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