Risk tool could better identify who would benefit from weight-loss medication on NHS

UK researchers have developed a prediction tool to identify those most at risk of obesity-related conditions and potentially inform use of weight loss injections.

It could be used alongside BMI to provide a more accurate and personalised way to identify who might benefit from closer monitoring, earlier intervention or intensified treatment, the team said.

The risk tool known as OBSCORE, needs further evaluation in clinical trials but could one day help the NHS to prioritise patients for weight loss medications, they added.

It was developed with data from 200,000 middle-aged adults taking part in the UK Biobank study, with a BMI score of 27 and over.

The team analysed more than 2,000 health factors ranging from simple measures such as age and sex, lifestyle information and blood biomarkers.

In all they identified 20 indicators that most effectively predict the risk of developing obesity-related diseases or complications.

There were substantial differences in risk profiles for the 18 obesity-related complications tested among individuals within the same BMI category.

And people identified as being at the highest risk were not always those with the highest BMI, the team reported in Nature Medicine.

A considerable proportion of individuals predicted to be at highest risk were people living with overweight rather than obesity, whose combination of metabolic and clinical factors increased their likelihood of developing complications, they added.  

Co-author Professor Nick Wareham, co-director of the Institute of Metabolic Science at the University of Cambridge, said the score would help with ‘more rational resource allocation’.

‘So, can we prescribe therapy to those people who are most likely to need it and most likely to benefit from it – which is what we should do within the NHS.’

Lead author Professor Claudia Langenberg, director of Queen Mary University of London’s Precision Healthcare University Research Institute and head of the computational medicine group at Berlin Institute of Health, said: ‘With obesity affecting a growing proportion of the global population, preventing its long-term health complications has become a major challenge for healthcare systems.

‘Our work shows how… large-scale health data can be used to develop data-driven frameworks that identify individuals at higher risk of developing complications and may help support more risk-based approaches to manage obesity.’ 

Naveed Sattar, professor of cardiometabolic medicine and honorary consultant at the University of Glasgow, pointed out that several variables in the study were not routinely accessible in NHS records currently.

And he noted for conditions like cardiovascular disease and type 2 diabetes there were already well-established risk scores in use.

‘Overall, this study represents a considered step towards more integrated risk prediction across multiple obesity‑related conditions, but considerable further refinement and validation will be needed before such an approach is suitable for routine clinical implementation. 

He added: ‘It is also worth noting that effective weight‑loss interventions are increasingly being evaluated across many obesity‑related conditions, and as treatment costs decline, the reliance on such risk scores may diminish over the coming decade.’