Literature DB >> 29943377

Development of Conversion Functions Mapping the FACT-B Total Score to the EQ-5D-5L Utility Value by Three Linking Methods and Comparison with the Ordinary Least Square Method.

Chun Fan Lee1, Raymond Ng2, Nan Luo3, Yin Bun Cheung4,5,6.   

Abstract

INTRODUCTION: Health-related quality-of-life (HRQoL) measures are commonly mapped to a value that represents a utility for economic evaluation via regression models, which may lead to shrinkage of the variance.
OBJECTIVES: This study aimed to develop and compare conversion functions that map the Functional Assessment of Cancer Therapy-Breast (FACT-B) total score to the EuroQoL 5-Dimensions, 5-Levels (EQ-5D-5L) utility value via four methods.
METHODS: We used the HRQoL scores of 238 Singapore patients with breast cancer to develop the conversion function for the equipercentile, linear equating, mean rank and ordinary least squares (OLS) methods. We compared the distributions of the observed values and the four sets of mapped values and performed regression analyses to assess whether the association with risk factors was preserved by utility values derived from mapping.
RESULTS: At baseline, the observed EQ-5D-5L utility value had a mean ± standard deviation (SD) of 0.820 ± 0.152, and 24.8% of the respondents attained a value of 1. The OLS method (mean 0.820; SD 0.112; proportion 0%) better agreed with the observed data than the equipercentile (mean 0.831; SD 0.152; proportion 23.5%), linear equating (mean 0.814; SD 0.145; proportion 11.8%) and mean rank method (mean 0.821; SD 0.147; proportion 23.9%). The significance of association was preserved for all parameters involved in the regression analyses by the equipercentile and linear equating methods, but the mean rank and OLS methods were inconsistent with the observed data for one and two parameters, respectively.
CONCLUSION: The problem of shrinkage in the variance occurred in the OLS method, but it provided an unbiased estimate for the mean and better agreement. Among the other three linking methods, the mean rank method better described the distribution, whereas the equipercentile and linear equating methods better assessed the association with risk factors.

Entities:  

Mesh:

Year:  2018        PMID: 29943377     DOI: 10.1007/s40258-018-0404-8

Source DB:  PubMed          Journal:  Appl Health Econ Health Policy        ISSN: 1175-5652            Impact factor:   2.561


  9 in total

1.  Mapping the cancer-specific FACT-B onto the generic SF-6Dv2.

Authors:  Azin Nahvijou; Hossein Safari; Mahmood Yousefi; Marziyeh Rajabi; Morteza Arab-Zozani; Hosein Ameri
Journal:  Breast Cancer       Date:  2020-07-25       Impact factor: 4.239

2.  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

3.  Mapping the Shah-modified Barthel Index to the Health Utility Index Mark III by the Mean Rank Method.

Authors:  Yin Bun Cheung; Hui Xing Tan; Nan Luo; Hwee Lin Wee; Gerald C H Koh
Journal:  Qual Life Res       Date:  2019-07-27       Impact factor: 4.147

4.  CORR Insights®: Mapping and Crosswalk of the Oxford Hip Score and Different Versions of the Hip Disability and Osteoarthritis Outcome Score.

Authors:  Takashi Nishii
Journal:  Clin Orthop Relat Res       Date:  2021-07-01       Impact factor: 4.755

5.  Mapping the medical outcomes study HIV health survey (MOS-HIV) to the EuroQoL 5 Dimension (EQ-5D-3 L) utility index.

Authors:  Yuan Shi; Jennifer Thompson; A Sarah Walker; Nicholas I Paton; Yin Bun Cheung
Journal:  Health Qual Life Outcomes       Date:  2019-05-10       Impact factor: 3.186

6.  Mapping function from FACT-B to EQ-5D-5 L using multiple modelling approaches: data from breast cancer patients in China.

Authors:  Qing Yang; Xue Xin Yu; Wei Zhang; Hui Li
Journal:  Health Qual Life Outcomes       Date:  2019-10-15       Impact factor: 3.186

7.  Health variations among breast-cancer patients from different disease states: evidence from China.

Authors:  Qing Yang; Xuexin Yu; Wei Zhang
Journal:  BMC Health Serv Res       Date:  2020-11-11       Impact factor: 2.655

8.  Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer.

Authors:  Laura A Gray; Monica Hernandez Alava; Allan J Wailoo
Journal:  BMC Cancer       Date:  2021-11-18       Impact factor: 4.430

9.  Mapping and Crosswalk of the Oxford Hip Score and Different Versions of the Hip Disability and Osteoarthritis Outcome Score.

Authors:  Sophie Putman; Cristian Preda; Julien Girard; Alain Duhamel; Henri Migaud
Journal:  Clin Orthop Relat Res       Date:  2021-07-01       Impact factor: 4.755

  9 in total

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