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Gepubliceerd in: Quality of Life Research 6/2020

03-02-2020

Modelling a preference-based index for EQ-5D-3L and EQ-5D-3L + Sleep using a Bayesian framework

Auteurs: Samer A. Kharroubi, Yara S. Beyh, John Brazier, Yaling Yang

Gepubliceerd in: Quality of Life Research | Uitgave 6/2020

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Abstract

Background

Conventionally, frequentist approach has been used to model health state valuation data. Recently, researchers started to explore the use of Bayesian methods in this area.

Objectives

This paper presents an alternative approach to modelling health state valuation data of the EQ-5D-3L and EQ-5D-3L + Sleep descriptive systems, using a Bayesian framework, and demonstrates its superiority to conventional frequentist methods.

Methods

The valuation study is composed of 18 EQ-5D-3L health states and 18 EQ-5D-3L + Sleep health states valued by 160 members of the general public in South Yorkshire, UK, using the time tradeo-ff technique. Three different models were developed for EQ-5D-3L and EQ-5D-3L + Sleep accordingly using Bayesian Markov chain Monte Carlo simulation methods. Bayesian methods were applied to models fitted included a linear regression, random effect and random effect with covariates. The models are compared based on their predictive performance using mean predictions, root mean squared error (RMSE) and deviance information criterion (DIC). All analyses were performed using Bayesian Markov chain Monte Carlo simulation methods.

Results

The random effects with covariates model performs best under all criterions for the two preference-based measures, with RMSE (0.037) and DIC (637.5) for EQ-5D-3L and RMSE (0.019), DIC (416.4) for EQ-5D + Sleep. Compared with models previously estimated using frequentist approach, the Bayesian models reported in this paper provided better predictions of observed values.

Conclusion

Bayesian methods provide a better way to model EQ-5D-3L valuation data with and without a sleep ‘bolt-on’ and provide a more flexible in characterizing the full range of uncertainty inherent in these estimates.
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Literatuur
1.
go back to reference Brazier, J., Ratcliffe, J., Salomon, J. A., & Tsuchyia, A. (2017). Measuring and valuing health benefits for economic evaluation (2nd ed.). Oxford: Oxford University Press. Brazier, J., Ratcliffe, J., Salomon, J. A., & Tsuchyia, A. (2017). Measuring and valuing health benefits for economic evaluation (2nd ed.). Oxford: Oxford University Press.
2.
go back to reference Brooks, R., & Group, E. (1996). EuroQol: The current state of play. Health Policy,37, 53–72. Brooks, R., & Group, E. (1996). EuroQol: The current state of play. Health Policy,37, 53–72.
3.
go back to reference Herdman, M., Gudex, C., Lloyd, A., Janssen, M. F., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research,20(10), 1727–1736.PubMedPubMedCentral Herdman, M., Gudex, C., Lloyd, A., Janssen, M. F., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research,20(10), 1727–1736.PubMedPubMedCentral
4.
go back to reference Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system: Health Utilities Index Mark 2. Medical Care,34, 702–722.PubMed Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system: Health Utilities Index Mark 2. Medical Care,34, 702–722.PubMed
5.
go back to reference Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Medical care,40, 113–128.PubMed Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Medical care,40, 113–128.PubMed
6.
go back to reference Hawthorne, G., Richardson, J., & Day, N. A. (2001). A comparison of the Assessment of Quality of Life (AQoL) with four other generic utility instruments. Annals of medicine,33, 358–370.PubMed Hawthorne, G., Richardson, J., & Day, N. A. (2001). A comparison of the Assessment of Quality of Life (AQoL) with four other generic utility instruments. Annals of medicine,33, 358–370.PubMed
7.
go back to reference Kaplan, R. M., & Anderson, J. P. (1988). A general health policy model: Update and application. Health Services Research,23, 203–235.PubMedPubMedCentral Kaplan, R. M., & Anderson, J. P. (1988). A general health policy model: Update and application. Health Services Research,23, 203–235.PubMedPubMedCentral
8.
go back to reference Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics,21, 271–292.PubMed Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics,21, 271–292.PubMed
9.
go back to reference Revicki, D. A., Leidy, N. K., Brennan-Diemer, F., Sorensen, S., & Togias, A. (1998). Integrating patient preferences into health outcomes assessment: The multiattribute Asthma Symptom Utility Index. Chest,114, 998–1007.PubMed Revicki, D. A., Leidy, N. K., Brennan-Diemer, F., Sorensen, S., & Togias, A. (1998). Integrating patient preferences into health outcomes assessment: The multiattribute Asthma Symptom Utility Index. Chest,114, 998–1007.PubMed
10.
go back to reference Rowen, D., Brazier, J., Ara, R., & Zouraq, I. A. (2017). The role of condition-specific preference-based measures in health technology assessment. PharmacoEconomics,35, 33–41.PubMed Rowen, D., Brazier, J., Ara, R., & Zouraq, I. A. (2017). The role of condition-specific preference-based measures in health technology assessment. PharmacoEconomics,35, 33–41.PubMed
11.
go back to reference Rencz, F., Gulacsi, L., Drummond, M., et al. (2016). EQ-5D in Central and Eastern Europe: 2000–2015. Quality of Life Research,25(11), 2693–2710.PubMed Rencz, F., Gulacsi, L., Drummond, M., et al. (2016). EQ-5D in Central and Eastern Europe: 2000–2015. Quality of Life Research,25(11), 2693–2710.PubMed
12.
go back to reference Rowen, D., Azzabi Zouraq, I., Chevrou-Severac, H., & van Hout, B. (2017). International regulations and recommendations for utility data for health technology assessment. Pharmacoeconomics,35, 11–19.PubMed Rowen, D., Azzabi Zouraq, I., Chevrou-Severac, H., & van Hout, B. (2017). International regulations and recommendations for utility data for health technology assessment. Pharmacoeconomics,35, 11–19.PubMed
13.
go back to reference Xie, F., Gaebel, K., Perampaladas, K., Doble, B., & Pullenayegum, E. (2014). Comparing EQ-5D valuation studies: A systematic review and methodological reporting checklist. Medical Decision Making,34, 8–20.PubMed Xie, F., Gaebel, K., Perampaladas, K., Doble, B., & Pullenayegum, E. (2014). Comparing EQ-5D valuation studies: A systematic review and methodological reporting checklist. Medical Decision Making,34, 8–20.PubMed
14.
go back to reference Brooks, R., Coons, S. J., De Cock, P., et al. (2003). EQ-5D in selected countries around the world. In R. Brooks, R. Rabin, & F. Charro (Eds.), The measurement and valuation of health status using EQ-SD: A European perspective (pp. 207–227). Dordrecht: Kluwer Academic Publishers. Brooks, R., Coons, S. J., De Cock, P., et al. (2003). EQ-5D in selected countries around the world. In R. Brooks, R. Rabin, & F. Charro (Eds.), The measurement and valuation of health status using EQ-SD: A European perspective (pp. 207–227). Dordrecht: Kluwer Academic Publishers.
15.
go back to reference Liu, G. G., Wu, H., Li, M., Gao, C., & Luo, N. (2014). Chinese time trade-off values for EQ-5D health states. Value Health,17, 597–604.PubMed Liu, G. G., Wu, H., Li, M., Gao, C., & Luo, N. (2014). Chinese time trade-off values for EQ-5D health states. Value Health,17, 597–604.PubMed
16.
go back to reference Viney, R., Norman, R., King, M. K., Cronin, P., Street, D. J., Knox, S., et al. (2011). Time Trade-Off Derived EQ-5D Weights for Australia. Value in Health,14(6), 928–936.PubMed Viney, R., Norman, R., King, M. K., Cronin, P., Street, D. J., Knox, S., et al. (2011). Time Trade-Off Derived EQ-5D Weights for Australia. Value in Health,14(6), 928–936.PubMed
17.
go back to reference Dolan, P. (1997). Modeling valuation for Euroqol health states. Medical Care,35(11), 1095–1108. Dolan, P. (1997). Modeling valuation for Euroqol health states. Medical Care,35(11), 1095–1108.
18.
go back to reference McCabe, C., Stevens, K., Roberts, J., & Brazier, J. E. (2005). Health state values for the HUI2 descriptive system: Results from a UK Survey. Health Economics,14, 231–244.PubMed McCabe, C., Stevens, K., Roberts, J., & Brazier, J. E. (2005). Health state values for the HUI2 descriptive system: Results from a UK Survey. Health Economics,14, 231–244.PubMed
19.
go back to reference Kharroubi, S. A., O'Hagan, A., & Brazier, J. E. (2005). Estimating Utilities from individual health state preference data: A nonparametric Bayesian approach. Applied Statistics,54, 879–895. Kharroubi, S. A., O'Hagan, A., & Brazier, J. E. (2005). Estimating Utilities from individual health state preference data: A nonparametric Bayesian approach. Applied Statistics,54, 879–895.
20.
go back to reference Kharroubi, S. A., Brazier, J., O'Hagan, A., & Roberts, J. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics,26, 597–612.PubMed Kharroubi, S. A., Brazier, J., O'Hagan, A., & Roberts, J. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics,26, 597–612.PubMed
21.
go back to reference Kharroubi, S. A., Brazier, J., & McGhee, S. (2013). Modelling SF-6D Hong Kong standard gamble health state preference data using a nonparametric Bayesian method. Value in Health,16(6), 1032–1045.PubMed Kharroubi, S. A., Brazier, J., & McGhee, S. (2013). Modelling SF-6D Hong Kong standard gamble health state preference data using a nonparametric Bayesian method. Value in Health,16(6), 1032–1045.PubMed
22.
go back to reference Kharroubi, S. A., & Abou Daher, C. (2018). Modelling a preference-based index for EQ-5D using a nonparametric Bayesian method. Quality of Life Research,27(11), 2841–2850.PubMed Kharroubi, S. A., & Abou Daher, C. (2018). Modelling a preference-based index for EQ-5D using a nonparametric Bayesian method. Quality of Life Research,27(11), 2841–2850.PubMed
23.
go back to reference Kharroubi, S. A., O’Hagan, A., & Brazier, J. E. (2010). A comparison of United States and United Kingdom EQ-5D health state valuations using a non-parametric Bayesian method. Statistics in Medicine,29, 1622–1634.PubMed Kharroubi, S. A., O’Hagan, A., & Brazier, J. E. (2010). A comparison of United States and United Kingdom EQ-5D health state valuations using a non-parametric Bayesian method. Statistics in Medicine,29, 1622–1634.PubMed
24.
go back to reference Kharroubi, S. A., Brazier, J., & McGhee, S. (2014). A comparison of Hong Kong and United Kingdom SF-6D health states valuations using a nonparametric Bayesian method. Value Health,17(4), 397–405.PubMed Kharroubi, S. A., Brazier, J., & McGhee, S. (2014). A comparison of Hong Kong and United Kingdom SF-6D health states valuations using a nonparametric Bayesian method. Value Health,17(4), 397–405.PubMed
25.
go back to reference Kharroubi, S. A. (2015). A comparison of Japan and United Kingdom SF-6D health states valuations using a nonparametric Bayesian method. Applied Health Economics and Health Policy,13(4), 409–420.PubMed Kharroubi, S. A. (2015). A comparison of Japan and United Kingdom SF-6D health states valuations using a nonparametric Bayesian method. Applied Health Economics and Health Policy,13(4), 409–420.PubMed
26.
go back to reference Chan, K. K. W., Xie, F., Willan, A. R., & Pullenayegum, E. (2017). Underestimation of variance of predicted health utilities derived from multiattribute utility instruments: The use of multiple imputation as a potential solution. Medical Decision Making,37(3), 262–272.PubMed Chan, K. K. W., Xie, F., Willan, A. R., & Pullenayegum, E. (2017). Underestimation of variance of predicted health utilities derived from multiattribute utility instruments: The use of multiple imputation as a potential solution. Medical Decision Making,37(3), 262–272.PubMed
27.
go back to reference Pullenayegum, E. M., Chan, K. K., & Xie, F. (2016). Quantifying parameter uncertainty in EQ-5D-3L value sets and its impact on studies that use the EQ-5D-3L to measure health utility: A Bayesian approach. Medical Decision Making,36(2), 223–233.PubMed Pullenayegum, E. M., Chan, K. K., & Xie, F. (2016). Quantifying parameter uncertainty in EQ-5D-3L value sets and its impact on studies that use the EQ-5D-3L to measure health utility: A Bayesian approach. Medical Decision Making,36(2), 223–233.PubMed
28.
go back to reference Shams, S., & Pullenayegum, E. M. (2019). Reducing uncertainty in EQ-5D value sets: The role of spatial correlation. Medical Decision Making,39(2), 91–99.PubMed Shams, S., & Pullenayegum, E. M. (2019). Reducing uncertainty in EQ-5D value sets: The role of spatial correlation. Medical Decision Making,39(2), 91–99.PubMed
29.
go back to reference Yang, Y., Brazier, J., & Tsuchiya, A. (2014). Effect of adding a sleep dimension to the EQ-5D descriptive system: A “bolt-on” experiment. Medical Decision Making,34(1), 42–53.PubMed Yang, Y., Brazier, J., & Tsuchiya, A. (2014). Effect of adding a sleep dimension to the EQ-5D descriptive system: A “bolt-on” experiment. Medical Decision Making,34(1), 42–53.PubMed
30.
go back to reference Group, T. E. (1990). EuroQol-a new facility for the measurement of health-related quality of life. Health Policy,16(3), 199–208. Group, T. E. (1990). EuroQol-a new facility for the measurement of health-related quality of life. Health Policy,16(3), 199–208.
31.
go back to reference Patrick, D. L., Starks, H. E., Cain, K. C., Uhlmann, R. F., & Pearlman, R. A. (1994). Measuring preferences for health states worse than death. Medical Decision Making,14(1), 9–18.PubMed Patrick, D. L., Starks, H. E., Cain, K. C., Uhlmann, R. F., & Pearlman, R. A. (1994). Measuring preferences for health states worse than death. Medical Decision Making,14(1), 9–18.PubMed
32.
go back to reference Gudex, C. (1994). Time trade-off user manual: Props and self-completion methods Working Papers 020cheop. New York: Centre for Health Economics, University of York. Gudex, C. (1994). Time trade-off user manual: Props and self-completion methods Working Papers 020cheop. New York: Centre for Health Economics, University of York.
33.
go back to reference Gilks, W. R., Richardson, S., & Spiegelhalter, D. (1995). Markov chain Monte Carlo in practice. Boca Raton: Chapman and Hall/CRC. Gilks, W. R., Richardson, S., & Spiegelhalter, D. (1995). Markov chain Monte Carlo in practice. Boca Raton: Chapman and Hall/CRC.
34.
go back to reference Spiegelhatler, D. J., Thomas, A., Best, N. G., & Lunn, D. (2003). WinBUGS User manual: Version 1.4. Cambridge: MRC Biostatistics Unit. Spiegelhatler, D. J., Thomas, A., Best, N. G., & Lunn, D. (2003). WinBUGS User manual: Version 1.4. Cambridge: MRC Biostatistics Unit.
35.
go back to reference Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Sciences,7, 457–472. Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Sciences,7, 457–472.
36.
go back to reference Natarajan, R., & Kass, R. E. (2000). Reference Bayesian methods for generalized linear mixed models. Journal of the American Statistical Association,95(449), 227–237. Natarajan, R., & Kass, R. E. (2000). Reference Bayesian methods for generalized linear mixed models. Journal of the American Statistical Association,95(449), 227–237.
37.
go back to reference Kharroubi, S. A., Meads, D., Edlin, R., Browne, C., & McCabe, C. (2015). Use of Bayesian Markov Chain Monte Carlo methods to estimate EQ-5D utility scores from EORTC QLQ data in Myeloma. Medical Decision Making,35(3), 351–360.PubMed Kharroubi, S. A., Meads, D., Edlin, R., Browne, C., & McCabe, C. (2015). Use of Bayesian Markov Chain Monte Carlo methods to estimate EQ-5D utility scores from EORTC QLQ data in Myeloma. Medical Decision Making,35(3), 351–360.PubMed
Metagegevens
Titel
Modelling a preference-based index for EQ-5D-3L and EQ-5D-3L + Sleep using a Bayesian framework
Auteurs
Samer A. Kharroubi
Yara S. Beyh
John Brazier
Yaling Yang
Publicatiedatum
03-02-2020
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 6/2020
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-020-02436-2

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