Literature DB >> 27090196

Crosswalk algorithms for the conversion of mean EQ-5D indices calculated with different value sets.

Szilárd Nemes1, Göran Garellick2, Roger Salomonsson3, Ola Rolfson2.   

Abstract

AIMS: The EQ-5D questionnaire of EuroQol is an important tool, not only for researchers, but also for quality registers. Until 2013, Sweden did not have a country-specific value set to convert the EQ-5D health states into a single index. Commonly, the UK time trade-off (UK TTO) value set has been used. The study reported here aimed to establish an easy to use tool for the bidirectional crosswalk of the mean EQ-5D values based on two different value sets: the UK TTO and the Swedish TTO value sets.
METHODS: Using an artificial data set encompassing all possible EQ-5D outcomes, we calculated the EQ-5D index using both the UK TTO and Swedish TTO value sets. Thereafter we modelled the relationship between the two indices using least-squares regression and major axis regression. A series of simulations was run to assess the feasibility of the obtained crosswalk algorithms.
RESULTS: Major axis regression was superior to ordinary least-squares regression. Converting the mean EQ-5D values from the UK TTO scale to the Swedish TTO scale was more accurate than the inverse conversion. Values close to the floor and ceiling of the EQ-5D index were more challenging to crosswalk. CONCLUSIONS WE ESTABLISHED ALGORITHMS BASED ON MAJOR AXIS REGRESSION TO CROSSWALK EQ-5D VALUES BASED ON THE UK TTO AND THE SWEDISH TTO VALUE SETS THE PRESENTED ALGORITHM MAY FACILITATE COMPARISONS OF EQ-5D VALUES WHEN ONLY MEAN VALUES ARE AVAILABLE THE EXISTENCE OF A CROSSWALK ALGORITHM WILL EASE THE TRANSITION FROM THE UK TTO TO THE SWEDISH TTO VALUE SET.
© 2016 the Nordic Societies of Public Health.

Keywords:  EQ-5D index; Swedish time-trade-off; UK time-trade-off; crosswalk; major axis regression

Mesh:

Year:  2016        PMID: 27090196     DOI: 10.1177/1403494816642886

Source DB:  PubMed          Journal:  Scand J Public Health        ISSN: 1403-4948            Impact factor:   3.021


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