medwireNews: Adding cerebrospinal fluid (CSF) assessment and dopamine transporter (DAT) imaging data to age and clinical assessment improves cognitive impairment prediction in newly diagnosed patients with Parkinson’s disease, study findings indicate.
For the cohort study – Parkinson’s Progression Markers Initiative (PPMI) – the ability of various clinical, imaging, biological, and genetic biomarkers to predict cognitive impairment were compared for 390 drug-naïve patients whose Montreal Cognitive Assessment scores were determined at baseline and again at 2 years.
Of the initial cohort, 314 had complete data available at 2 years and, of these, 52 were classified as having mild cognitive impairment or dementia, report Anette Schrag (University College London, UK) and colleagues.
Multivariate analysis showed that age was the strongest single clinical predictor of cognitive decline at 2 years in the newly diagnosed patients, with an area under the receiver operating characteristic curve (AUC) of 0.68.
Combining age with clinical variables (University of Pennsylvania Smell Inventory Test [UPSIT] scores; Rapid Eye Movement Sleep Behavior Disorder Screening questionnaire [RBDSQ]; Geriatric Depression Scale; and Movement Disorder Society Unified Parkinson’s Disease Rating Scale motor scores) improved the prediction accuracy to an AUC of 0.76.
Similar improvements in prediction accuracy were achieved with the addition of CSF markers or DAT imaging results to age, with respective AUCs of 0.74 and 0.76, respectively.
But combining five of the variables most strongly associated with cognitive impairment from across the different biomarker types, namely age, UPSIT score, RBDSQ score, CSF beta-amyloid (Aβ)42, and mean caudate uptake, in one model, significantly increased the AUC to 0.80 compared with age alone.
The model performed equally well across 10 different samples. And the team gives one example of a 70-year-old man with an UPSIT score of 22, an RBDSQ score of 5, a CSF Aβ42 of 399 pg/mL, and mean caudate uptake of 1.99 striatal binding ratio, for whom the predicted risk of cognitive impairment at 2 years was 13%. This compared with 5% if he was 50 years old and 34% if he was 70 years old and had an UPSIT score of 17, an RBDSQ score of 7, a CSF Aβ42 of 310 pg/mL, and a mean caudate uptake of 1.79 striatal binding ratio.
The team comments in The Lancet Neurology: “Combining these clinical and biomarker variables could be helpful in clinical practice, but most importantly, in clinical trials aiming to identify people at risk of cognitive decline; in this context, being able to estimate a 5% risk, compared with a 13% or a 34% risk, is likely to be clinically useful.”
Nour Majbour and Omar El-Agnaf, both from Hamad Bin Khalifa University in Doha, Qatar, point out in a related comment that “[a]lthough other studies have assessed several predictors for cognitive decline in Parkinson’s disease, this is the first study to assess a wide range of markers in the same cohort.”
They conclude: “This research could help to define reliable makers of cognitive impairment, identify high-risk individuals who are good candidates for clinical trials and, more importantly, establish strategies to delay and perhaps halt cognitive impairment.”
By Lucy Piper
https://www.medwirenews.com/parkinson-s-disease/neurology/biomarker-combination-predicts-early-parkinson-s-cognitive-impai/11080596
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