Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic review, statistical modelling and survey

Longworth, L; Yang, Y; Young, T; Mulhern, B; Hernández Alava, M; Mukuria, C; Rowen, D; Tosh, J; Tsuchiya, A; Evans, P; Devianee Keetharuth, A; Brazier, J

Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic review, statistical modelling and survey

Longworth, L Yang, Y Young, T Mulhern, B

Hernández Alava, M Mukuria, C Rowen, D Tosh, J Tsuchiya, A Evans, P Devianee Keetharuth, A Brazier, J

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Publication Type:: Journal Article
Citation:: Health Technology Assessment, 2014, 18 (9), pp. 1 - 224
Issue Date:: 2014-02-01

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Field	Value	Language
dc.contributor.author	Longworth, L	en_US
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Young, T	en_US
dc.contributor.author	Mulhern, B https://orcid.org/0000-0003-3656-8063	en_US
dc.contributor.author	Hernández Alava, M	en_US
dc.contributor.author	Mukuria, C	en_US
dc.contributor.author	Rowen, D	en_US
dc.contributor.author	Tosh, J	en_US
dc.contributor.author	Tsuchiya, A	en_US
dc.contributor.author	Evans, P	en_US
dc.contributor.author	Devianee Keetharuth, A	en_US
dc.contributor.author	Brazier, J	en_US
dc.date.issued	2014-02-01	en_US
dc.identifier.citation	Health Technology Assessment, 2014, 18 (9), pp. 1 - 224	en_US
dc.identifier.issn	1366-5278	en_US
dc.identifier.uri	http://hdl.handle.net/10453/115721
dc.description.abstract	Background: The National Institute for Health and Care Excellence recommends the use of generic preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However, these data may not be available or appropriate for all health conditions. Objectives: To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate. Design: The project was conducted in three stages: (1) A systematic review of the psychometric properties of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential modelling approaches to 'map' EQ-5D values from condition-specific and clinical measures of health [European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Functional Assessment of Cancer Therapy - General Scale (FACT-G)] are compared for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the EQ-5D are developed as 'bolt-on' items relating to hearing, tiredness and vision. They are valued using the time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without the vision bolt-on item in an additional sample of 300 people. Setting: The valuation surveys were conducted using face-to-face interviews in the respondents' homes. Participants: Two representative samples of the UK general population from Yorkshire (n = 600). Interventions: None. Main outcome measures: Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30 and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness. A full valuation study was conducted for the EQ + vision. Results: (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3 performed well for hearing and vision disorders. It also performed well in cancers although evidence was limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a limited dependent variable mixture model performed better than an equivalent linear model. In the full analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and tiredness had a significant impact on values of the health states, but the direction and magnitude of differences depended on the severity of the health state. The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated. Conclusions: EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons provide a promising solution. More primary research into the psychometric properties of the generic preference-based measures is required, particularly in cancer and for the assessment of reliability. Further research is needed for the development and valuation of bolt-ons to EQ-5D. Funding: This project was funded by the UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486) and will be published in full in Health Technology Assessment; Vol. 18, No. 9. See the NIHR Journals Library website for further project information. © Queen's Printer and Controller of HMSO 2014.	en_US
dc.relation.ispartof	Health Technology Assessment	en_US
dc.relation.isbasedon	10.3310/hta18090	en_US
dc.subject.classification	Health Policy & Services	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Neoplasms	en_US
dc.subject.mesh	Hearing Disorders	en_US
dc.subject.mesh	Vision Disorders	en_US
dc.subject.mesh	Skin Diseases	en_US
dc.subject.mesh	Models, Statistical	en_US
dc.subject.mesh	Quality-Adjusted Life Years	en_US
dc.subject.mesh	Quality of Health Care	en_US
dc.subject.mesh	Quality Indicators, Health Care	en_US
dc.title	Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic review, statistical modelling and survey	en_US
dc.type	Journal Article
utslib.citation.volume	9	en_US
utslib.citation.volume	18	en_US
utslib.for	1117 Public Health and Health Services	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0807 Library and Information Studies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
utslib.copyright.status	open_access
pubs.issue	9	en_US
pubs.publication-status	Published	en_US
pubs.volume	18	en_US

Abstract:

Background: The National Institute for Health and Care Excellence recommends the use of generic preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However, these data may not be available or appropriate for all health conditions. Objectives: To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate. Design: The project was conducted in three stages: (1) A systematic review of the psychometric properties of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential modelling approaches to 'map' EQ-5D values from condition-specific and clinical measures of health [European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Functional Assessment of Cancer Therapy - General Scale (FACT-G)] are compared for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the EQ-5D are developed as 'bolt-on' items relating to hearing, tiredness and vision. They are valued using the time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without the vision bolt-on item in an additional sample of 300 people. Setting: The valuation surveys were conducted using face-to-face interviews in the respondents' homes. Participants: Two representative samples of the UK general population from Yorkshire (n = 600). Interventions: None. Main outcome measures: Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30 and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness. A full valuation study was conducted for the EQ + vision. Results: (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3 performed well for hearing and vision disorders. It also performed well in cancers although evidence was limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a limited dependent variable mixture model performed better than an equivalent linear model. In the full analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and tiredness had a significant impact on values of the health states, but the direction and magnitude of differences depended on the severity of the health state. The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated. Conclusions: EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons provide a promising solution. More primary research into the psychometric properties of the generic preference-based measures is required, particularly in cancer and for the assessment of reliability. Further research is needed for the development and valuation of bolt-ons to EQ-5D. Funding: This project was funded by the UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486) and will be published in full in Health Technology Assessment; Vol. 18, No. 9. See the NIHR Journals Library website for further project information. © Queen's Printer and Controller of HMSO 2014.

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