Methodological similarities and variations among EQ-5D-5L value set studies: a systematic review

Figures & data

Figure 1. PRISMA flow diagram of study selection process. Abbreviations. cTTO, Composite Time Trade-Off; DCE, Discrete Choice Experiment; PAPRIKA, Potentially All Pairwise RanKings of all possible Alternatives; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; tTTO, Traditional Time Trade-Off; VAS, Visual Analog Scale.

Table 1. Evidence table summarizing the methodological elements of EQ-5D-5L for the retained studies (n = 31).

Country	Publication year	General study characteristics						Preference elicitation technique and modeling						Value set
		Sample		Data collection				TTO			DCE
		Sampling	Analyzed^a	Training	Mode	Protocol version	QC^b	Design	C/R	Model^c	Design	C/R	Model^c	Final model
EQ-VT Version 2
Uganda^26	2022	Q	492	Y	CAPI	EQ-VT Lite	Y	cTTO	20	Tobit	—	—	—	Tobit
Denmark^37	2021	—	1,014	Y	CAPI	EQ-VT 2.1	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
Egypt^28	2021	Q	974	Y	CAPI	EQ-VT 2.1	Y	cTTO	10	Heteroskedastic	DCE	7	CLM	Heteroskedastic
Mexico^27	2021	St	1,000	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Heteroskedastic	—	—	—	Heteroskedastic
France^9	2020	Q	1,048	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
Hungary^48	2020	Q	1,000	—	CAPI	EQ-VT 2.1	Y	cTTO	10	Tobit	DCE	7	—	Tobit
Peru^29	2020	St	1,000	Y	CAPI	EQ-VT 2.1	Y	cTTO	11	Tobit	DCE	34	ZBT	Tobit
Vietnam^43	2020	St	1,200	Y	CAPI	EQ-VT 2.1	Y	cTTO	10	Tobit	DCE	7	LM	Hybrid
Ethiopia^51	2019	St	1,048	Y	CAPI	EQ-PVT 2.1	Y	cTTO	10	OLS	DCE	7	CLM	Hybrid
Poland^35	2019	Q	1,252	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	—	DCE	7	—	Hybrid
Portugal^34	2019	St	1,451	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
US^45	2019	Q	1,102	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	MLM	Tobit
Germany^41	2018	Q	1,158	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	13	CLM	Hybrid
Ireland^36	2018	St	1,160	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	—	DCE	7	—	Hybrid
Malaysia^49	2018	St	1,125	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Mixed effect	DCE	7	CLM	Hybrid
Taiwan^40	2018	St	1,000	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
Hong Kong^52	2017	—	1,014	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
Indonesia^46	2017	St	1,054	Y	CAPI	EQ-VT 2.0	Y	cTTO	10	Tobit	DCE	7	CLM	Hybrid
EQ-VT Version 1
Spain^47	2018	St	973	Y	CAPI	EQ-VT 1.0	Re	cTTO	10	Linear	DCE	7	CLM	Hybrid
Thailand^44	2018	St	1,205	Y	CAPI	EQ-VT 1.1	Y	cTTO	10	Multilevel	DCE	7	CLM	Hybrid
China^42	2017	Q	1,271	Y	CAPI	EQ-VT 1.0	—	cTTO	10	Nonlinear	DCE	—	—	Non-linear
England^33	2017	R	912	Y	CAPI	EQ-VT 1.0	Re	cTTO	10	—	DCE	7	—	Hybrid
Canada^53	2016	Q	1,073	–	CAPI	EQ-VT 1.0	—	cTTO + tTTO	10	Linear	—	—	—	Linear
Japan^15	2016	St	1,026	Y	CAPI	EQ-VT 1.1	Y	cTTO	10	Linear mixed	DCE	7	CLM	Linear mixed
Korea^38	2016	St	1,080	Y	CAPI	EQ-VT 1.1	Y	cTTO	10	Linear mixed	DCE	7	CLM	Linear mixed
Netherlands^16	2016	St	992	Y	CAPI	EQ-VT 1.0	Re	cTTO	10	Tobit	DCE	7	CLM	Tobit
Uruguay^30	2016	St	794	Y	CAPI	EQ-VT 1.1	Y	cTTO	10	Robust	DCE	7	—	Robust
Others
New Zealand^50	2020	Re	2,468	—	SAOS	—	Y	—	—	—	DCE ( PAPRIKA)	—	—	—
Sweden^31^d	2020	R	25,867	—	SAPS	—	—	TTO	1	OLS	—	—	—	OLS
US^32	2018	Q	8,222	—	SAOS	—	—	—	—	—	DCE	20	ZBT	ZBT
Germany^39^d	2017	R	8,114	—	SAPS	N	—	—	—	—	—	—	—	GLM

Abbreviations. –, not used/unspecified/unclear; CAPI, face-to-face computer-assisted personal interviewing; CLM, conditional logit model; C/R represents choice/respondent; cTTO, composite time trade-off; DCE, discrete choice experiment; EB, experience based; EQ-PVT, EuroQol portable valuation technology; EQ-VT, EuroQol valuation technology; GLM, generalized linear model; HS, hypothetical state; LM, logit model; MLM, mixed logit model; OLS, ordinary least square; Q, quota sampling; QC, quality control; R, random sampling; Re, market research companies; Rp, representative; SAOS, self-administered online survey; SAPS, self-administered paper/postal survey; St, stratified sampling; tTTO, traditional time trade-off; VAS, visual analog scale; Y, yes; ZBT, zermelo-bradley-terry.

^aThe sample represents the final sample size analyzed.

^bQC represents the use of quality control procedure recommended by the EuroQol.

^cModel indicates the final model used to analyze the TTO/DCE data.

^dVisual analog scale (VAS) was used to derived value set based on own health experience.

Table 2. Summary characteristics of the value sets based on utility score (n = 31).

Country	Utility score^a				Dimension scores^b					Relative importance^c
	Mean	SD	Min	Max	MO	SC	UA	PD	AD
Asia
China^42	0.310	0.236	–0.391	1.000	0.345	0.253	0.233	0.302	0.258	MO > PD > AD > SC > UA
Hong Kong^52	0.113	0.314	–0.865	1.000	0.529	0.352	0.282	0.354	0.348	MO > PD > SC > AD > UA
Indonesia^46	0.112	0.314	–0.865	1.000	0.613	0.316	0.385	0.246	0.305	MO > UA > SC > AD > PD
Japan^15	0.449	0.155	–0.025	1.000	0.304	0.221	0.236	0.252	0.257	MO > AD > PD > UA > SC
Korea^38	0.451	0.159	–0.066	1.000	0.425	0.296	0.349	0.381	0.311	MO > PD > UA > AD > SC
Malaysia^49	0.331	0.239	–0.442	1.000	0.340	0.261	0.202	0.338	0.300	MO > PD > AD > SC > UA
Taiwan^40	0.036	0.338	–1.026	1.000	0.477	0.324	0.351	0.453	0.421	MO > PD > AD > UA > SC
Thailand^44	0.379	0.234	–0.421	1.000	0.371	0.250	0.248	0.256	0.295	MO > AD > PD > SC > UA
Vietnam^43	0.353	0.246	–0.512	1.000	0.376	0.231	0.299	0.367	0.239	MO > PD > UA > AD > SC
Europe
Denmark^37	0.267	0.338	–0.758	1.000	0.220	0.209	0.174	0.537	0.618	AD > PD > MO > SC > UA
England^33	0.383	0.226	–0.285	1.000	0.274	0.203	0.184	0.335	0.289	PD > AD > MO > SC > UA
France^9	0.424	0.269	–0.525	1.000	0.325	0.258	0.240	0.444	0.258	PD > MO > SC > AD > UA
Germany^41	0.343	0.308	–0.661	1.000	0.224	0.260	0.209	0.612	0.356	PD > AD > SC > MO > UA
Germany^39^d	0.448	0.149	0.104	0.920	0.143	0.190	0.208	0.361	0.214	PD > AD > UA > SC > MO
Hungary^48	0.251	0.318	–0.848	1.000	0.455	0.366	0.276	0.411	0.340	MO > PD > SC > AD > UA
Ireland^36	0.131	0.367	–0.974	1.000	0.344	0.287	0.187	0.510	0.646	AD > PD > MO > SC > UA
Netherlands^16	0.287	0.268	–0.446	0.953	0.203	0.168	0.192	0.415	0.421	AD > PD > MO > UA > SC
Poland^35	0.476	0.286	–0.590	1.000	0.314	0.264	0.205	0.575	0.232	PD > MO > SC > AD > UA
Portugal^34	0.366	0.263	–0.603	1.000	0.356	0.294	0.263	0.406	0.284	PD > MO > SC > AD > UA
Spain^47	0.351	0.241	–0.415	1.000	0.337	0.196	0.153	0.381	0.348	PD > AD > MO > SC > UA
Sweden^31^d	0.605	0.140	0.243	0.976	0.055	0.085	0.166	0.200	0.236	AD > PD > UA > SC > MO
America
Canada^53	0.399	0.202	–0.148	0.949	0.207	0.242	0.188	0.319	0.278	PD > AD > SC > MO > UA
Mexico^27	0.374	0.264	–0.596	1.000	0.270	0.259	0.276	0.458	0.334	PD > AD > UA > MO > SC
New Zealand^50^d	0.198	0.292	–0.83	1.000	0.350	0.370	0.340	0.381	0.389	AD > PD > SC > MO > UA
Peru^29	0.047	0.321	–1.073	1.000	0.473	0.355	0.347	0.476	0.422	PD > MO > AD > SC > UA
Uruguay^30	0.540	0.209	–0.264	1.000	0.311	0.286	0.244	0.283	0.190	MO > SC > PD > UA > AD
US^45	0.235	0.272	–0.573	1.000	0.322	0.261	0.255	0.414	0.321	PD > MO > AD > SC > UA
US^32^d	0.501	0.238	–0.287	1.000	0.250	0.262	0.211	0.324	0.240	PD > SC > MO > AD > UA
Africa
Egypt^28	0.151	0.359	–0.978	1.000	0.602	0.285	0.213	0.443	0.419	MO > PD > AD > SC > UA
Ethiopia^51	0.349	0.303	–0.718	1.000	0.360	0.222	0.272	0.406	0.458	AD > PD > MO > UA > SC
Uganda^26	0.081	0.395	–1.116	1.000	0.376	0.354	0.306	0.798	0.282	PD > MO > SC > UA > AD

Abbreviations. AD, Anxiety/Depression; MO, Mobility; PD, Pain/Discomfort; SC, Self-Care; UA, Usual Activities.

^aMean and standard deviation of utility score are for the 3,125 health states. Min = minimum utility value, Max = Maximum utility value.

^bDimension scores were calculated as the magnitude of relative utility decrements for a dimension. For example, in the case of Thailand, the dimension score for AD was estimated as the difference between the utility for full health (11111) = 1 subtracted by the utility level for the fifth level of AD (11115) = 0.7047 (i.e. 1 ‒ 0.7047 = 0.295).

^cRelative importance was estimated from the ordering of the magnitude of the dimension scores. For example, in the case of Thailand, MO (0.371) > AD (0.295) > PD (0.256) > SC (0.250) > UA (0.248).

^dUtility scores were derived from the experience-based value set.

Table 3. Results for meta-regression analysis (n = 17).

Variable	Sampling technique (stratified)^b		Sample size (1,000 or more)^b		Protocol version (EQ-VT 2)^b		QC procedure (Yes)^b		Final model (hybrid)^b
	Estimates	p-value	Estimates	p-value	Estimates	p-value	Estimates	p-value	Estimates	p-value
Mean utility^a	0.079	0.141	–0.084	0.168	–0.099	0.067*	–0.006	0.928	–0.013	0.819
MO2	–0.006	0.656	0.011	0.521	0.005	0.759	–0.001	0.952	0.012	0.397
MO3	–0.033	0.218	–0.006	0.844	0.014	0.650	–0.007	0.855	–0.020	0.479
MO4	–0.050	0.203	–0.002	0.968	0.030	0.491	–0.003	0.952	–0.027	0.513
MO5	–0.043	0.410	0.001	0.991	0.063	0.273	0.083	0.220	–0.021	0.701
SC2	–0.002	0.820	0.008	0.436	0.005	0.602	0.004	0.682	0.002	0.813
SC3	–0.012	0.297	–0.001	0.949	–0.004	0.757	–0.015	0.349	–0.021	0.063*
SC4	–0.023	0.322	0.014	0.612	0.019	0.460	0.004	0.886	–0.018	0.432
SC5	–0.017	0.469	0.042	0.131	0.046	0.067*	0.065	0.027**	–0.004	0.860
UA2	0.008	0.149	0.000	0.959	–0.005	0.474	0.000	0.964	–0.002	0.715
UA3	–0.001	0.950	0.005	0.737	–0.008	0.486	–0.019	0.171	–0.029	0.004**
UA4	–0.027	0.241	–0.010	0.706	0.011	0.678	–0.013	0.670	–0.048	0.026**
UA5	0.014	0.477	0.036	0.119	0.018	0.406	0.034	0.191	–0.014	0.485
PD2	0.007	0.418	0.008	0.467	0.003	0.739	–0.007	0.564	0.010	0.255
PD3	–0.004	0.772	0.015	0.412	0.011	0.495	–0.011	0.581	0.006	0.680
PD4	–0.040	0.189	0.018	0.631	0.045	0.179	–0.010	0.819	0.027	0.396
PD5	–0.065	0.203	0.062	0.305	0.137	0.008**	0.074	0.269	0.042	0.420
AD2	0.005	0.625	0.000	0.994	–0.001	0.962	–0.013	0.384	0.010	0.353
AD3	–0.010	0.675	–0.010	0.742	0.016	0.552	–0.011	0.744	0.000	0.995
AD4	–0.024	0.666	–0.010	0.883	0.034	0.576	–0.027	0.714	0.027	0.640
AD5	–0.016	0.805	0.027	0.721	0.081	0.234	0.028	0.740	0.037	0.561

Significance level:** 0.05, * 0.1.

Abbreviations. AD2, slight problems for the dimension Anxiety/Depression; AD3, moderate problems for the dimension Anxiety/Depression; AD4, severe problems for the dimension Anxiety/Depression; AD5, Unable/extreme problems for the dimension Anxiety/Depression; MO2, slight problems for the dimension Mobility; MO3, moderate problems for the dimension Mobility; MO4, severe problems for the dimension Mobility; MO5, Unable/extreme problems for the dimension Mobility; PD2, slight problems for the dimension Pain/Discomfort; PD3, moderate problems for the dimension Pain/Discomfort; PD4, severe problems for the dimension Pain/Discomfort; PD5, Unable/extreme problems for the dimension Pain/Discomfort; SC2, slight problems for the dimension Self-Care; SC3, moderate problems for the dimension Self-Care; SC4, severe problems for the dimension Self-Care; SC5, Unable/extreme problems for the dimension Self-Care; UA2, slight problems for the dimension Usual Activities; UA3, moderate problems for the dimension Usual Activities; UA4, severe problems for the dimension Usual Activities; UA5, Unable/extreme problems for the dimension Usual Activities.

^aUtility value for each of the 3,125 health states was derived from the scoring algorithm of each country. The mean and standard error of the utility value was then constructed.

^bReference for the variable included in the meta-regression analysis consists of: Sampling Technique (Other); Sample Size (less than 1,000); Protocol Version (EQ-VT 1); QC procedure (No); Final Model (Others).

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Data availability statement

All data generated or analyzed during this study are included in this published article.