia Risk Score, could help rule out patients at very low risk for conditions such as Alzheimer’s disease in primary care.
The researchers used randomly selected anonymized data, collected by 377 UK general practices between 2000 and 2011, recorded in The Health Improvement Network (THIN) database. The database contains patient records for around 6% of general practices in the UK.
Based on known possible risk factors for dementia recorded in the THIN database, the researchers examined four variables as possible predictors of dementia risk: socio-demographic measures (e.g., age, sex, social deprivation); health and lifestyle measurements (e.g., alcohol use, Body Mass Index, blood pressure); medical diagnoses (e.g. diabetes, coronary heart disease); and use of prescription medication. The researchers checked these variables for their association with newly recorded dementia diagnoses during a five-year follow-up period.
To validate the accuracy of their algorithm, the researchers selected an additional 264,224 patients, without previous recordings of dementia from 95 different UK general practices.
Both groups of patients – those selected during the development and those selected during the validation phase of the study – were divided into sub-groups of people aged 60-79 and 80-95 years. The groups were divided based on previous findings that the risk of dementia increases sharply at age 80, as well as an observed difference in the distribution of risk factors between people aged 60-79 and older individuals.
The algorithm performed well in predicting risk for the 60-79 age group but not in the 80-95 age group. This suggests that risk assessment models for dementia using traditional risk factors do not perform well in patients aged 80 years or older and a different approach may be needed for this group.
Risk factors that are poorly recorded in UK primary care, such as family history of dementia or physical activity, could not be included in the score. As the current model is based on UK patient data, the researchers suggest further tests to assess the performance of their risk score for populations outside of the UK.
Lead researcher, Kate Walters, said: “Before this score is widely used we would recommend that it is independently tested in further populations of people, and that the ethical implications of using it in practice are considered.”
She added: “The score could be especially useful for identifying people at a very low risk of dementia (as recorded by their GP). This could help general practitioners working with people who are anxious about developing dementia.”
T: +44 (0)20 3192 2744
Notes to editor:
1. Predicting dementia risk in primary care: development and validation of the Dementia Risk Score (DRS) using routinely collected data.
Walters K, Hardoon S, Petersen I, Iliffe S, Omar RZ, Nazareth I, Rait G
BMC Medicine 2016
Article available at journal website.
Please name the journal in any story you write. If you are writing for the web, please link to the article. All articles are available free of charge, according to BioMed Central's open access policy.
3. With an ethos of transparency and accessibility, BMC Medicine is an open access, open peer-reviewed general medical journal publishing outstanding and influential research in all areas of clinical practice, translational medicine, public health, policy, and general topics of interest to the biomedical research community. As the flagship medical journal of the BMC series, we also publish stimulating debates and reviews as well as unique forum articles and concise tutorials.
4. BioMed Central is an STM (Science, Technology and Medicine) publisher which has pioneered the open access publishing model. All peer-reviewed research articles published by BioMed Central are made immediately and freely accessible online, and are licensed to allow redistribution and reuse. BioMed Central is part of Springer Nature, a major new force in scientific, scholarly, professional and educational publishing, created in May 2015 through the combination of Nature Publishing Group, Palgrave Macmillan, Macmillan Education and Springer Science+Business Media.
5. The National Institute for Health Research (NIHR) is funded by the Department of Health to improve the health and wealth of the nation through research. Since its establishment in April 2006, the NIHR has transformed research in the NHS. It has increased the volume of applied health research for the benefit of patients and the public, driven faster translation of basic science discoveries into tangible benefits for patients and the economy, and developed and supported the people who conduct and contribute to applied health research. The NIHR plays a key role in the Government’s strategy for economic growth, attracting investment by the life-sciences industries through its world-class infrastructure for health research. Together, the NIHR people, programmes, centres of excellence and systems represent the most integrated health research system in the world. For further information, visit the NIHR website(www.nihr.ac.uk).