The Challenge of Measuring Quality of Life in Huntington's Disease
Author(s)
Grzęda M1, Spray I1, Johnston E2, Thorpe J2, Moldovan R3, Landwehrmeyer B4
1Galen Research, Manchester, UK, 2Galen Research, Manchester, Greater Manchester, UK, 3Manchester Centre for Genomic Medicine, Manchester, Greater Manchester, UK, 4Ulm University Hospital, Ulm, Baden-Württemberg, Germany
Presentation Documents
OBJECTIVES: Huntington’s Disease (HD) is a rare, hereditary condition characterized by the gradual degeneration of nerve cells in the brain. Degeneration affects motor control, cognition, and behaviour. Existing literature emphasizes the importance of Quality of Life (QoL) for HD patients. The progression of the disease presents methodological challenges when assessing QoL in individuals with HD. Challenges include cognitive symptoms that can hinder questionnaire completion. To address this, researchers can employ proxy-reported measures, allowing continued QoL assessment even when patients are no longer able to complete questionnaires themselves. Leveraging the advantages of Rasch measurement theory, results from proxy-reported measures can be compared to self-reported measures.
METHODS: The HDmQOL, a 49-item draft questionnaire, in self-reported and proxy-reported formats, was tested with 250 respondents recruited from UK, Ireland, Germany, Czechia, and Italy. Once data collection is completed, Rasch analysis will be used to obtain comparable results between self- and proxy-reported measures.
RESULTS: Initial analyses were performed on partial data including 62 patients (52 carers) from the UK. Results suggest the QoL scale for people with HD has 25 items and the proxy- has 17 items, with 11 items common to both questionnaires. The results obtained for final versions of HDmQOL and HDmQOL-proxy indicate good data-model fit and psychometric characteristics for both scales (self-reported: chi-sq=49.6; df=50; p=0.488; PSI=0.885; proxy- : chi-sq=22.1; df=34; p=0.942; PSI=0.830). After both data sets were stacked, 31 items were entered into the model. The model estimates were anchored by HDmQOL responses to common items. A diagnostic tests applied showed good data-model fit of the common scale (chi-sq=69.0; df=62; p=0.240; PSI=0.859).
CONCLUSIONS: Results of initial analyses suggest good data model fit and the HDmQOL and HDmQOL-proxy can be placed on the same continuum, thus confirming that the cross-walk table can be justifiably prepared. Results of analyses performed on full data will be presented at the conference.
Conference/Value in Health Info
Value in Health, Volume 27, Issue 12, S2 (December 2024)
Code
MSR158
Topic
Clinical Outcomes, Patient-Centered Research
Topic Subcategory
Clinical Outcomes Assessment, Instrument Development, Validation, & Translation, Patient-reported Outcomes & Quality of Life Outcomes, Performance-based Outcomes
Disease
Mental Health (including addition), Neurological Disorders, Personalized & Precision Medicine