Validation of a self-completed Dystonia Non-Motor Symptoms Questionnaire.

OBJECTIVE: To develop and validate a novel 14-item self-completed questionnaire (in English and German) enquiring about the presence of non-motor symptoms (NMS) during the past month in patients with craniocervical dystonia in an international multicenter study. METHODS: The Dystonia Non-Motor Symptoms Questionnaire (DNMSQuest) covers seven domains including sleep, autonomic symptoms, fatigue, emotional well-being, stigma, activities of daily living, sensory symptoms. The feasibility and clinimetric attributes were analyzed. RESULTS: Data from 194 patients with CD (65.6% female, mean age 58.96 ± 12.17 years, duration of disease 11.95 ± 9.40 years) and 102 age- and sex-matched healthy controls (66.7% female, mean age 55.67 ± 17.62 years) were collected from centres in Germany and the UK. The median total NMS score in CD patients was 5 (interquartile range 3-7), significantly higher than in healthy controls with 1 (interquartile range 0.75-2.25) (P < 0.001, Mann-Whitney U-test). Evidence for intercorrelation and convergent validity is shown by moderate to high correlations of total DNMSQuest score with motor symptom severity (TWSTRS: rs  = 0.61), clinical global impression (rs  = 0.40), and health-related quality of life measures: CDQ-24 (rs  = 0.74), EQ-5D index (rs  = -0.59), and scale (rs  = -0.49) (all P < 0.001). Data quality and acceptability was very satisfactory. INTERPRETATION: The DNMSQuest, a patient self-completed questionnaire for NMS assessment in CD patients, appears robust, reproducible, and valid in clinical practice showing a tangible impact of NMS on quality of life in CD. As there is no specific, comprehensive, validated tool to assess the burden of NMS in dystonia, the DNMSQuest can bridge this gap and could easily be integrated into clinical practice.

Parkinson's Disease Subtypes Identified from Cluster Analysis of Motor and Non-motor Symptoms.

Parkinson's disease is now considered a complex, multi-peptide, central, and peripheral nervous system disorder with considerable clinical heterogeneity. Non-motor symptoms play a key role in the trajectory of Parkinson's disease, from prodromal premotor to end stages. To understand the clinical heterogeneity of Parkinson's disease, this study used cluster analysis to search for subtypes from a large, multi-center, international, and well-characterized cohort of Parkinson's disease patients across all motor stages, using a combination of cardinal motor features (bradykinesia, rigidity, tremor, axial signs) and, for the first time, specific validated rater-based non-motor symptom scales. Two independent international cohort studies were used: (a) the validation study of the Non-Motor Symptoms Scale (n = 411) and (b) baseline data from the global Non-Motor International Longitudinal Study (n = 540). k-means cluster analyses were performed on the non-motor and motor domains (domains clustering) and the 30 individual non-motor symptoms alone (symptoms clustering), and hierarchical agglomerative clustering was performed to group symptoms together. Four clusters are identified from the domains clustering supporting previous studies: mild, non-motor dominant, motor-dominant, and severe. In addition, six new smaller clusters are identified from the symptoms clustering, each characterized by clinically-relevant non-motor symptoms. The clusters identified in this study present statistical confirmation of the increasingly important role of non-motor symptoms (NMS) in Parkinson's disease heterogeneity and take steps toward subtype-specific treatment packages.