Cargando…

Measuring quality of life of patients with axial spondyloarthritis for economic evaluation

OBJECTIVES: To estimate the relationship between EQ5D (three levels, UK version) and the Ankylosing Spondylitis Disease Activity Score (ASDAS) for use in the economic evaluation of health technologies for people with axial spondyloarthritis (axSpA). To compare against the relationship with the Bath...

Descripción completa

Detalles Bibliográficos
Autores principales: Hernandez Alava, Monica, Wailoo, Allan, Chrysanthou, Georgios, Barcelos, Filipe, van Gaalen, Floris A, Santos, Helena, Fagerli, Karen Minde, Gago, Laura, Margarida Cunha, Maria, van de Sande, Marleen, Couto, Maura C, Bernardes, Miguel, Ramonda, Roberta, Exarchou, Sofia, Carvalho, Pedro D, van der Heijde, Desirée, Machado, Pedro M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860088/
https://www.ncbi.nlm.nih.gov/pubmed/35177554
http://dx.doi.org/10.1136/rmdopen-2021-001955
Descripción
Sumario:OBJECTIVES: To estimate the relationship between EQ5D (three levels, UK version) and the Ankylosing Spondylitis Disease Activity Score (ASDAS) for use in the economic evaluation of health technologies for people with axial spondyloarthritis (axSpA). To compare against the relationship with the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). METHODS: An electronic, prospective, Portuguese, nationwide, rheumatic disease register (Reuma.pt) provided data on 1140 patients (5483 observations) with a confirmed diagnosis of axSpA. We estimated models of EQ5D as a function of ASDAS, alone or in combination with measures of functional impairment, using bespoke mixture models which reflect the complex distributional features of EQ5D. The SPondyloArthritis Caught Early cohort provided data from 344 patients (1405 observations) in four European countries and was used for validation. A previously published model of BASDAI/Bath Ankylosing Spondylitis Functional Index (BASFI) was also used to generate predicted EQ5D scores and model performance compared. RESULTS: A non-linear relationship exists between EQ5D from ASDAS. The final model included ASDAS, ASDAS squared, age and age squared and demonstrated close fit in both datasets except where data were sparse for patients with very high levels of disease activity (ASDAS >4). This finding held in the validation dataset. Models that included BASFI improved model fit. The ASDAS based models fit the data marginally less well than models using BASDAI. CONCLUSIONS: Mapping models linking ASDAS to EQ5D allow results from clinical studies to be used in economic evaluation of health technologies with confidence. There is some loss of information compared with BASDAI but this has only a marginal impact.