Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN)
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| Title: | Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN) |
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| Authors: | Badia, X., Roset, M., Valassi, E., Franz, H., Forsythe, A., Webb, S. M. |
| Source: | Quality of Life Research. Dec2013, Vol. 22 Issue 10, p2941-2950. 10p. |
| Subjects: | Quality of life, Cushing's syndrome, Scientific observation, Patient satisfaction, Acquisition of data, Prediction models |
| Geographic Terms: | Europe |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 92719867 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN) – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Badia%2C+X%2E%22">Badia, X.</searchLink><br /><searchLink fieldCode="AR" term="%22Roset%2C+M%2E%22">Roset, M.</searchLink><br /><searchLink fieldCode="AR" term="%22Valassi%2C+E%2E%22">Valassi, E.</searchLink><br /><searchLink fieldCode="AR" term="%22Franz%2C+H%2E%22">Franz, H.</searchLink><br /><searchLink fieldCode="AR" term="%22Forsythe%2C+A%2E%22">Forsythe, A.</searchLink><br /><searchLink fieldCode="AR" term="%22Webb%2C+S%2E+M%2E%22">Webb, S. M.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Quality+of+Life+Research%22">Quality of Life Research</searchLink>. Dec2013, Vol. 22 Issue 10, p2941-2950. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22Cushing's+syndrome%22">Cushing's syndrome</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+observation%22">Scientific observation</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+satisfaction%22">Patient satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Europe%22">Europe</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11136-013-0396-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 2941 Subjects: – SubjectFull: Quality of life Type: general – SubjectFull: Cushing's syndrome Type: general – SubjectFull: Scientific observation Type: general – SubjectFull: Patient satisfaction Type: general – SubjectFull: Acquisition of data Type: general – SubjectFull: Prediction models Type: general – SubjectFull: Europe Type: general Titles: – TitleFull: Mapping CushingQOL scores to EQ-5D utility values using data from the European Registry on Cushing’s syndrome (ERCUSYN) Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Badia, X. – PersonEntity: Name: NameFull: Roset, M. – PersonEntity: Name: NameFull: Valassi, E. – PersonEntity: Name: NameFull: Franz, H. – PersonEntity: Name: NameFull: Forsythe, A. – PersonEntity: Name: NameFull: Webb, S. M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 09629343 Numbering: – Type: volume Value: 22 – Type: issue Value: 10 Titles: – TitleFull: Quality of Life Research Type: main |
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