Feng Xie Department of Clinical Epidemiology and Biostatistics McMaster University
Feng Xie
Department of Clinical Epidemiology and Biostatistics
McMaster University
Acknowledgements
Coauthors: Eleanor Pullenayegum, Simon Pickard, Juan Manuel Ramos Goni, Min-Woo Jo, Ataru Igarashi
We thank Drs. Ben Van Hout, Elly Stolk, Nan Luo, Juntana Pattanaphesaj, Juan Manuel Ramos Goñi, Min-Woo Jo, and Ataru Igarashi for sharing their data
This project was sponsored by a fast-track research grant from the EuroQol Research Foundation (#2013180)
Drs. Feng Xie is funded by the Canadian Institutes for Health Research New Investigator Award (MSH #122801). Dr. Feng Xie is also supported by McMaster University and St. Joseph’s Healthcare Hamilton.
None of the sponsors had any involvement in the design and conduct of the study, collection, analysis, and interpretation of the data, preparation, review and approval of the work.
EQ-5D-5L Valuation Study
An international initiative by the EuroQol
Group
Standardized protocol – EuroQol
Valuation Technology (EQ-VT)
Canada, Spain, UK, the Netherlands,
Japan, Thailand, Korea, and China
More countries…
Discrete choice experiment (DCE)
DCE vs TTO
Full health Dead State 1 State 2
1.0 0.0
health
utility
DCE
latent
utility
Cognitive challenge
Online vs face-to-face interview
Health utilities from TTO vs latent
utilities from DCE
The motivation
Feasibility issues in conducting
interviews with a national representative
sample in geographically-spread
countries or those with resource
constraint
DCE could be a practical alternative if
an existing transforming function can be
used
Hypothesis and objective
The relationship between different
methods in eliciting health preference
may be similar across countries given
the same underlying construct being
elicited
To compare generic functions with
country-specific functions in
transforming latent utilities to health
utilities
The data sets
Valuation study data from the 8 countries
TTO –derived health utilities for 86 health
states
196 state pairs using DCE
Each participant was asked to value 10 health
states using TTO and 7 pairs of states using
DCE
Transforming L to U
1 • Conditional logit model to derive latent utilities using DCE data
2 • Calculating mean TTO-derived health utility for each of 86 states
3 • fractional polynomial models to transform L to U (e.g. E(U|L)=β0 + β1L
a)
4
• Calculating mean absolute error (MAE) between predicted and observed health utility for each state without including the data from that state in modeling
Criteria for MAEs
The standard deviations (SDs) of the
MAEs from 18 EQ-5D (3 level) TTO-
based valuation studies
≤1 SD (0.02): acceptable;
1 SD<~<2 SDs (0.02 to 0.04): applied
with caution
≥2 SDs (0.04): unacceptable.
Study and respondent characteristics
Canada U.K. Spain Netherlands China Thailand Korea Japan
No of
respondents*
1209 1221 1000 983 1299 1216 1080 1026
No of interviewers 11 60 33 19 21 6 27 31
Use of commercial
survey company
N Y Y N N N Y Y
Age, years,
mean±SD
47.5± 17.4 51.0 ± 17.9 43.8 ±
17.3
47.2 ± 16.8 42.3 ±
16.2
43.5 ±
15.1
45.0 ±
14.3
44.9 ±
14.9
Female, n(%) 667
(55.0%)
710
(58,2%)
525
(52.5%)
507
(51.6%)
649
(50.0%)
630
(51.8%)
548
(50.7%)
511
(49.8%)
EQ-VAS, mean±SD 82.3 ±
14.2
78.6 ±
19.0
82.3 ±
14.5
80.5 ± 14.8 86.0 ±
11.4
83.1 ±
11.9
83.0 ±
10.0
84.9 ±
11.2
Country-specific functions
Regional functions
Global function
The findings
The differences were larger in the four
eastern countries than those in the four
western countries
A global generic transforming function
was associated with large increase in
prediction errors
A generic function for western countries
may work
Discussion
DCE could be used as the sole technique in western countries where using TTO is not feasible
Provincial value set could be derived using the national transforming function applied to provincial DCE data
Trade-off between prediction precision for health state utilities and amount of research resources to spend must be made