Mapping Actuarial Criteria for Parkinson’s Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes

Is PDQ-39 a reliable measure of quality of life of patients at advanced stages of Parkinson's disease considered for Deep Brain Stimulation

Purpose

Parkinson's disease (PD) significantly impedes, especially at its advanced stages, the health-related quality of life (QoL) of patients. The Parkinson's disease questionnaire (PDQ-39) is a widely-used measure assessing the impact of the disease on the patients' QoL. To date, the reliability of PDQ-39 has not been selectively evaluated for patients at a particular delineated stage of the PD progression. Against this backdrop, the study aimed firstly to evaluate comprehensively the internal consistency reliability of PDQ-39 and the constituent scales specifically for patients at the advanced stages of PD who were candidates for Deep Brain Stimulation (DBS) surgery, and secondly, to compare the Cronbach's alpha coefficients with those reported in other studies conducted with patients across all stages of the PD progression.

Methods

The sample included 36 Bulgarian patients (29 men and 7 women) at advanced stages of PD (Hoehn and Yahr stage 4), PD duration, M = 11.06, SD = 3.50). The internal consistency reliability of the questionnaire and the constituent scales was assessed using three criteria: Cronbach's alpha coefficients, inter-item and item-total correlations.

Results

The internal consistency reliability indicators were satisfactory for the entire instrument and for most of the scales and similar to those reported in previous studies. None of the scales had low internal consistency reliability results across the three criteria. Except for the Communication scale, seven of the eight scales had Cronbach's alpha values that were satisfactory or marginally below the cut off score. All scales had acceptable inter-item correlations. Three of the scales (Emotional Well-Being, Cognition and Communication) contained more than one item with non-satisfactory item-total correlations. With minor exceptions, the removal of the items with low item-total correlations either did not improve or improved marginally or even decreased the Cronbach's alpha coefficients of the respective scale. The Communication scale was the only scale with a Cronbach's alpha coefficient that was both low and comparatively different to other studies and had as well low item-total correlations for all constituent items, thus showing non-satisfactory results on two of the three internal consistency reliability estimates. In contrast, the Mobility scale met all three internal consistency reliability criteria.

Conclusion

PDQ-39 is a reliable tool for assessing the QoL of patients at advanced stages of PD across multiple health-related domains. The questionnaire can be recommended for inclusion in the best practice guidelines for evaluating DBS candidacy and the efficacy of DBS treatment for patients' QoL.

Perception of cognitive change by individuals with Parkinson's disease or essential tremor seeking deep brain stimulation: Utility of the cognitive change index

OBJECTIVE

The Cognitive Change Index (CCI-20) is a validated questionnaire that assesses subjective cognitive complaints (SCCs) across memory, language, and executive domains. We aimed to: (a) examine the internal consistency and construct validity of the CCI-20 in patients with movement disorders and (b) learn how the CCI-20 corresponds to objective neuropsychological and mood performance in individuals with Parkinson's disease (PD) or essential tremor (ET) seeking deep brain stimulation (DBS).

METHODS

216 participants (N = 149 PD; N = 67 ET) underwent neuropsychological evaluation and received the CCI-20. The proposed domains of the CCI-20 were examined via confirmatory (CFA) and exploratory (EFA) factor analyses. Hierarchical regressions were used to assess the relationship among subjective cognitive complaints, neuropsychological performance and mood symptoms.

RESULTS

PD and ET groups were similar across neuropsychological, mood, and CCI-20 scores and were combined into one group who was well educated (m = 15.01 ± 2.92), in their mid-60's (m = 67.72 ± 9.33), predominantly male (63%), and non-Hispanic White (93.6%). Previously proposed 3-domain CCI-20 model failed to achieve adequate fit. Subsequent EFA revealed two CCI-20 factors: memory and non-memory (p < 0.001; CFI = 0.924). Regressions indicated apathy and depressive symptoms were associated with greater memory and total cognitive complaints, while poor executive function and anxiety were associated with more non-memory complaints.

CONCLUSION

Two distinct dimensions were identified in the CCI-20: memory and non-memory complaints. Non-memory complaints were indicative of worse executive function, consistent with PD and ET cognitive profiles. Mood significantly contributed to all CCI-20 dimensions. Future studies should explore the utility of SCCs in predicting cognitive decline in these populations.

Moving towards a taxonomy of cognitive impairments in epilepsy: application of latent profile analysis to 1178 patients with temporal lobe epilepsy

In efforts to understand the cognitive heterogeneity within and across epilepsy syndromes, cognitive phenotyping has been proposed as a new taxonomy aimed at developing a harmonized approach to cognitive classification in epilepsy. Data- and clinically driven approaches have been previously used with variability in the phenotypes derived across studies. In our study, we utilize latent profile analysis to test several models of phenotypes in a large multicentre sample of patients with temporal lobe epilepsy and evaluate their demographic and clinical profiles. For the first time, we examine the added value of replacing missing data and examine factors that may be contributing to missingness. A sample of 1178 participants met the inclusion criteria for the study, which included a diagnosis of temporal lobe epilepsy and the availability of comprehensive neuropsychological data. Models with two to five classes were examined using latent profile analysis and the optimal model was selected based on fit indices, posterior probabilities and proportion of sample sizes. The models were also examined with imputed data to investigate the impact of missing data on model selection. Based on the fit indices, posterior probability and distinctiveness of the latent classes, a three-class solution was the optimal solution. This three-class solution comprised a group of patients with multidomain impairments, a group with impairments predominantly in language and a group with no impairments. Overall, the multidomain group demonstrated a worse clinical profile and comprised a greater proportion of patients with mesial temporal sclerosis, a longer disease duration and a higher number of anti-seizure medications. The four-class and five-class solutions demonstrated the lowest probabilities of a group membership. Analyses with imputed data demonstrated that the four-class solution was the optimal solution; however, there was a weak agreement between the missing and imputed data sets for the four-Class solutions (κ = 0.288, P < 0.001). This study represents the first to use latent profile analysis to test and compare multiple models of cognitive phenotypes in temporal lobe epilepsy and to determine the impact of missing data on model fit. We found that the three-phenotype model was the most meaningful based on several fit indices and produced phenotypes with unique demographic and clinical profiles. Our findings demonstrate that latent profile analysis is a rigorous method to identify phenotypes in large, heterogeneous epilepsy samples. Furthermore, this study highlights the importance of examining the impact of missing data in phenotyping methods. Our latent profile analysis-derived phenotypes can inform future studies aimed at identifying cognitive phenotypes in other neurological disorders.

Systematic review of data-driven cognitive subtypes in Parkinson disease

BACKGROUND AND PURPOSE

Recent application of the mild cognitive impairment concept to Parkinson disease (PD) has proven valuable in identifying patients at risk of dementia. However, it has sparked controversy regarding the existence of cognitive subtypes. The present review evaluates the current literature pertaining to data-driven subtypes of cognition in PD.

METHODS

Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, systematic literature searches for peer-reviewed articles on the topic of cognitive subtyping in PD were performed.

RESULTS

Twenty-two relevant articles were identified in the systematic search. Subtype structures showed either a spectrum of severity or specific domains of impairment. Domain-specific subtypes included amnestic/nonamnestic, memory/executive, and frontal/posterior dichotomies, as well as more complex structures with less definitive groupings. Preliminary longitudinal evidence showed some differences in cognitive progression among subtypes. Neuroimaging evidence provided insight into distinct patterns of brain alterations among subtypes.

CONCLUSIONS

Recurring phenotypes in the literature suggest strong clinical relevance of certain cognitive subtypes in PD. Although the current literature is limited, it raises critical questions about the utility of data-driven methods in cognitive research. The results encourage further integration of neuroimaging research to define the latent neural mechanisms behind divergent subtypes. Although there is no consensus, there appears to be growing consistency and inherent value in identifying cognitive subtypes in PD.