Crosswalk methods

Introduction

Crosswalk methods allow EQ-5D values to be estimated when a country-specific value set exists for one instrument version but not another. eq5dsuite implements three widely used approaches:

Original crosswalk (eqxw) — maps EQ-5D-5L responses to EQ-5D-3L values (van Hout et al., 2012)
Reverse crosswalk (eqxwr) — maps EQ-5D-3L responses to EQ-5D-5L values (van Hout and Shaw, 2021)
NICE DSU mapping, 5L to 3L (eqxw_UK) — maps EQ-5D-5L responses to values on the UK EQ-5D-3L value set (Hernández Alava et al., 2023)
NICE DSU mapping, 3L to 5L (eqxwr_UK) — maps EQ-5D-3L responses to values on the UK EQ-5D-5L value set (Hernández Alava et al., 2023)

The two NICE DSU mappings are age- and sex-specific and cover the United Kingdom only. They are not the van Hout crosswalks: eqxwr() and eqxwr_UK() answer different questions and are not interchangeable.

When to use crosswalk methods

Use crosswalk methods when:

You have EQ-5D-5L data but only a 3L value set exists for your country → use eqxw()
You have EQ-5D-3L data but only a 5L value set exists → use eqxwr()
You are conducting a NICE technology appraisal and have only EQ-5D-3L data → use eqxwr_UK()

The current NICE position

NICE’s interim methods statement of 27 August 2026 (NICE, 2026; PMG51) takes the UK EQ-5D-5L value set (Rowen et al., 2026) as the reference case for topics started after that date – for technology appraisals, those whose invitation to participate was issued after it. Topics started earlier continue to map EQ-5D-5L data to EQ-5D-3L utility values (with eqxw_UK()). For new topics:

EQ-5D-5L data collected in the study should be valued directly, with eq5d5l(x, country = "GB"). No mapping is needed.
Only EQ-5D-3L data available → map with eqxwr_UK(), the mapping the statement specifies in that situation (Hernández Alava et al., 2023).
eqxw_UK() maps in the other direction, to the older UK EQ-5D-3L value set. It remains for topics started before 27 August 2026 and for reproducing earlier analyses.

Original crosswalk: eqxw()

eq5d5l_data <- data.frame(
  id = 1:5,
  mo = c(1, 2, 3, 1, 2),
  sc = c(1, 1, 2, 1, 3),
  ua = c(2, 1, 3, 1, 2),
  pd = c(2, 3, 2, 1, 4),
  ad = c(1, 2, 1, 3, 2)
)

# Apply crosswalk using UK 3L value set
eq5d5l_data$value_xw <- eqxw(
  eq5d5l_data,
  country   = "GB",
  dim.names = c("mo", "sc", "ua", "pd", "ad")
)

eq5d5l_data
#>   id mo sc ua pd ad  value_xw
#> 1  1  1  1  2  2  1 0.7947687
#> 2  2  2  1  1  3  2 0.6829058
#> 3  3  3  2  3  2  1 0.6288650
#> 4  4  1  1  1  1  3 0.8480001
#> 5  5  2  3  2  4  2 0.3374945

Reverse crosswalk: eqxwr()

eq5d3l_data <- data.frame(
  id = 1:5,
  mo = c(1, 2, 1, 3, 2),
  sc = c(1, 1, 2, 2, 1),
  ua = c(1, 2, 1, 3, 2),
  pd = c(2, 2, 1, 3, 3),
  ad = c(1, 1, 2, 2, 1)
)

# Apply reverse crosswalk using Spain 5L value set
eq5d3l_data$value_rxw <- eqxwr(
  eq5d3l_data,
  country   = "ES",
  dim.names = c("mo", "sc", "ua", "pd", "ad")
)

eq5d3l_data
#>   id mo sc ua pd ad   value_rxw
#> 1  1  1  1  1  2  1  0.90095476
#> 2  2  2  1  2  2  1  0.73260937
#> 3  3  1  2  1  1  2  0.81044151
#> 4  4  3  2  3  3  2 -0.04655332
#> 5  5  2  1  2  3  1  0.54478451

NICE DSU mapping, 5L to 3L: eqxw_UK()

Both NICE DSU mappings require age and sex in addition to the five EQ-5D dimensions. Age is used in years and grouped into five bands (16–34, 35–44, 45–54, 55–64, 65 and over); sex is 1 for male and 0 for female.

uk_data <- data.frame(
  id   = 1:5,
  mo   = c(1, 2, 1, 3, 2),
  sc   = c(1, 1, 2, 2, 1),
  ua   = c(1, 2, 1, 3, 2),
  pd   = c(2, 2, 1, 3, 3),
  ad   = c(1, 1, 2, 2, 1),
  age  = c(45, 62, 38, 71, 55),
  male = c(1,  0,  1,  0,  1)
)

uk_data$value_uk <- eqxw_UK(
  uk_data,
  age  = "age",
  male = "male"
)

uk_data
#>   id mo sc ua pd ad age male  value_uk
#> 1  1  1  1  1  2  1  45    1 0.8637525
#> 2  2  2  1  2  2  1  62    0 0.7420881
#> 3  3  1  2  1  1  2  38    1 0.8471943
#> 4  4  3  2  3  3  2  71    0 0.5306411
#> 5  5  2  1  2  3  1  55    1 0.6685958

NICE DSU mapping, 3L to 5L: eqxwr_UK()

When only EQ-5D-3L data are available, eqxwr_UK() maps them so they can be valued on the UK EQ-5D-5L value set:

uk3l <- data.frame(
  id   = 1:5,
  mo   = c(1, 2, 1, 3, 2),
  sc   = c(1, 1, 2, 2, 1),
  ua   = c(1, 2, 1, 3, 2),
  pd   = c(2, 2, 1, 3, 3),
  ad   = c(1, 1, 2, 2, 1),
  age  = c(45, 62, 38, 71, 55),
  male = c(1,  0,  1,  0,  1)
)

uk3l$value_uk5l <- eqxwr_UK(uk3l, age = "age", male = "male")

uk3l
#>   id mo sc ua pd ad age male  value_uk5l
#> 1  1  1  1  1  2  1  45    1  0.92506034
#> 2  2  2  1  2  2  1  62    0  0.79902655
#> 3  3  1  2  1  1  2  38    1  0.86239329
#> 4  4  3  2  3  3  2  71    0 -0.08121815
#> 5  5  2  1  2  3  1  55    1  0.56006048

Mapping a mean value

Both functions also accept an EQ-5D value instead of a health state, for mapping a mean reported in a published study. There is no unique health state behind a mean, so the result is a kernel-weighted average of the mapped values of nearby states. bwidth = "default" applies the DSU’s recommended bandwidths for mean values: 0.1 for values above 0.6, and 0.4 for values at or below 0.6.

# a mean EQ-5D-3L value of 0.54 in women aged 35
eqxwr_UK(0.54, age = 35, male = 0, bwidth = "default")
#> [1] 0.7005354

# the bandwidth matters: a narrower one weights fewer states
eqxwr_UK(0.54, age = 35, male = 0, bwidth = 0.1)
#> [1] 0.746695

This input is not intended for individual-level data. Map individual respondents from their health states, as above.

Crosswalk compatibility with custom value sets

All crosswalk functions are compatible with custom value sets added via eqvs_add(). The mapping and valuation steps are independent, so any compatible value set can be used without modification.

References

van Hout B, et al. (2012). Interim scoring for the EQ-5D-5L. Value in Health, 15(5), 708–715.

van Hout B, Shaw JW (2021). Mapping EQ-5D-3L to EQ-5D-5L. Value in Health, 24(9), 1285–1293.

Hernández Alava M, Pudney S, Wailoo A (2023). Estimating the relationship between EQ-5D-5L and EQ-5D-3L: results from a UK population study. PharmacoEconomics, 41(2), 199–207.

Rowen D, Mukuria C, Bray N, et al. (2026). A UK value set for the EQ-5D-5L. Value in Health, 29(5), 858–869.

National Institute for Health and Care Excellence (2026). Interim methods statement: implementing the EQ-5D-5L value set (PMG51). Published 27 August 2026. https://www.nice.org.uk/process/pmg51