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dc.contributor.authorLamu, Admassu Nadew
dc.contributor.authorChen, Gang
dc.contributor.authorGamst-Klaussen, Thor
dc.contributor.authorOlsen, Jan Abel
dc.date.accessioned2018-08-06T06:52:05Z
dc.date.available2018-08-06T06:52:05Z
dc.date.issued2018-03-22
dc.description.abstract<p><i>Purpose</i>: To develop mapping algorithms that transform Diabetes-39 (D-39) scores onto EQ-5D-5L utility values for each of eight recently published country-specific EQ-5D-5L value sets, and to compare mapping functions across the EQ-5D-5L value sets.</p> <p><i>Methods</i>: Data include 924 individuals with self-reported diabetes from six countries. The D-39 dimensions, age and gender were used as potential predictors for EQ-5D-5L utilities, which were scored using value sets from eight countries (England, Netherland, Spain, Canada, Uruguay, China, Japan and Korea). Ordinary least squares, generalised linear model, beta binomial regression, fractional regression, MM estimation and censored least absolute deviation were used to estimate the mapping algorithms. The optimal algorithm for each country-specific value set was primarily selected based on normalised root mean square error (NRMSE), normalised mean absolute error (NMAE) and adjusted-r2. Cross-validation with fivefold approach was conducted to test the generalizability of each model.</p> <p><i>Results</i>: The fractional regression model with loglog as a link function consistently performed best in all country-specific value sets. For instance, the NRMSE (0.1282) and NMAE (0.0914) were the lowest, while adjusted-r2 was the highest (52.5%) when the English value set was considered. Among D-39 dimensions, the energy and mobility was the only one that was consistently significant for all models.</p> <p><i>Conclusions</i>: The D-39 can be mapped onto the EQ-5D-5L utilities with good predictive accuracy. The fractional regression model, which is appropriate for handling bounded outcomes, outperformed other candidate methods in all country-specific value sets. However, the regression coefficients differed reflecting preference heterogeneity across countries.en_US
dc.descriptionThis is a pre-print of an article published in Quality of Life Research. The final authenticated version is available online at: <a href=https://doi.org/10.1007/s11136-018-1840-5> https://doi.org/10.1007/s11136-018-1840-5</a>.en_US
dc.identifier.citationLamu, A.N., Chen, G., Gamst-Klaussen, T. & Olsen, J.A. (2018). Do country-specific preference-weights matter in the choice of mapping algorithms? The case of mapping the Diabetes-39 onto eight country-specific EQ-5D-5L value sets. Quality of Life Research, 27, 1801-1814.en_US
dc.identifier.cristinIDFRIDAID 1585355
dc.identifier.doihttps://doi.org/10.1007/s11136-018-1840-5
dc.identifier.issn0962-9343
dc.identifier.issn1573-2649
dc.identifier.urihttps://hdl.handle.net/10037/13353
dc.language.isoengen_US
dc.publisherSpringer Verlag (Germany)en_US
dc.relation.journalQuality of Life Research
dc.relation.urihttps://link.springer.com/article/10.1007/s11136-018-1840-5#citeas
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Medisinske Fag: 700::Helsefag: 800en_US
dc.subjectVDP::Medical disciplines: 700::Health sciences: 800en_US
dc.subjectMappingen_US
dc.subjectDiabetes-39en_US
dc.subjectEQ-5D-5Len_US
dc.subjectHRQoLen_US
dc.subjectUtilityen_US
dc.subjectQALYen_US
dc.titleDo country-specific preference weights matter in the choice of mapping algorithms? The case of mapping the Diabetes-39 onto eight country-specific EQ-5D-5L value setsen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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