Literature DB >> 23337232

Mapping to obtain EQ-5D utility values for use in NICE health technology assessments.

Louise Longworth1, Donna Rowen.   

Abstract

Quality-adjusted life-years (QALYs) are widely used as an outcome for the economic evaluation of health interventions. However, preference-based measures used to obtain health-related utility values to produce QALY estimates are not always included in key clinical studies. Furthermore, organizations responsible for reviewing or producing health technology assessments (HTAs) may have preferred instruments for obtaining utility estimates for QALY calculations. Where data using a preference-based measure or the preferred instrument have not been collected, it may be possible to "map" or "crosswalk" from other measures of health outcomes. The aims of this study were 1) to provide an overview of how mapping is currently used as reported in the published literature and in an HTA policy-making context, specifically at the National Institute for Health and Clinical Excellence in the United Kingdom, and 2) to comment on best current practice on the use of mapping for HTA more generally. The review of the National Institute for Health and Clinical Excellence guidance found that mapping has been used since first established but that reporting of the models used to map has been poor. Recommendations for mapping in HTA include an explicit consideration of the generalizability of the mapping function to the target sample, reporting of standard econometric and statistical tests including the degree of error in the mapping model across subsets of the range of utility values, and validation of the model(s). Mapping can provide a route for linking outcomes data collected in a trial or observational study to the specific preferred instrument for obtaining utility values. In most cases, however, it is still advantageous to directly collect data by using the preferred utility-based instrument and mapping should usually be viewed as a "second-best" solution.
Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23337232     DOI: 10.1016/j.jval.2012.10.010

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  88 in total

1.  Constructing indirect utility models: some observations on the principles and practice of mapping to obtain health state utilities.

Authors:  Christopher McCabe; Richard Edlin; David Meads; Chantelle Brown; Samer Kharroubi
Journal:  Pharmacoeconomics       Date:  2013-08       Impact factor: 4.981

Review 2.  An educational review of the statistical issues in analysing utility data for cost-utility analysis.

Authors:  Rachael Maree Hunter; Gianluca Baio; Thomas Butt; Stephen Morris; Jeff Round; Nick Freemantle
Journal:  Pharmacoeconomics       Date:  2015-04       Impact factor: 4.981

3.  Mapping MacNew Heart Disease Quality of Life Questionnaire onto country-specific EQ-5D-5L utility scores: a comparison of traditional regression models with a machine learning technique.

Authors:  Lan Gao; Wei Luo; Utsana Tonmukayakul; Marj Moodie; Gang Chen
Journal:  Eur J Health Econ       Date:  2021-01-13

4.  Mapping clinical outcomes to generic preference-based outcome measures: development and comparison of methods.

Authors:  Mónica Hernández Alava; Allan Wailoo; Stephen Pudney; Laura Gray; Andrea Manca
Journal:  Health Technol Assess       Date:  2020-06       Impact factor: 4.014

5.  Converting Parkinson-Specific Scores into Health State Utilities to Assess Cost-Utility Analysis.

Authors:  Gang Chen; Miguel A Garcia-Gordillo; Daniel Collado-Mateo; Borja Del Pozo-Cruz; José C Adsuar; José Manuel Cordero-Ferrera; José María Abellán-Perpiñán; Fernando Ignacio Sánchez-Martínez
Journal:  Patient       Date:  2018-12       Impact factor: 3.883

6.  Mapping the Alzheimer's Disease Cooperative Study-Activities of Daily Living Inventory to the Health Utility Index Mark III.

Authors:  Yin Bun Cheung; Hui Xing Tan; Vivian Wei Wang; Nagaendran Kandiah; Nan Luo; Gerald C H Koh; Hwee Lin Wee
Journal:  Qual Life Res       Date:  2018-09-01       Impact factor: 4.147

7.  Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

Authors:  Christine Mpundu-Kaambwa; Gang Chen; Remo Russo; Katherine Stevens; Karin Dam Petersen; Julie Ratcliffe
Journal:  Pharmacoeconomics       Date:  2017-04       Impact factor: 4.981

8.  Should linking replace regression when mapping from profile-based measures to preference-based measures?

Authors:  Peter M Fayers; Ron D Hays
Journal:  Value Health       Date:  2014-03       Impact factor: 5.725

9.  Can Mapping Algorithms Based on Raw Scores Overestimate QALYs Gained by Treatment? A Comparison of Mappings Between the Roland-Morris Disability Questionnaire and the EQ-5D-3L Based on Raw and Differenced Score Data.

Authors:  Jason Madan; Kamran A Khan; Stavros Petrou; Sarah E Lamb
Journal:  Pharmacoeconomics       Date:  2017-05       Impact factor: 4.981

10.  Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

Authors:  Brett Doble; Paula Lorgelly
Journal:  Qual Life Res       Date:  2015-09-21       Impact factor: 4.147

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