Data scientists have used clinical data to help predict how the incurable neurological condition amyotrophic lateral sclerosis (ALS) will progress in individual patients, offering hope for better management and quicker trials of new treatments.
Affecting up to 5,000 adults in the UK at any one time, ALS (also called motor neurone disease or Lou Gehrig’s disease) leaves patients unable to move, talk, swallow and eventually breathe.
The latest research, led by Professor Joanna Holbrook from the NIHR Southampton Biomedical Research Centre and published in the journal PLOS one, could help to explain why this muscle wasting disease progresses much faster in some patients than others.
Better prediction of disease progression could enable smaller and more targeted clinical trials, which focus on groups of patients with the same form of the disease.
Most ALS patients only survive 3-5 years from the point of diagnosis, but this varies from person to person. Some people can live up to ten years and in a few rare cases, such as Professor Stephen Hawking, even longer.
This study set out to use existing patients’ clinical data to predict how fast the disease would progress.
The research team analysed anonymous data from people with ALS in who had taken part in clinical trials, stored in the PROACT database, collected by the Prize4Life foundation.
Using this data, they developed an algorithm based on four indicators (weight, alkaline phosphatase, albumin and creatine kinase) that could predict the rate of disease progression and likelihood of survival over the course of the two year period covered.
The algorithm will aid the study of the role of these indicators and other factors in the slower and faster forms of the disease, opening the potential for targeted treatments for specific groups of patients.