Cognition, psychiatric symptoms and conversion to dementia in Parkinson’s disease
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
Parkinson’s disease (PD) is a complex neurodegenerative disorder which can have a significant effect on a patient’s quality of life. Psychiatric symptoms and cognitive decline are common, with dementia (PDD) ultimately occurring in approximately 90% of patients. Mild cognitive impairment in PD (PD-MCI) is an intermediate state of cognitive decline, where patients are at a higher risk of progression to PDD than non-PD-MCI patients. The high rates of patients who develop PDD demonstrate that it is pertinent to have indicators of imminent PDD; particularly should a preventative therapy ever become available. Therefore, the aim of my PhD project was to use cognitive and neuropsychiatric measures to predict cognitive decline within a four-year period.
Firstly, we examined permitted variations within Movement Disorder Society Task Force (MDS-TF) Level II diagnostic PD-MCI criteria. We aimed to identify a PD-MCI criterion which optimally captured individuals who later progressed to PDD. To evaluate this, we followed 121 non-demented PD patients for up to 4.5 years; 21% converted to PDD over this period. Three unique groups of patients were classified as PD-MCI using baseline neuropsychological assessments. Each patient was required to have two impaired cognitive test scores, with impairment defined as (1) -2SD, (2) -1.5SD or (3) -1SD below normative data. Relative risk (RR) of PDD for each criterion was calculated, with the -1.5SD criterion found to be optimal for maximizing progression to PDD over four-years.
Secondly, another variation within the MDS-TF PD-MCI criteria was examined - whether the impaired tests need to occur within a single cognitive domain or only across two or more cognitive domains. The same sample of PD patients was reassessed to determine (1) RR of PDD when two impairments at -1.5SD existed within one cognitive domain, followed by (2) RR of PDD in the unique group whose two impairments at -1.5SD did not exist within one cognitive domain. The -1.5SD cut-off produced a high RR of PDD only when two impairments were identified within one cognitive domain (7.2, 95% confidence interval (CI) = 3.4–16.6, p<0.0001). This suggests that if the intent of a PD-MCI diagnosis is to detect increased risk of PDD in the next four years, optimal criteria should identify at least two impairments at -1.5SD within a single cognitive domain.
Next, we examined the number of tests permitted per cognitive domain by the MDS-TF criteria. We tested a reduced test battery of only two tests per cognitive domain, to determine if it could identify PD-MCI patients who were at risk of PDD within the next four-years. Tests were ranked for each cognitive domain based on the number of PD-MCI level impairments they identified. Subsequently, we used an improved methodology, logistic regression, to select two tests sensitive to PDD over four-years in each of five cognitive domains. The 10 neuropsychological test battery consisted of map search, digit ordering (Attention), Stroop interference, Trails B (Executive), picture completion, Rey copy (Visuospatial), CVLT-II SF free recall, Rey-short delay (Memory), DRS-2 similarities and ADAS-Cog language measures (Language). To determine if at-risk patients could be identified RR was conducted on an updated sample of 138 PD patients; 28 progressed to PDD. Using this 10 neuropsychological test battery, patients who classified as PD-MCI defined by ‘two impairments at -1.5SD in one cognitive domain’ had an equivalent RR (7.0, 95% CI 3.8-12.6) to the same group classified using the full 24 neuropsychological test battery (RR = 6.9, 95% CI 3.3-14.6). PD-MCI in patients with ‘one impairment in each of two cognitive domains’ now showed significance (RR = 3.6, 95% CI 1.3-9.5), unlike when the same criterion when applied to the 24 neuropsychological test battery. A modified PD-MCI criterion of ‘two impairments in any of the 10 neuropsychological tests’ was used and showed a similar RR (7.1, 95% CI 3.2-16.1) to the PD-MCI ‘two impairments in one cognitive domain’ criterion. This study demonstrated that a 10 neuropsychological test battery can identify PD patients at-risk of PDD within four-years and demonstrated that a modified PD-MCI criterion (‘two impairments in any 10 neuropsychological tests’) can be used when the battery consists of tests sensitive to PDD.
Lastly, the relationship between neuropsychiatric symptoms in PD and progression to dementia was explored. One-hundred-and-twenty-three non-demented PD patients, followed over 3.5-4.5 years were included; 27 progressed to PDD. All received comprehensive Level II neuropsychological testing and neuropsychiatric evaluations. ROC analysis was used to analyse whether neuropsychiatric measures at study entry were associated with future PDD progression. Patient-reported hallucinations was the only neuropsychiatric measure which related to future progression to PDD (PD Questionnaire hallucinations measure: AUC=0.70, CI=0.60-0.80; Unified PD Rating Scale hallucinations measure: AUC=0.69, 95% CI=0.57-0.80). By contrast, hallucinations reported by the patient’s significant other on the Neuropsychiatric Inventory did not discriminate patients. Neither patient-reported hallucinations (OR=1.70, 95% CI=0.73-4.03) nor motor function (OR=1.02, 95% CI=0.97-1.09) were found to add any additional useful information above global cognitive ability (OR=26.34, 95% CI=6.44-184.71) and age (OR=1.28, 95% CI=1.11-1.54) for predicting PDD. Cognitive ability and age were stronger predictors of conversion to PDD within the next four-years than any neuropsychiatric measures tested.
The findings of this thesis show that MDS-TF PD-MCI criteria can identify patients at-risk of PDD within a four-year period, even when a reduced 10 neuropsychological test battery is used for classification. Cognition and age were found to be more useful at predicting future PDD than any neuropsychiatric symptom assessed. Hence, specific PD-MCI criteria may be used as an additional tool to enrich samples for disease modifying interventions.