Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV

Vilija R. Joyce; Huiying Sun; Paul G. Barnett; Nick Bansback; Susan C. Griffin; Ahmed M. Bayoumi; Aslam H. Anis; Mark Sculpher; William Cameron; Sheldon T. Brown; Mark Holodniy; Douglas K. Owens

doi:10.1177/2381468317716440

Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV

Vilija R. Joyce, Huiying Sun, Paul G. Barnett, Nick Bansback, Susan C. Griffin, Ahmed M. Bayoumi, Aslam H. Anis, Mark Sculpher, William Cameron, Sheldon T. Brown, Mark Holodniy, Douglas K. Owens

Centre for Health Economics

Research output: Contribution to journal › Article › peer-review

Abstract

Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (

Original language	English
Number of pages	13
Journal	MDM Policy Practice
Volume	2
Issue number	2
DOIs	https://doi.org/10.1177/2381468317716440
Publication status	Published - 3 Jul 2017

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10.1177/2381468317716440

2381468317716440
© The Author(s), 2017.
Final published version, 277 KBLicence: CC BY-NC

http://dx.doi.org/10.1177/2381468317716440

Cite this

@article{5bf8e3cae12940a19b84fb973c9c1792,

title = "Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV",

abstract = "Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (",

author = "Joyce, {Vilija R.} and Huiying Sun and Barnett, {Paul G.} and Nick Bansback and Griffin, {Susan C.} and Bayoumi, {Ahmed M.} and Anis, {Aslam H.} and Mark Sculpher and William Cameron and Brown, {Sheldon T.} and Mark Holodniy and Owens, {Douglas K.}",

note = " {\textcopyright} The Author(s), 2017.",

year = "2017",

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doi = "10.1177/2381468317716440",

language = "English",

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T1 - Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV

AU - Joyce, Vilija R.

AU - Sun, Huiying

AU - Barnett, Paul G.

AU - Bansback, Nick

AU - Griffin, Susan C.

AU - Bayoumi, Ahmed M.

AU - Anis, Aslam H.

AU - Sculpher, Mark

AU - Cameron, William

AU - Brown, Sheldon T.

AU - Holodniy, Mark

AU - Owens, Douglas K.

PY - 2017/7/3

Y1 - 2017/7/3

N2 - Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (

AB - Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (

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