Factor Analysis and Clustering of the Movement Disorder Society-Non-Motor Rating Scale

Revisiting delusion subtypes in schizophrenia based on their underlying structures

A clear understanding of the pathophysiology of schizophrenia and related spectrum disorders has been limited by clinical heterogeneity. We investigated whether relative severity and predominance of one or more delusion subtypes might yield clinically differentiable patient profiles. Patients (N = 286) with schizophrenia spectrum disorders (SSD) completed the 21-item Peters et al. Delusions Inventory (PDI-21). We performed factor analysis followed by k-means clustering to identify delusion factors and patient subtypes. Patients were further assessed via the Brief Psychiatric Rating Scale, Brief Negative Symptom Scale, Digit Symbol and Digit Substitution tasks, use of cannabis and tobacco, and stressful life events. The overall patient sample clustered into subtypes corresponding to Low-Delusion, Grandiose-Predominant, Paranoid-Predominant, and Pan-Delusion patients. Paranoid-Predominant and Pan-Delusion patients showed significantly higher burden of positive symptoms, while Low-Delusion patients showed the highest burden of negative symptoms. The Paranoia delusion factor score showed a positive association with Digit Symbol and Digit Substitution tasks in the overall sample, and the Paranoid-Predominant subtype exhibited the best performance on both tasks. Grandiose-Predominant patients showed significantly higher tobacco smoking severity than other subtypes, while Paranoid-Predominant patients were significantly more likely to have a lifetime diagnosis of Cannabis Use Disorder. We suggest that delusion self-report inventories such as the PDI-21 may be of utility in identifying sub-syndromes in SSD. From the current study, a Paranoid-Predominant form may be most distinctive, with features including less cognitive impairment and a stronger association with cannabis use.

Expanded and Independent Spanish Validation of the MDS-Non Motor Rating Scale

Background

The Movement Disorder Society-sponsored Non-motor Rating Scale (MDS-NMS) assess the severity and disability caused by non-motor symptoms (NMS) in Parkinson's disease (PD).

Objective

This article encapsulates the formal process for completing this program and the data on the first officially approved non-English version of the MDS-NMS (Spanish).

Methods

The MDS-NMS translation program involves four steps: translation and back-translation; cognitive pre-testing to ensure that raters and patients understand the scale and are comfortable with its content; field testing of the finalized version; analysis of the factor structure of the tested version against the original English language version for the nine domains that could be analyzed in a confirmatory factor analysis. To be designated an "Official MDS translation," the confirmatory factor analysis Comparative Fit Index had to be ≥0.90.

Results

The Spanish MDS-NMS was tested in 364 native-Spanish-speaking patients with PD from seven countries. For all subjects with fully computable data with all domains of the MDS-NMS (n = 349), the Comparative Fit Index was ≥0.90 for the nine eligible domains. Missing data were negligible and moderate floor effect (42.90%) was found for the Non-Motor Fluctuations subscale. Item homogeneity coefficient was adequate, and the correlation of the MDS-NMS domains with other measures for related constructs was acceptable (r s ≥ 0.50).

Conclusions

The Spanish version of the MDS-NMS followed the IPMDS Translation Program protocol, reached the criterion to be designated as an Official Translation, and is now available on the MDS website.

The neuropsychiatry of Parkinson's disease: advances and challenges

In people with Parkinson's disease, neuropsychiatric signs and symptoms are common throughout the disease course. These symptoms can be disabling and as clinically relevant as motor symptoms, and their presentation can be similar to, or distinct from, their counterparts in the general population. Correlates and risk factors for developing neuropsychiatric signs and symptoms include demographic, clinical, and psychosocial characteristics. The underlying neurobiology of these presentations is complex and not well understood, with the strongest evidence for neuropathological changes associated with Parkinson's disease, mechanisms linked to dopaminergic therapy, and effects not specific to Parkinson's disease. Assessment instruments and formal diagnostic criteria exist, but there is little routine screening of these signs and symptoms in clinical practice. Mounting evidence supports a range of pharmacological and non-pharmacological interventions, but relatively few efficacious treatment options exist. Optimising the management of neuropsychiatric presentations in people with Parkinson's disease will require additional research, raised awareness, specialised training, and development of innovative models of care.

Identifying Parkinson's disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering

Identification of Parkinson's disease subtypes may help understand underlying disease mechanisms and provide personalized management. Although clustering methods have been previously used for subtyping, they have reported generic subtypes of limited relevance in real life practice because patients do not always fit into a single category. The aim of this study was to identify new subtypes assuming that patients could be grouped differently according to certain sets of related symptoms. To this purpose, a novel model-based multi-partition clustering method was applied on data from an international, multi-center, cross-sectional study of 402 Parkinson's disease patients. Both motor and non-motor symptoms were considered. As a result, eight sets of related symptoms were identified. Each of them provided a different way to group patients: impulse control issues, overall non-motor symptoms, presence of dyskinesias and pyschosis, fatigue, axial symptoms and motor fluctuations, autonomic dysfunction, depression, and excessive sweating. Each of these groups could be seen as a subtype of the disease. Significant differences between subtypes (P< 0.01) were found in sex, age, age of onset, disease duration, Hoehn & Yahr stage, and treatment. Independent confirmation of these results could have implications for the clinical management of Parkinson's disease patients.

Disentangling the PIGD classification for the prediction of cognitive impairment in de novo Parkinson's disease

Background

Postural Instability and Gait difficulties (PIGD) subtype has been associated with worse cognitive performance in Parkinson’s disease (PD).

Objective

To investigate whether PIGD subtype classification or PIGD-related clinical features predict the development of cognitive decline in de novo PD patients.

Methods

Data from 422 PD patients with de novo PD were obtained from the PPMI database. At follow-up (up to 6 years), patients were categorized as having cognitive impairment or not. Multivariate Cox survival analysis was carried out including motor subtype and individual MDS-UPDRS items defining PIGD phenotype as predictors. Previously validated clinical predictors of cognitive impairment were included in the model as covariates. Occurrence of cognitive impairment at follow-up was used as the time-to-event and Kaplan–Meier curve was generated.

Results

At baseline, 76 patients were classified as PIGD, 299 tremor-dominant and 47 as indeterminate. Development of cognitive impairment was not associated with PIGD subtype (p = 0.252). When individual MDS-UPDRS items were interrogated in the model, postural instability proved to be an independent predictor of cognitive impairment (HR = 2.045; 95%CI: 1.068–3.918; p = 0.031), while gait difficulties were not associated with cognitive decline (p = 0.870).

Conclusions

Our findings suggest that postural instability, as assessed by MDS-UPDRS III, may serve as a possible indicator of the risk of developing cognitive impairment in de novo PD patients rather than the PIGD phenotype.

Non-motor complications in late stage Parkinson's disease: recognition, management and unmet needs

Introduction: The burden of non-motor symptoms (NMS) is a major determinant of health-related quality of life in Parkinson's disease (PD), particularly at its late stage.Areas covered: The late stage is usually defined as the period from unstable advanced to the palliative stage, characterized by a combination of emerging treatment-resistant axial motor symptoms (freezing of gait, postural instability, falls and dysphagia), as well as both non-dopaminergic and dopaminergic NMS: cognitive decline, neuropsychiatric symptoms, aspects of dysautonomia, pain and sleep disturbances (insomnia and excessive day-time sleepiness). Here, the authors summarize the current knowledge on NMS dominating the late stage of PD and propose a pragmatic and clinically focused approach for their recognition and treatment.Expert opinion: The NMS progression pattern is complex and remains under-researched. While dopamine-dependent NMS may improve with dopamine replacement therapy, non-dopamine dependent NMS worsen progressively and culminate at the late stages of PD. Furthermore, some PD specific features could interact negatively with other comorbidities, multiple medication use and frailty - the evaluation of these aspects is important in the creation of personalized management plans in the late stage of PD.