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The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common?

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Abstract

Purpose

EQ-5D, HUI II and SF-6D often produce very different valuations for the same health state. This paper aims at clarifying to what extent this might be caused by differences between the multi-attribute classification systems belonging to these instruments.

Methods

Subjects were 264 patients of rehabilitation clinics in Mecklenburg-Western Pomerania (44.3% female; mean age 49.1) who completed the EQ-5D, the HUI II and the SF-36 (the basis of the SF-6D). After scaling with principal component analyses for categorical data, each attribute of each classification system was regressed on the classification systems of the other two instruments, and all attributes together were subjected to ordinary principal component analysis with varimax rotation.

Results

Adjusted multiple R 2 for regression analyses ranged from 0.01 to 0.57. The HUI II attribute ‘sensation’ and the SF-6D attribute ‘role limitation’ are virtually unrelated to the remainder. All other attributes of all three instruments can be predicted by each other. EQ-5D and HUI II focus distinctly more on physical functioning than SF-6D.

Conclusion

Although all three classification systems have a lot in common, they differ so much that EQ-5D, HUI II and SF-6D would produce different valuations even if these valuations were determined according to the same principle.

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Abbreviations

EQ-5D:

Euro-Qol 5 Dimensions

HRQoL:

Health-Related Quality of Life

HUI:

Health Utility Index

HUI II:

Health Utility Index, Mark II

HUI III:

Health Utility Index, Mark III

PCACAT:

Principal Component Analysis for Categorical Data

PCACATs:

Principal Component Analysis for Categorical Data

R 2adj :

Adjusted squared multiple correlation coefficient

SEQ:

Standardised estimated quantification

SEQs:

Standardised estimated quantifications

SF-36:

Short Form 36 items

SF-6D:

Short Form 6 Dimensions

SPSS:

Statistical Package for the Social Sciences

SPSS 15.0:

Statistical Package for the Social Sciences, Version 15.0

References

  1. Brooks, R., & The EuroQol Group. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  3. Feeny, D., Furlong, W., Boyle, M., & Torrance, G. W. (1995). Multi-attribute health status classification systems. Pharmacoeconomics, 7(6), 490–502.

    Article  PubMed  CAS  Google Scholar 

  4. Furlong, W. J., Feeny, D. H., Torrance, G. W., & Barr, R. D. (2001). The Health Utilities Index (HUI) system for assessing health-related quality of life in clinical studies. Annals of Medicine, 33(5), 375–384.

    Article  PubMed  CAS  Google Scholar 

  5. 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 

  6. Brazier, J., Usherwood, T., Harper, R., & Thomas, K. (1998). Deriving a preference-based single index from the UK SF-36 Health Survey. Journal of Clinical Epidemiology, 51(11), 1115–1128.

    Article  PubMed  CAS  Google Scholar 

  7. Ware, J. E., Kosinski, M., & Dewey, J. E. (2000). How to score version two of the SF-36 health survey. Lincoln, RI: QualityMetric, Incorporated.

    Google Scholar 

  8. Ware, J. E., & Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36). Medical Care, 30(6), 473–483.

    Article  PubMed  Google Scholar 

  9. Michaels, J. A., Brazier, J. E., Campbell, W. B., MacIntyre, J. B., Palfreyman, S. J., & Ratcliffe, J. (2006). Randomized clinical trial comparing surgery with conservative treatment for uncomplicated varicose veins. The British Journal of Surgery, 93(2), 175–181.

    Article  PubMed  CAS  Google Scholar 

  10. Teng, Y. K., Verburg, R. J., Sont, J. K., van den Hout, W. B., Breedveld, F. C., & van Laar, J. M. (2005). Long-term followup of health status in patients with severe rheumatoid arthritis after high-dose chemotherapy followed by autologous hematopoietic stem cell transplantation. Arthritis and Rheumatism, 52(8), 2272–2276.

    Article  PubMed  CAS  Google Scholar 

  11. van den Hout, W. B., de Jong, Z., Munneke, M., Hazes, J. M., Breedveld, F. C., & Vliet Vlieland, T. P. (2005). Cost-utility and cost-effectiveness analyses of a long-term, high-intensity exercise program compared with conventional physical therapy in patients with rheumatoid arthritis. Arthritis and Rheumatism, 53(1), 39–47.

    Article  PubMed  Google Scholar 

  12. Barton, G. R., Bankart, J., & Davis, A. C. (2005). A comparison of the quality of life of hearing-impaired people as estimated by three different utility measures. International Journal of Audiology, 44(3), 157–163.

    Article  PubMed  Google Scholar 

  13. Barton, G. R., Bankart, J., Davis, A. C., & Summerfield, Q. A. (2004). Comparing utility scores before and after hearing-aid provision: Results according to the EQ-5D, HUI3 and SF-6D. Applied Health Economics and Health Policy, 3(2), 103–105.

    Article  PubMed  Google Scholar 

  14. 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 

  15. Conner-Spady, B., & Suarez-Almazor, M. E. (2003). Variation in the estimation of quality-adjusted life-years by different preference-based instruments. Medical Care, 41(7), 791–801.

    Article  PubMed  Google Scholar 

  16. Espallargues, M., Czoski-Murray, C. J., Bansback, N. J., Carlton, J., Lewis, G. M., Hughes, L. A., et al. (2005). The impact of age-related macular degeneration on health status utility values. Investigative Ophthalmology and Visual Science, 46(11), 4016–4023.

    Article  PubMed  Google Scholar 

  17. Feeny, D., Wu, L., & Eng, K. (2004). Comparing short form 6D, standard gamble, and Health Utilities Index Mark 2 and Mark 3 utility scores: results from total hip arthroplasty patients. Quality of Life Research, 13(10), 1659–1670.

    Article  PubMed  Google Scholar 

  18. Franks, P., Hanmer, J., & Fryback, D. G. (2006). Relative disutilities of 47 risk factors and conditions assessed with seven preference-based health status measures in a national U.S. sample: toward consistency in cost-effectiveness analyses. Medical Care, 44(5), 478–485.

    Article  PubMed  Google Scholar 

  19. 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(5), 358–370.

    Article  PubMed  CAS  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  PubMed  CAS  Google Scholar 

  21. Luo, N., Johnson, J. A., Shaw, J. W., Feeny, D., & Coons, S. J. (2005). Self-reported health status of the general adult U.S. population as assessed by the EQ-5D and Health Utilities Index. Medical Care, 43(11), 1078–1086.

    Article  PubMed  Google Scholar 

  22. Marra, C. A., Esdaile, J. M., Guh, D., Kopec, J. A., Brazier, J. E., Koehler, B. E., et al. (2004). A comparison of four indirect methods of assessing utility values in rheumatoid arthritis. Medical Care, 42(11), 1125–1131.

    Article  PubMed  Google Scholar 

  23. McDonough, C. M., Grove, M. R., Tosteson, T. D., Lurie, J. D., Hilibrand, A. S., & Tosteson, A. N. (2005). Comparison of EQ-5D, HUI, and SF-36-derived societal health state values among spine patient outcomes research trial (SPORT) participants. Quality of Life Research, 14(5), 1321–1332.

    Article  PubMed  Google Scholar 

  24. Moock, J., & Kohlmann, T. (2008). Comparing preference-based quality-of-life measures: results from rehabilitation patients with musculoskeletal, cardiovascular, or psychosomatic disorders. Quality of Life Research, 17(3), 485–495.

    Article  PubMed  Google Scholar 

  25. O’Brien, B. J., Spath, M., Blackhouse, G., Severens, J. L., Dorian, P., & Brazier, J. (2003). A view from the bridge: agreement between the SF-6D utility algorithm and the Health Utilities Index. Health Economics, 12(11), 975–981.

    Article  PubMed  Google Scholar 

  26. Petrou, S., & Hockley, C. (2005). An investigation into the empirical validity of the EQ-5D and SF-6D based on hypothetical preferences in a general population. Health Economics, 14(11), 1169–1189.

    Article  PubMed  Google Scholar 

  27. 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 

  28. Siderowf, A., Ravina, B., & Glick, H. A. (2002). Preference-based quality-of-life in patients with Parkinson’s disease. Neurology, 59(1), 103–108.

    PubMed  Google Scholar 

  29. Stavem, K., Froland, S. S., & Hellum, K. B. (2005). Comparison of preference-based utilities of the 15D, EQ-5D and SF-6D in patients with HIV/AIDS. Quality of Life Research, 14(4), 971–980.

    Article  PubMed  Google Scholar 

  30. Szende, A., Svensson, K., Ståhl, E., Mészáros, A., & Berta, G. Y. (2004). Psychometric and utility-based measures of health status of asthmatic patients with different disease control level. Pharmacoeconomics, 22(8), 537–547.

    Article  PubMed  Google Scholar 

  31. Thomas K.J., MacPherson H., Ratcliffe J., Thorpe L., Brazier J., Campbell M., Fitter M., Roman M., Walters S., Nicholl J. P. (2005). Longer term clinical and economic benefits of offering acupuncture care to patients with chronic low back pain. Health Technology Assessment, 9(32), iii-iv, ix-x, 1–109.

    Google Scholar 

  32. 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, 25, 4:20.

    Google Scholar 

  33. Kopec, A., & Willison, K. D. (2003). A comparative review of four preference-weighted measures of health-related quality of life. Journal of Clinical Epidemiology, 56, 317–325.

    Article  PubMed  Google Scholar 

  34. 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  Google Scholar 

  35. 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(7), 702–722.

    Article  PubMed  CAS  Google Scholar 

  36. Bryan, S., & Longworth, L. (2005). Measuring health-related utility: Why the disparity between EQ-5D and SF-6D? European Journal of Health Economics, 6(3), 253–260.

    Article  PubMed  Google Scholar 

  37. Anagnostopoulos, F., Niakas, D., & Pappa, E. (2005). Construct validation of the Greek SF-36 Health Survey. Quality of Life Research, 14(8), 1959–1965.

    Article  PubMed  Google Scholar 

  38. Augustovski, F. A., Lewin, G., Elorrio, E. G., & Rubinstein, A. (2008). The Argentine-Spanish SF-36 Health Survey was successfully validated for local outcome research. Journal of Clinical Epidemiology, 61(12), 1279–1284.

    Article  PubMed  Google Scholar 

  39. Beals, J., Welty, T. K., Mitchell, C. M., Rhoades, D. A., Yeh, J. L., Henderson, J. A., et al. (2006). Different factor loadings for SF36: The strong heart study and the national survey of functional health status. Journal of Clinical Epidemiology, 59(2), 208–215.

    Article  PubMed  Google Scholar 

  40. Fukuhara, S., Bito, S., Green, J., Hsiao, A., & Kurokawa, K. (1998). Translation, adaptation, and validation of the SF-36 Health Survey for use in Japan. Journal of Clinical Epidemiology, 51(11), 1037–1044.

    Article  PubMed  CAS  Google Scholar 

  41. Fukuhara, S., Ware, J. E., Jr, Kosinski, M., Wada, S., & Gandek, B. (1998). Psychometric and clinical tests of validity of the Japanese SF-36 Health Survey. Journal of Clinical Epidemiology, 51(11), 1045–1053.

    Article  PubMed  CAS  Google Scholar 

  42. Hann, M., & Reeves, D. (2008). The SF-36 scales are not accurately summarised by independent physical and mental component scores. Quality of Life Research, 17(3), 413–423.

    Article  PubMed  Google Scholar 

  43. Jenkinson, C., Stewart-Brown, S., Petersen, S., & Paice, C. (1999). Assessment of the SF-36 version 2 in the United Kingdom. Journal of Epidemiology and Community Health, 53(1), 46–50.

    Article  PubMed  CAS  Google Scholar 

  44. Lewin-Epstein, N., Sagiv-Schifter, T., Shabtai, E. L., & Shmueli, A. (1998). Validation of the 36-item short-form Health Survey (Hebrew version) in the adult population of Israel. Medical Care, 36(9), 1361–1370.

    Article  PubMed  CAS  Google Scholar 

  45. Li, L., Wang, H. M., & Shen, Y. (2003). Chinese SF-36 Health Survey: Translation, cultural adaptation, validation, and normalisation. Journal of Epidemiology and Community Health, 57(4), 259–263.

    Article  PubMed  CAS  Google Scholar 

  46. Maslić Sersić, D., & Vuletić, G. (2006). Psychometric evaluation and establishing norms of Croatian SF-36 health survey: Framework for subjective health research. Croatian Medical Journal, 47(1), 95–102.

    PubMed  Google Scholar 

  47. McHorney, C. A., Ware, J. E., Jr, & Raczek, A. E. (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31(3), 247–263.

    Article  PubMed  CAS  Google Scholar 

  48. Mishra, G., & Schofield, M. J. (1998). Norms for the physical and mental health component summary scores of the SF-36 for young, middle-aged and older Australian women. Quality of Life Research, 7(3), 215–220.

    Article  PubMed  CAS  Google Scholar 

  49. Montazeri, A., Goshtasebi, A., Vahdaninia, M., & Gandek, B. (2005). The Short Form Health Survey (SF-36): Translation and validation study of the Iranian version. Quality of Life Research, 14(3), 875–882.

    Article  PubMed  Google Scholar 

  50. Sanson-Fisher, R. W., & Perkins, J. J. (1998). Adaptation and validation of the SF-36 Health Survey for use in Australia. Journal of Clinical Epidemiology, 51(11), 961–967.

    Article  PubMed  CAS  Google Scholar 

  51. Thumboo, J., Fong, K. Y., Machin, D., Chan, S. P., Leon, K. H., Feng, P. H., et al. (2001). A community-based study of scaling assumptions and construct validity of the English (UK) and Chinese (HK) SF-36 in Singapore. Quality of Life Research, 10(2), 175–188.

    Article  PubMed  CAS  Google Scholar 

  52. Ware, J. E., Jr, Gandek, B., Kosinski, M., Aaronson, N. K., Apolone, G., Brazier, J., et al. (1998). The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: results from the IQOLA Project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51(11), 1167–1170.

    Article  PubMed  Google Scholar 

  53. Ware, J. E., Jr, Kosinski, M., Gandek, B., Aaronson, N. K., Apolone, G., Bech, P., et al. (1998). The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA Project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51(11), 1159–1165.

    Article  PubMed  Google Scholar 

  54. Wu, C. H., Lee, K. L., & Yao, G. (2007). Examining the hierarchical factor structure of the SF-36 Taiwan version by exploratory and confirmatory factor analysis. Journal of Evaluation in Clinical Practice, 13(6), 889–900.

    PubMed  Google Scholar 

  55. Essink-Bot, M. L., Krabbe, P. F., Bonsel, G. J., & Aaronson, N. K. (1997). An empirical comparison of four generic health status measures. The Nottingham Health Profile, the Medical Outcomes Study 36-item Short-Form Health Survey, the COOP/WONCA charts, and the EuroQol instrument. Medical Care, 35(5), 522–537.

    Article  PubMed  CAS  Google Scholar 

  56. Huang, I. C., Hwang, C. C., Wu, M. Y., Lin, W., Leite, W., & Wu, A. W. (2008). Diabetes-specific or generic measures for health-related quality of life? Evidence from psychometric validation of the D-39 and SF-36. Value in Health, 11(3), 450–461.

    Article  PubMed  CAS  Google Scholar 

  57. Huang, I. C., Wu, A. W., & Frangakis, C. (2006). Do the SF-36 and WHOQOL-BREF measure the same constructs? Evidence from the Taiwan population. Quality of Life Research, 15(1), 15–24.

    Article  PubMed  CAS  Google Scholar 

  58. Meijer, C. J., Schene, A. H., & Koeter, M. W. (2002). Quality of life in schizophrenia measured by the MOS SF-36 and the Lancashire Quality of Life Profile: A comparison. Acta Psychiatrica Scandinavica, 105(4), 293–300.

    Article  PubMed  CAS  Google Scholar 

  59. Furlong, W. J., Feeny, D. H., & Torrance, G. W. (2002). Health utilities index (HUI) procedures manual. Dundas Ontario Canada: Health Utilities Incorporation.

    Google Scholar 

  60. Brazier J., Walters S. (2003). SF-6D UK Programme. SPSS-Syntax. 24 October 2003.

  61. Gifi, A. (1990). Nonlinear multivariate analysis. New York: John Wiley.

    Google Scholar 

  62. Brachinger, H. W., & Ost, F. (1996). Modelle mit latenten Variablen: Faktorenanalyse, Latent-Structure-Analyse und LISREL-Analyse [Models with latent variables: Factor analysis, latent structure analysis and LISREL analysis]. In L. Fahrmeir, A. Hamerle, & G. Tutz (Eds.), Multivariate statistische Verfahren, 2. erweiterte Auflage [Multivariate statistical methods, 2nd extended edition] (pp. 639–766). Berlin: Walter de Gruyter.

    Google Scholar 

  63. Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. New York: Houghton Mifflin.

    Google Scholar 

  64. Munro, B. H. (1997). Regression. In B. H. Munro (Ed.), Statistical methods in health care (pp. 246–286). Philadelphia, New York: Lippincott.

    Google Scholar 

  65. Grieve, R., Grishchenko, M., & Cairns, J. (2009). SF-6D versus EQ-5D: Reasons for differences in utility scores and impact on reported cost-utility. European Journal of Health Economy, 10, 15–23.

    Article  Google Scholar 

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Acknowledgments

This project was funded by a grant (no. 01GD0106) from the German Federal Ministry of Education and Research within the North German Network for Rehabilitation Research (NVRF). The analyses presented here were financially supported by an additional grant from the German Federal Ministry of Education and Research (grant no. 01ZZ0403). We would like to thank Kathrin Bezold for her support in performing the study, three anonymous reviewers for critically discussing a former version of the manuscript, and Peter Bereza for correcting our English.

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Authors and Affiliations

  1. Trimberg Research Academy, University of Bamberg, c/o Kapuziner Straße 16, 96047, Bamberg, Germany

    Uwe Konerding

  2. Institute for Community Medicine, University of Greifswald, Walther-Rathenau-Straße 48, 17475, Greifswald, Germany

    Jörn Moock & Thomas Kohlmann

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  1. Uwe Konerding
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Correspondence to Uwe Konerding.

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Konerding, U., Moock, J. & Kohlmann, T. The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common?. Qual Life Res 18, 1249–1261 (2009). https://doi.org/10.1007/s11136-009-9525-8

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