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Comparison of the EQ-5D-3L and the SF-6D (SF-12) contemporaneous utility scores in patients with cardiovascular disease

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Abstract

Purpose

Multi-attribute utility instruments (MAUIs) are widely used to measure utility weights. This study sought to compare utility weights of two popular MAUIs, the EQ-5D-3L and the SF-6D, and inform researchers in the selection of generic MAUI for use with cardiovascular (CVD) patients.

Methods

Data were collected in the Young@Heart study, a randomised controlled trial of a nurse-led multidisciplinary home-based intervention compared to standard usual care. Participants (n = 598) completed the EQ-5D-3L and the SF-12v2, from which the SF-6D can be constructed, at baseline and at 24-month follow-up. This study examined discrimination, responsiveness, correlation and differences across the two instruments.

Results

Both MAUIs were able to discriminate between the NYHA severity classes and recorded similar changes between the two time points although only SF-6D differences were significant. Correlations between the dimensions of the two MAUIs were low. There were significant differences between the two instruments in mild conditions but they were similar in severe conditions. Substantial ceiling and floor effects were observed.

Conclusions

Our findings indicate that the EQ-5D and the SF-6D cover different spaces in health due to their classification systems. Both measures were capable of discriminating between severity groups and responsive to quality of life changes in the follow-up. It is recommended to use the EQ-5D-3L in severe and the SF-6D in mild CVD conditions.

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References

  1. National Institute for Health and Care Excellence (NICE). (2008). Guide to the methods of technology appraisal. London: NICE.

    Google Scholar 

  2. Euro Qol group. EQ5D: EuroQol; 2011 Retrieved from: http://www.euroqol.org/eq-5d/reference-search/reference-search.html.

  3. 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(2), 271–292.

    Article  PubMed  Google Scholar 

  4. 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(2), 113–128.

    Article  PubMed  Google Scholar 

  5. AQoL. Assessment of Quality of life 2011 Retrieved from: http://www.aqol.com.au/research-papers.html.

  6. Pharmaceutical Benefits Advisory Committee. Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee 2015 [Appendix 7.2]. Retrieved from: https://pbac.pbs.gov.au/content/information/printable-files/pbacg-book.pdf.

  7. Konerding, U., Moock, J., & Kohlmann, T. (2009). The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common? Quality of Life Research, 18(9), 1249–1261.

    Article  PubMed  Google Scholar 

  8. McDonough, C. M., & Tosteson, A. N. (2007). Measuring preferences for cost-utility analysis: How choice of method may influence decision-making. Pharmacoeconomics, 25(2), 93–106.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Rabin, R., & de Charro, F. (2001). EQ-5D: A measure of health status from the EuroQol Group. Annals of Medicine, 33(5), 337–343.

    Article  CAS  PubMed  Google Scholar 

  10. Kularatna, S., Whitty, J. A., Johnson, N. W., Jayasinghe, R., & Scuffham, P. A. (2014). Valuing EQ-5D health states for Sri Lanka. Quality of Life Research, 24, 1785–1793.

    Article  PubMed  Google Scholar 

  11. Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108.

    Article  CAS  PubMed  Google Scholar 

  12. Shaw, J., Johnson, J., & Coons, S. (2005). US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Medical Care, 43(3), 203–220.

    Article  PubMed  Google Scholar 

  13. Ramos-Goñi, J. M., Pinto-Prades, J. L., Oppe, M., Cabasés, J. M., Serrano-Aguilar, P., & Rivero-Arias, O. (2017). Valuation and modeling of EQ-5D-5L health states using a hybrid approach. Medical Care, 55(7), e51–e58.

    Article  PubMed  Google Scholar 

  14. Brazier, J. E., & Roberts, J. (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care, 42(9), 851–859.

    Article  PubMed  Google Scholar 

  15. Australian Institute of Health and Welfare. Impact of cardiovascular disease. (2015). Retrieved from: http://www.aihw.gov.au/cardiovascular-health/impact/.

  16. Centers for Disease Control and Prevention Heart Disease. (2015). Retrieved from: http://www.cdc.gov/heartdisease/facts.htm.

  17. European Heart Network. European cardiovascular disease statistics 2012 2015. Retrieved from: http://www.ehnheart.org/cvd-statistics.html.

  18. British Heart Foundation. Heart statistics 2015 Retrieved from: https://www.bhf.org.uk/research/heart-statistics.

  19. Rowen, D., Young, T., Brazier, J., & Gaugris, S. (2012). Comparison of generic, condition-specific, and mapped health state utility values for multiple myeloma cancer. Value in Health, 15(8), 1059–1068.

    Article  PubMed  Google Scholar 

  20. Lamers, L. M., Bouwmans, C. A., van Straten, A., Donker, M. C., & Hakkaart, L. (2006). Comparison of EQ-5D and SF-6D utilities in mental health patients. Health Economics, 15(11), 1229–1236.

    Article  CAS  PubMed  Google Scholar 

  21. Brazier, J., Roberts, J., Tsuchiya, A., & Busschbach, J. (2004). A comparison of the EQ-5D and SF-6D across seven patient groups. Health Economics, 13(9), 873–884.

    Article  PubMed  Google Scholar 

  22. Richardson, J., Iezzi, A., & Khan, M. A. (2015). Why do multi-attribute utility instruments produce different utilities: The relative importance of the descriptive systems, scale and ‘micro-utility’ effects. Quality of Life Research, 24(8), 2045–2053.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Feeny, D., Spritzer, K., Hays, R. D., Liu, H., Ganiats, T. G., Kaplan, R. M., et al. (2012). Agreement about identifying patients who change over time: cautionary results in cataract and heart failure patients. Medical Decision Making: An International Journal of the Society for Medical Decision Making, 32(2), 273–286.

    Article  Google Scholar 

  24. van Stel, H. F., & Buskens, E. (2006). Comparison of the SF-6D and the EQ-5D in patients with coronary heart disease. Health and Quality of Life Outcomes, 4, 20.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Chan, Y.-K., Stewart, S., Calderone, A., Scuffham, P., Goldstein, S., & Carrington, M. J. (2012). Exploring the potential to remain “Young @ Heart”: Initial findings of a multi-centre, randomised study of nurse-led, home-based intervention in a hybrid health care system. International Journal of Cardiology, 154(1), 52–58.

    Article  PubMed  Google Scholar 

  26. Carrington, M. J., Chan, Y. K., Calderone, A., Scuffham, P. A., Esterman, A., Goldstein, S., et al. (2013). A multicenter, randomized trial of a nurse-led, home-based intervention for optimal secondary cardiac prevention suggests some benefits for men but not for women: the Young at Heart study. Circulation: Cardiovascular Quality of Outcomes, 6(4), 379–389.

    Google Scholar 

  27. Williams, J. R. (2008). The Declaration of Helsinki and public health. Bulletin of the World Health Organization, 86(8), 650–652.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Antes, G. (2010). The new CONSORT statement. BMJ: British Medical Journal, 340(7748), 666–667.

    Google Scholar 

  29. Ramos-Goñi, J. M., & Rivero-Arias, O. (2011). eq5d: A command to calculate index values for the EQ-5D quality-of-life instrument. Stata Journal, 11(1), 120–125.

    Google Scholar 

  30. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.

    Article  CAS  PubMed  Google Scholar 

  31. Kularatna, S., Whitty, J. A., Johnson, N. W., Jayasinghe, R., & Scuffham, P. A. (2016). A comparison of health state utility values associated with oral potentially malignant disorders and oral cancer in Sri Lanka assessed using the EQ-5D-3 L and the EORTC-8D. Health Quality of Life Outcomes, 14, 101.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Teckle, P., Peacock, S., McTaggart-Cowan, H., van der Hoek, K., Chia, S., Melosky, B., et al. (2011). The ability of cancer-specific and generic preference-based instruments to discriminate across clinical and self-reported measures of cancer severities. Health Quality of Life Outcomes, 9, 106.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Whitehurst, D. G. T., Bryan, S., & Lewis, M. (2011). Systematic review and empirical comparison of contemporaneous EQ-5D and SF-6D group mean scores. Medical Decision Making, 31(6), E34–E44.

    Article  PubMed  Google Scholar 

  34. Pickard, A. S., Johnson, J. A., & Feeny, D. H. (2005). Responsiveness of generic health-related quality of life measures in stroke. Quality of Life Research, 14(1), 207–219.

    Article  PubMed  Google Scholar 

  35. Longworth, L., & Bryan, S. (2003). An empirical comparison of EQ-5D and SF-6D in liver transplant patients. Health Economics, 12(12), 1061–1067.

    Article  PubMed  Google Scholar 

  36. Brazier, J., Rowen, D., Tsuchiya, A., Yang, Y., & Young, T. A. (2011). The impact of adding an extra dimension to a preference-based measure. Social Science and Medicine, 73(2), 245–253.

    Article  PubMed  PubMed Central  Google Scholar 

  37. National Institute for Health and Care Excellence (NICE). (2001). Technical guidance for manufacturers and sponsors on making a submission to a technology appraisal. London: NICE.

    Google Scholar 

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Authors

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Correspondence to Sanjeewa Kularatna.

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Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This study made use of clinical trial data. The trial was registered with the Australian New Zealand Clinical Trials Registry (No. 12608000014358) and conforms to both the principles outlined in the Declaration of Helsinki.

Informed consent

The study was approved by the human Research Ethics Committee of Uniting Care Health, Brisbane, Australia, and all patients provided written informed consent to participate.

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Kularatna, S., Byrnes, J., Chan, Y.K. et al. Comparison of the EQ-5D-3L and the SF-6D (SF-12) contemporaneous utility scores in patients with cardiovascular disease. Qual Life Res 26, 3399–3408 (2017). https://doi.org/10.1007/s11136-017-1666-6

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  • DOI: https://doi.org/10.1007/s11136-017-1666-6

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