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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.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.
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.sourceScopus OA2021
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.sourcetitleBMC Psychiatry
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