Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12888-021-03463-0
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dc.titleMapping the PHQ-8 to EQ-5D, HUI3 and SF6D in patients with depression
dc.contributor.authorAbdin, Edimansyah
dc.contributor.authorChong, Siow Ann
dc.contributor.authorSeow, Esmond
dc.contributor.authorTan, Kelvin Bryan
dc.contributor.authorSubramaniam, Mythily
dc.date.accessioned2022-10-13T01:06:08Z
dc.date.available2022-10-13T01:06:08Z
dc.date.issued2021-09-13
dc.identifier.citationAbdin, Edimansyah, Chong, Siow Ann, Seow, Esmond, Tan, Kelvin Bryan, Subramaniam, Mythily (2021-09-13). Mapping the PHQ-8 to EQ-5D, HUI3 and SF6D in patients with depression. BMC Psychiatry 21 (1) : 451. ScholarBank@NUS Repository. https://doi.org/10.1186/s12888-021-03463-0
dc.identifier.issn1471-244X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/232715
dc.description.abstractBackground: There is limited evidence of mapping clinical instruments to a generic preference-based instrument in Asian patient populations. The current study aims to map the eight-item Patient Health Questionnaire depression scale (PHQ-8) onto the EuroQol Five-Dimension (EQ-5D), the Health Utilities Index Mark 3 (HUI3) and the Short Form Six-Dimension (SF-6D) which helps to inform future cost-utility analyses of treatments for depression. Methods: A total of 249 participants who had completed PHQ-8, EQ-5D, SF-6D and HUI3 questionnaires were included in the analyses. A beta regression mixture model was used to map the utility scores as a function of PHQ-8 total scores, PHQ-squared, age and gender. The predictive accuracy of the models was examined using mean absolute error and root mean square error. Results: The results were compared against two common regression methods including Ordinary Least Square (OLS) and Tobit regression models. The mean age of the sample was 36.2 years (SD = 11.1). The mean EQ-5D-3L, EQ-5D-5L, HUI3 and SF-6D utility scores were 0.615, 0.709, 0.461 and 0.607, respectively. The EQ-5D-3L, EQ-5D-5L and SF-6D utility scores were best predicted by the beta mixture regression model consisting of PHQ-8 total sores, PHQ-squared, and covariates including age and gender. The HUI3 was best predicted by the OLS regression model. Conclusions: The current study provides important evidence to clinicians and researchers about the mapping algorithms that can be used in economic evaluation among patients with depression. © 2021, The Author(s).
dc.publisherBioMed Central Ltd
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2021
dc.typeArticle
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.doi10.1186/s12888-021-03463-0
dc.description.sourcetitleBMC Psychiatry
dc.description.volume21
dc.description.issue1
dc.description.page451
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