Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing's syndrome (ERCUSYN)
Purpose To construct a model to predict preferenceadjusted EuroQol 5D (EQ-5D) health utilities for CS using the disease-specific health-related quality of life measure (CushingQOL). Methods Data were obtained from the European Registry on CS (ERCUSYN). ERCUSYN is a web-based, multicenter, observatio...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:303539 |
| Acceso en línea: | https://ddd.uab.cat/record/303539 https://dx.doi.org/urn:doi:10.1007/s11136-013-0396-7 |
| Access Level: | acceso abierto |
| Palabra clave: | Cushing's syndrome EQ-5D Mapping Quality of life Questionnaire |
| Sumario: | Purpose To construct a model to predict preferenceadjusted EuroQol 5D (EQ-5D) health utilities for CS using the disease-specific health-related quality of life measure (CushingQOL). Methods Data were obtained from the European Registry on CS (ERCUSYN). ERCUSYN is a web-based, multicenter, observational study that enrolled 508 CS patients from 36 centers in 23 European countries. Patients included in the study completed both the EQ-5D and the diseasespecific CushingQOL questionnaire. Socio-demographic and clinical data were also collected. The UK tariff values were used to calculate EQ-5D utility scores. Various predictive models were tested, and the final model was selected based on four criteria: explanatory power (adjusted R-squared), consistency of estimated coefficients (sign and parameter estimation), normality of prediction errors (mean error, mean absolute error, root mean squared error), and parsimony. Results For the mapping analysis, data were available from a total of 129 patients. Mean (SD) age was 43.1 (13) years, and the sample was predominantly female (84.5 %). Patients had a mean (SD) CushingQOL score of 39.7 (17.1) and a mean (SD) 'tariff' value on the EQ-5D of 0.55 (0.3). The model which best met the criteria for selection included the intercept and 3 CushingQOL's questions and had an R2 of 0.506 and a root mean square error of 0.216. Conclusions It was possible to find a mapping function which successfully predicted the EQ-5D UK utilities from disease-specific CushingQOL scores. The function may be useful in calculating EQ-5D scores when EQ-5D data have not been gathered directly in a study. © The Author(s) 2013. This article is published with open access at Springerlink.com. |
|---|