TY - JOUR
T1 - Obtaining EQ-5D-5L utilities from the disease specific quality of life Alzheimer’s disease scale: development and results from a mapping study
AU - Rombach, Ines
AU - Iftikhar, Marvi
AU - Jhuti, Gurleen S.
AU - Gustavsson, Anders
AU - Lecomte, Pascal
AU - Belger, Mark
AU - Handels, Ron
AU - Castro Sanchez, Amparo Y.
AU - Kors, Jan
AU - Hopper, Louise
AU - Olde Rikkert, Marcel
AU - Selbæk, Geir
AU - Stephan, Astrid
AU - Sikkes, Sietske A. M.
AU - Woods, Bob
AU - Gonçalves-Pereira, Manuel
AU - Zanetti, Orazio
AU - Ramakers, Inez H. G. B.
AU - Verhey, Frans R. J.
AU - Gallacher, John
AU - ROADMAP Consortium
AU - Actifcare Consortium, null
AU - LeARN Consortium, null
AU - Landeiro, Filipa
AU - Gray, Alastair M.
PY - 2021/3
Y1 - 2021/3
N2 - Purpose: The Quality of Life Alzheimer’s Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available. Methods: Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error. Results: The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset. Conclusions: The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected.
AB - Purpose: The Quality of Life Alzheimer’s Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available. Methods: Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error. Results: The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset. Conclusions: The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected.
KW - Cross-walking
KW - Dementia
KW - Health related quality of life
KW - Mapping algorithm
KW - Preference based measures
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85092760168&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/33068236
U2 - 10.1007/s11136-020-02670-8
DO - 10.1007/s11136-020-02670-8
M3 - Article
C2 - 33068236
JO - Quality of Life Research
JF - Quality of Life Research
SN - 0962-9343
ER -