New tool may identify Parkinson’s patients at risk of cognitive problems
Age, genetic changes, and cognitive test scores helped estimate five-year risk
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An illustration of a human brain. Researchers developed a model that may help predict the risk of cognitive problems in people with Parkinson's disease over five years. (Photo from iStock)
- A new predictive tool may help estimate the five-year risk of developing memory and thinking difficulties in people with Parkinson’s disease.
- Key risk factors include older age, GBA gene mutations, self-reported cognitive difficulties, and slower information-processing speed.
- The model requires validation in independent patient groups before it can be used in clinical practice.
A new model that combines clinical, cognitive, and genetic information may help estimate the risk of developing memory and thinking difficulties over five years in people with Parkinson’s disease, according to a U.S. study.
Older age, mutations in the GBA gene, self-reported cognitive difficulties, and lower scores on a test measuring how quickly people process information were among the strongest predictors.
Five-year cognitive impairment risk varied widely
The model identified groups with estimated five-year rates of cognitive impairment ranging from 10% to 66%.
Although the model still needs to be tested in a separate group of patients, “this tool may facilitate individualized risk assessment and prognostic counseling,” the researcher wrote.
The study, “A Multimodal Nomogram Predicting the Risk of Cognitive Impairment in Parkinson Disease,” was published in Movement Disorders Clinical Practice.
Parkinson’s is best known for its motor symptoms, such as tremors, stiffness, and slowed movement. But many people with the disease also develop cognitive problems that affect memory, attention, and thinking.
These difficulties may begin as mild cognitive impairment, when changes in memory or thinking are noticeable but people can generally manage daily activities independently. Some may later develop dementia.
Although several factors have been linked to cognitive decline in Parkinson’s, it remains difficult to predict who will develop these problems.
To help address this challenge, a researcher at Virginia Commonwealth University developed a tool that combines multiple types of patient information to estimate the five-year risk of cognitive impairment.
The analysis used data from what is now known as the Parkinson’s Precision Medicine Initiative (PPMI), an international study that tracks Parkinson’s progression over time.
Study tracked cognitive changes in 1,188 Parkinson’s patients
The analysis included 1,188 people with Parkinson’s who had normal cognitive function at their first assessment. Their average age was 62.5 years, and 60.9% were men. Participants were followed for up to 13 years (median follow-up was three years).
The researcher evaluated 27 potential predictors, including age, sex, education, genetic variants, movement symptoms, cognitive test scores, mental health and behavioral symptoms, and the ability to perform daily activities.
Of these, 14 factors were selected for a nomogram, a scoring system that combines individual characteristics to estimate the likelihood of an outcome.
During follow-up, 457 participants (38.5%) developed cognitive impairment. At first detection, 446 had mild cognitive impairment, and 11 had dementia.
The strongest predictors included age, mutations in the GBA gene (a known genetic risk factor), cognitive complaints, and scores on the Symbol Digit Modalities Test, which measures information-processing speed by having people match symbols with numbers.
Each additional year of age was associated with a 5% higher rate of developing cognitive impairment over time. People carrying a GBA mutation had approximately twice the rate of developing cognitive impairment as those without such mutations.
People reporting greater cognitive difficulties were also more likely to develop impairment over time, while those with better information-processing speed had lower rates of impairment.
Sleep and autonomic symptoms also helped predict cognitive problems
Other factors that contributed to the model included symptoms associated with REM sleep behavior disorder, a condition in which people physically act out their dreams. Symptoms of autonomic dysfunction, which affects automatic body functions such as blood pressure regulation, heart rate, and digestion, also contributed, as did difficulties with daily activities.
During internal validation, the model achieved a five-year area under the curve (AUC) of approximately 0.78, indicating its ability to distinguish between people who developed cognitive impairment and those who did not. On this measure of predictive performance, 0.5 represents performance no better than chance, while 1.0 represents perfect discrimination.
When participants were divided into three groups based on their predicted risk, the estimated rates of cognitive impairment over five years were 10% in the lowest-risk group, 34% in the intermediate-risk group, and 66% in the highest-risk group.
A second model developed without genetic information performed similarly, suggesting that the approach may also be useful when genetic testing is unavailable.
The researcher cautioned that the model had only been internally validated using data from the same study population. He noted that it must be tested in separate, more diverse groups of patients before it can be used in clinical practice.
If confirmed, the tool may “guide the intensity and frequency of cognitive monitoring, inform discussions about prognosis and advance care planning,” the researcher concluded.
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