Literature DB >> 25840901

Mapping between 6 Multiattribute Utility Instruments.

Gang Chen1, Munir A Khan2, Angelo Iezzi2, Julie Ratcliffe1, Jeff Richardson2.   

Abstract

BACKGROUND: Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. AIM: This article presents mapping functions ("crosswalks") from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions.
METHODS: Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator.
RESULTS: Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means.
CONCLUSION: Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments.
© The Author(s) 2015.

Entities:  

Keywords:  cost-effectiveness analysis; cost-utility analysis; health-related quality of life; mapping; utility

Mesh:

Year:  2015        PMID: 25840901     DOI: 10.1177/0272989X15578127

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  18 in total

1.  Health state utility instruments compared: inquiring into nonlinearity across EQ-5D-5L, SF-6D, HUI-3 and 15D.

Authors:  Thor Gamst-Klaussen; Gang Chen; Admassu N Lamu; Jan Abel Olsen
Journal:  Qual Life Res       Date:  2015-12-21       Impact factor: 4.147

2.  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

3.  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

4.  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

5.  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

6.  Chronic Conditions and Utility-Based Health-Related Quality of Life in Adult Childhood Cancer Survivors.

Authors:  Jennifer M Yeh; Janel Hanmer; Zachary J Ward; Wendy M Leisenring; Gregory T Armstrong; Melissa M Hudson; Marilyn Stovall; Leslie L Robison; Kevin C Oeffinger; Lisa Diller
Journal:  J Natl Cancer Inst       Date:  2016-04-21       Impact factor: 13.506

7.  Deriving population norms for the AQoL-6D and AQoL-8D multi-attribute utility instruments from web-based data.

Authors:  Aimee Maxwell; Mehmet Özmen; Angelo Iezzi; Jeff Richardson
Journal:  Qual Life Res       Date:  2016-06-25       Impact factor: 4.147

8.  Mapping the Chinese Version of the EORTC QLQ-BR53 Onto the EQ-5D-5L and SF-6D Utility Scores.

Authors:  Tong Liu; Shunping Li; Min Wang; Qiang Sun; Gang Chen
Journal:  Patient       Date:  2020-10       Impact factor: 3.883

9.  Does one size fit all? Assessing the preferences of older and younger people for attributes of quality of life.

Authors:  Julie Ratcliffe; Emily Lancsar; Thomas Flint; Billingsley Kaambwa; Ruth Walker; Gill Lewin; Mary Luszcz; Ian D Cameron
Journal:  Qual Life Res       Date:  2016-08-23       Impact factor: 4.147

10.  Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index-9 Dimension (CHU-9D) Score for Economic Evaluation in Children.

Authors:  Tosin Lambe; Emma Frew; Natalie J Ives; Rebecca L Woolley; Carole Cummins; Elizabeth A Brettell; Emma N Barsoum; Nicholas J A Webb
Journal:  Pharmacoeconomics       Date:  2018-04       Impact factor: 4.981

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