After a Parkinson's diagnosis, one of the first questions a person asks is, "What is going to happen to me?" People with Parkinson's disease (PD) understandably want to know how their symptoms will change over time. But because everyone follows a unique course with the disease, it can be hard to predict exactly what the future will hold.
A recent study published in JAMA Neurology may offer clues to how a person will fare with Parkinson's. To find what factors at diagnosis might predict how disease progresses, Eduardo De Pablo-Fernández, MD, and colleagues at University College London examined the medical records of 111 people with autopsy-confirmed PD. They looked at how old a person was at diagnosis, what movement symptoms and non-movement symptoms (such as cognitive problems and REM sleep behavior disorder) they had, and how severe they were. Researchers also calculated the time from diagnosis to end of life and, if they occurred, recurrent falls, need for a wheelchair, dementia (significant memory and thinking problems) and move to a nursing home. The researchers also matched symptoms and disease course with brain changes at autopsy.
Based on their findings, the researchers separated people with Parkinson's into three subtypes at diagnosis to predict future progression: mild-motor predominant, intermediate and diffuse malignant. People in the first group were diagnosed in their mid-50s, had less severe movement symptoms and experienced a slower progression. Those in the latter group were diagnosed around age 70, had less benefit from Parkinson's medication and experienced a faster progression of disease.
"We can see by looking back at the first signs of symptoms that the subtypes do predict how the disease will progress," said Dr. De Pablo-Fernández. "This analysis suggests that we may be able to use this type of classification to help guide treatment, as well as help patients better understand their disease course."
The results of this study build on previous knowledge -- that people with young-onset PD tend to progress more slowly and those who are older may more quickly develop age-related conditions such as dementia and falls. They give more detail around a complex disease that doctors see differs tremendously from one person to the next but researchers are still working to determine how and why.
This subtyping system isn't ready for widespread use because it's based on medical chart review of a relatively small number of patients. Additional work is necessary to confirm the results in a larger population of people with PD.
And a number of MJFF studies and grantees are pursuing similar findings. Our Parkinson's Progression Markers Initiative (PPMI) follows people at-risk of Parkinson's and from the early stages of disease to better understand early predictors of PD onset and progression. MJFF-funded scientists at the National Institutes of Health applied machine-learning techniques to PPMI data to identify slow, moderate and fast progressor profiles, and our Foundation has given $1 million to IBM research to create other predictive models from the PPMI data set.
These projects are steps toward understanding how individuals fare after diagnosis. This can not only direct care decisions and future planning, but also to optimize clinical trials by, for example, testing therapies in the best populations of patients.
