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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 preference-adjusted 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, observa...

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Autores principales: Badia, X., Roset, M., Valassi, E., Franz, H., Forsythe, A., Webb, S. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3853865/
https://www.ncbi.nlm.nih.gov/pubmed/23539468
http://dx.doi.org/10.1007/s11136-013-0396-7
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author Badia, X.
Roset, M.
Valassi, E.
Franz, H.
Forsythe, A.
Webb, S. M.
author_facet Badia, X.
Roset, M.
Valassi, E.
Franz, H.
Forsythe, A.
Webb, S. M.
author_sort Badia, X.
collection PubMed
description PURPOSE: To construct a model to predict preference-adjusted 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 disease-specific 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 R(2) 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.
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spelling pubmed-38538652013-12-09 Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN) Badia, X. Roset, M. Valassi, E. Franz, H. Forsythe, A. Webb, S. M. Qual Life Res Article PURPOSE: To construct a model to predict preference-adjusted 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 disease-specific 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 R(2) 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. Springer Netherlands 2013-03-29 2013 /pmc/articles/PMC3853865/ /pubmed/23539468 http://dx.doi.org/10.1007/s11136-013-0396-7 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Badia, X.
Roset, M.
Valassi, E.
Franz, H.
Forsythe, A.
Webb, S. M.
Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title_full Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title_fullStr Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title_full_unstemmed Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title_short Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
title_sort mapping cushingqol scores to eq-5d utility values using data from the european registry on cushing’s syndrome (ercusyn)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3853865/
https://www.ncbi.nlm.nih.gov/pubmed/23539468
http://dx.doi.org/10.1007/s11136-013-0396-7
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