Journals Library

An error occurred retrieving content to display, please try again.

Page not found (404)

Sorry - the page you requested could not be found.

Please choose a page from the navigation or try a website search above to find the information you need.

{{metadata.Title}}

{{metadata.Headline}}

{{author}}{{author}}{{($index < metadata.AuthorsAndEtalArray.length-1) ? ',' : '.'}}

Louise Longworth 1,*, Yaling Yang 1, Tracey Young 2, Brendan Mulhern 2, Mónica Hernández Alava 2, Clara Mukuria 2, Donna Rowen 2, Jonathan Tosh 2, Aki Tsuchiya 2, Pippa Evans 2, Anju Devianee Keetharuth 2, John Brazier 2

1 Health Economics Research Group, Brunel University, Uxbridge, Middlesex, UK
2 School of Health and Related Research, University of Sheffield, Sheffield, UK
* Corresponding author Email:

{{metadata.Journal}} Volume: {{metadata.Volume}}, Issue:{{metadata.Issue}}, Published in {{metadata.PublicationDate | date:'MMMM yyyy'}}

https://doi.org/{{metadata.DOI}}

Citation: {{author}}{{ (($index < metadata.AuthorsArray.length-1) && ($index <=6)) ? ', ' : '' }}{{(metadata.AuthorsArray.length <= 6) ? '.' : '' }} {{(metadata.AuthorsArray.length > 6) ? 'et al.' : ''}} {{metadata.Title}}. {{metadata.JournalShortName}} {{metadata.PublicationDate | date:'yyyy'}};{{metadata.Volume}}({{metadata.Issue}})

You might also be interested in:
{{classification.Category.Concept}}

Report Content

The full text of this issue is available as a PDF document from the Toolkit section on this page.

The full text of this issue is available as a PDF document from the Toolkit section on this page.

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: EQâ + hearing/vision/tiredness. A full valuation study was conducted for the EQâ +â 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.

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: EQâ + hearing/vision/tiredness. A full valuation study was conducted for the EQâ +â 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.

If you would like to receive a notification when this project publishes in the NIHR Journals Library, please submit your email address below.

 

Responses to this report

 

No responses have been published.

If you would like to submit a response to this publication, please do so using the form below.

Comments submitted to the NIHR Journals Library are electronic letters to the editor. They enable our readers to debate issues raised in research reports published in the Journals Library. We aim to post within 2 working days all responses that contribute substantially to the topic investigated, as determined by the Editors.

Your name and affiliations will be published with your comment.

Once published, you will not have the right to remove or edit your response. The Editors may add, remove, or edit comments at their absolute discretion.

By submitting your response, you are stating that you agree to the terms & conditions