Using machine learning to investigate the role of co-existing conditions in people with MS
Around 77% of people with MS also have additional health conditions which co-exist with their MS. These are known as comorbidities. The most common comorbidities include depression, anxiety, high blood pressure, high cholesterol, and chronic lung disease.
People with MS who have comorbidities such as depression and diabetes, can have faster MS progression and a poorer quality of life.
About the project
The researchers will use data collected from the UK MS Register and machine learning, a way of teaching computers to recognise patterns. They plan to answer to following questions:
- What are the effects of specific comorbidities on MS activity and quality of life for people with MS?
- What types of people with MS are most at risk of developing comorbidities and who is most likely to be severely affected?
Using information from this study, the researchers will be able to determine which comorbidities affect disease severity and quality of life in people with MS. They will also determine if factors such as a person’s age or sex along with a specific comorbidity may result in poorer outcomes.
How will it help people with MS?
Understanding the effects of comorbidities on disease progression in people with MS, and which people are most affected, could help people with MS choose the most appropriate treatment option.
For conditions with established treatments, like high blood pressure, this will highlight the benefits of managing those conditions effectively. It could help doctors decide when more aggressive treatments are needed or which people should prioritised for follow up.
The difference you can make
Many people with MS also have additional health conditions. Gaining insight into how these conditions influence MS progression can guide treatment choices and enhance quality of life. By donating to the MS Society, you are helping fund groundbreaking research like this.
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