Top

Quality of Life Research

Gepubliceerd in:

01-02-2009

Comparing SF-6D and EQ-5D utilities across groups differing in health status

Auteurs: Nick Kontodimopoulos, Evelina Pappa, Angelos A. Papadopoulos, Yannis Tountas, Dimitris Niakas

Gepubliceerd in: Quality of Life Research | Uitgave 1/2009

Abstract

Objectives

To compare the EQ-5D and SF-6D within socio-demographic and clinical groups in a representative sample (n = 1,005) of the Greek general population and to examine mean utility differences across groups differing in health in this population and in a highly morbid disease sample (diabetes, n = 215).

Methods

Association and level of agreement between instruments were estimated with Pearson’s r and the intraclass correlation coefficient (ICC), respectively. Paired-samples t-test was used to identify significant score differences, which were regarded as minimally important differences (MID) when they exceeded 0.03. The EQ-VAS was used to classify individuals into health status groups, covering the range from very poor to very good health, and the same classification was used in the diabetes sample.

Results

EQ-5D and SF-6D were in agreement and strongly correlated over the entire sample (ICC = 0.536, P < 0.001 and r = 0.662, P < 0.001), but correlation varied according to socio-demographic factors and clinical conditions. In healthier responders, EQ-5D scores were significantly higher than SF-6D scores (P < 0.001) and differences constituted MIDs. Contrarily, in individuals with clinical conditions, SF-6D scores were predominantly higher than EQ-5D. The pattern of results was replicated in the disease sample as well.

Conclusions

The hypotheses that EQ-5D generates higher scores in healthier populations and the SF-6D in less healthier groups were confirmed. Based on the evidence provided here, EQ-5D and SF-6D measuring discrepancies generate utility differences across VAS-based health groups, which warrant further within-sample investigation.

vorige artikel Disease-specific health-related quality of life questionnaires for heart failure: a systematic review with meta-analyses

volgende artikel Using patient-reported outcomes in clinical practice: challenges and opportunities

Drummond, M. F., O’Brien, B. J., Stoddard, G. L., & Torrance, G. W. (1997). Methods for the economic evaluation of health care programmes (2nd ed.). Oxford: Oxford University Press.

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, 9–18. doi:10.1177/0272989X9401400102.PubMedCrossRef

Räsänen, P., Roine, E., Sintonen, H., Semberg-Konttinen, V., Ryynänen, O. P., & Roine, R. (2006). Use of quality-adjusted life years for the estimation of effectiveness of health care: A systematic literature review. International Journal of Technology Assessment in Health Care, 22, 235–241. doi:10.1017/S0266462306051051.PubMedCrossRef

Rosser, R., & Kind, P. (1978). A scale of valuations of states of illness: Is there a social consensus? International Journal of Epidemiology, 7, 347–358. doi:10.1093/ije/7.4.347.PubMedCrossRef

Sintonen, H., & Pekurinen, M. (1993). A fifteen-dimensional measure of health-related quality of health-related quality of life (15D) and its applications. In S. R. Walker & R. M. Rosser (Eds.), Quality of life assessment. Key issues in the 1990s (pp. 185–195). Dordrecht: Kluwer.

Kaplan, R. M., & Anderson, J. P. (1988). A general health policy model: Update and applications. Health Services Research, 23, 203–235.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. doi:10.1097/00005650-199607000-00004.PubMedCrossRef

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. doi:10.1097/00005650-200202000-00006.PubMedCrossRef

Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35, 1095–1108. doi:10.1097/00005650-199711000-00002.PubMedCrossRef

10.

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. doi:10.1016/S0167-6296(01)00130-8.PubMedCrossRef

11.

Ware, J. E., Jr., & Sherbourne, C. D. (1992). The MOS 36-item Short-Form Health Survey (SF-36). I. Conceptual framework and item selection. Medical Care, 30, 473–483. doi:10.1097/00005650-199206000-00002.PubMedCrossRef

12.

The EuroQol group. (1990). EuroQol—a new facility for the measurement of health-related quality of life. Health Policy (Amsterdam), 16, 199–208. doi:10.1016/0168-8510(90)90421-9.

13.

Brooks, R. (1996). EuroQol: The current state of play. Health Policy (Amsterdam), 37, 53–72. doi:10.1016/0168-8510(96)00822-6.

14.

Dolan, P., Gudex, C., Kind, P., & Williams, A. (1996). The time trade-off method: Results from a general population study. Health Economics, 5, 141–154. doi:10.1002/(SICI)1099-1050(199603)5:2<141::AID-HEC189>3.0.CO;2-N.PubMedCrossRef

15.

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, 1115–1128. doi:10.1016/S0895-4356(98)00103-6.PubMedCrossRef

16.

Brazier, J., Jones, N., & Kind, P. (1993). Testing the validity of the Euroqol and comparing it with the SF-36 health survey questionnaire. Quality of Life Research, 2, 169–180. doi:10.1007/BF00435221.PubMedCrossRef

17.

Bryan, S., & Longworth, L. (2005). Measuring health-related utility: Why the disparity between EQ-5D and SF-6D? The European Journal of Health Economics, 6, 253–260. doi:10.1007/s10198-005-0299-9.PubMedCrossRef

18.

Longworth, L., & Bryan, S. (2003). An empirical comparison of EQ-5D and SF-6D in liver transplant patients. Health Economics, 12, 1061–1067. doi:10.1002/hec.787.PubMedCrossRef

19.

Gerard, K., Nicholson, T., Mullee, M., Mehta, R., & Roderick, P. (2004). EQ-5D versus SF-6D in an older, chronically ill patient group. Applied Health Economics and Health Policy, 3, 91–102. doi:10.2165/00148365-200403020-00005.PubMedCrossRef

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, 1229–1236. doi:10.1002/hec.1125.PubMedCrossRef

21.

Xie, F., Li, S. C., Luo, N., Lo, N. N., Yeo, S. J., Yang, K. Y., et al. (2007). Comparison of the EuroQol and short form 6D in Singapore multiethnic Asian knee osteoarthritis patients scheduled for total knee replacement. Arthritis and Rheumatism, 57, 1043–1049. doi:10.1002/art.22883.PubMedCrossRef

22.

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, 873–884. doi:10.1002/hec.866.PubMedCrossRef

23.

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. doi:10.1186/1477-7525-4-20.PubMedCrossRef

24.

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, 1169–1189. doi:10.1002/hec.1006.PubMedCrossRef

25.

Bharmal, M., & Thomas, J., 3rd (2006). Comparing the EQ-5D and the SF-6D descriptive systems to assess their ceiling effects in the US general population. Value in Health, 9, 262–271. doi:10.1111/j.1524-4733.2006.00108.x.PubMedCrossRef

26.

Barton, G. R., Sach, T. H., Avery, A. J., Jenkinson, C., Doherty, M. Whynes, D. K., et al. (2008). A comparison of the performance of the EQ-5D and SF-6D for individuals aged ≥45 years. Health Economics, 17, 815–832. doi:10.1002/hec.1298.PubMedCrossRef

27.

Yfantopoulos, J. (2001). The Greek version of the EuroQol (EQ-5D) instrument. Archives of Hellenic Medicine, 18, 180–191.

28.

Kontodimopoulos, N., Pappa, E., Niakas, D., Yfantopoulos, J., Dimitrakaki, C., & Tountas, Y. (2008). Validity of the EuroQoL (EQ-5D) instrument in a Greek general population. Value in Health, 11, 1162–1169. doi:10.1111/j.1524-4733.2008.00356.x.CrossRef

29.

Pappa, E., Kontodimopoulos, N., & Niakas, D. (2005). Validating and norming of the Greek SF-36 Health Survey. Quality of Life Research, 14, 1433–1438. doi:10.1007/s11136-004-6014-y.PubMedCrossRef

30.

Anagnostopoulos, F., Niakas, D., & Pappa, E. (2005). Construct validation of the Greek SF-36 Health Survey. Quality of Life Research, 14, 1959–1965. doi:10.1007/s11136-005-3866-8.PubMedCrossRef

31.

Kontodimopoulos, N., & Niakas, D. (2008). An estimate of lifelong costs and QALYs in renal replacement therapy based on patients’ life expectancy. Health Policy (Amsterdam), 86, 85–96.

32.

Maddigan, S. L., Feeny, D. H., & Johnson, J. A. (2005). Health-related quality of life deficits associated with diabetes and comorbidities in a Canadian National Population Health Survey. Quality of Life Research, 14, 1311–1320. doi:10.1007/s11136-004-6640-4.PubMedCrossRef

33.

Papadopoulos, A. A., Kontodimopoulos, N., Frydas, A., Ikonomakis, E., & Niakas, D. (2007). Predictors of health-related quality of life in type II diabetic patients in Greece. BMC Public Health, 7, 186. doi:10.1186/1471-2458-7-186.PubMedCrossRef

34.

Franks, P., Gold, M. R., & Fiscella, K. (2003). Sociodemographics, self-rated health, and mortality in the US. Social Science and Medicine, 56, 2505–2514. doi:10.1016/S0277-9536(02)00281-2.PubMedCrossRef

35.

Jiang, Y., & Hesser, J. E. (2006). Associations between health-related quality of life and demographics and health risks. Results from Rhode Island’s 2002 behavioral risk factor survey. Health and Quality of Life Outcomes, 4, 14. doi:10.1186/1477-7525-4-14.PubMedCrossRef

36.

Lam, C. L., Fong, D. Y., Lauder, I., & Lam, T. P. (2002). The effect of health-related quality of life (HRQOL) on health service utilisation of a Chinese population. Social Science and Medicine, 55, 1635–1646. doi:10.1016/S0277-9536(01)00296-9.PubMedCrossRef

37.

Pappa, E., & Niakas, D. (2006). Assessment of health care needs and utilization in a mixed public-private system: The case of the Athens area. BMC Health Services Research, 6, 146. doi:10.1186/1472-6963-6-146.PubMedCrossRef

38.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033-2909.112.1.155.CrossRef

39.

Jaeschke, R., Singer, J., & Guyatt, G. H. (1989). Measurement of health status. Ascertaining the minimal clinically important difference. Controlled Clinical Trials, 10, 407–415. doi:10.1016/0197-2456(89)90005-6.PubMedCrossRef

40.

Walters, S. J., & Brazier, J. E. (2003). What is the relationship between the minimally important difference and health state utility values? The case of the SF-6D. Health and Quality of Life Outcomes, 1, 4. doi:10.1186/1477-7525-1-4.PubMedCrossRef

41.

Sullivan, P. W., Lawrence, W. F., & Ghushchyan, V. (2005). A national catalog of preference-based scores for chronic conditions in the United States. Medical Care, 43, 736–749. doi:10.1097/01.mlr.0000172050.67085.4f.PubMedCrossRef

42.

Marra, C. A., Woolcott, J. C., Kopec, J. A., Shojania, K., Offer, R., Brazier, J. E., et al. (1995). A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Social Science and Medicine, 60, 1571–1582. doi:10.1016/j.socscimed.2004.08.034.

43.

Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research, 14, 1523–1532. doi:10.1007/s11136-004-7713-0.PubMedCrossRef

44.

Badia, X., Schiaffino, A., Alonso, J., & Herdman, M. (1998). Using the EuroQol 5-D in the Catalan general population: Feasibility and construct validity. Quality of Life Research, 7, 311–322. doi:10.1023/A:1008894502042.PubMedCrossRef

45.

Johnson, J. A., & Coons, S. J. (1998). Comparison of the EQ-5D and SF-12 in an adult US sample. Quality of Life Research, 7, 155–166. doi:10.1023/A:1008809610703.PubMedCrossRef

46.

Kind, P., Dolan, P., Gudex, C., & Williams, A. (1998). Variations in population health status: Results from a United Kingdom national questionnaire survey. BMJ (Clinical Research Ed.), 316, 736–741.

47.

Johnson, J. A., & Pickard, A. S. (2000). Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada. Medical Care, 38, 115–121. doi:10.1097/00005650-200001000-00013.PubMedCrossRef

48.

Lubetkin, E. I., Jia, H., Franks, P., & Gold, M. R. (2005). Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the U.S. general population. Quality of Life Research, 14, 2187–2196. doi:10.1007/s11136-005-8028-5.PubMedCrossRef

49.

Savoia, E., Fantini, M. P., Pandolfi, P. P., Dallolio, L., & Collina, N. (2006). Assessing the construct validity of the Italian version of the EQ-5D: Preliminary results from a cross-sectional study in North Italy. Health and Quality of Life Outcomes, 4, 47. doi:10.1186/1477-7525-4-47.PubMedCrossRef

50.

Jia, H., & Lubetkin, E. I. (2005). The impact of obesity on health-related quality-of-life in the general adult US population. Journal of Public Health, 27, 156–164. doi:10.1093/pubmed/fdi025.PubMedCrossRef

51.

Sach, T. H., Barton, G. R., Doherty, M., Muir, K. R., Jenkinson, C., & Avery, A. J. (2007). The relationship between body mass index and health-related quality of life: Comparing the EQ-5D, EuroQol VAS and SF-6D. International Journal of Obesity, 31, 189–196. doi:10.1038/sj.ijo.0803365.PubMedCrossRef

52.

Barton, G. R., Sach, T. H., Doherty, M., Avery, A. J., Jenkinson, C., & Muir, K. R. (2008). An assessment of the discriminative ability of the EQ-5D_index, SF-6D, and EQ VAS, using sociodemographic factors and clinical conditions. The European Journal of Health Economics, 9, 237–249. doi:10.1007/s10198-007-0068-z.PubMedCrossRef

53.

Walters, S. J., & Campbell, M. J. (2004). The use of bootstrap methods for analysing health-related quality of life outcomes (particularly the SF-36). Health and Quality of Life Outcomes, 2, 70. doi:10.1186/1477-7525-2-70.PubMedCrossRef

54.

Bleichrodt, H. (2002). A new explanation for the difference between time trade-off utilities and standard gamble utilities. Health Economics, 11, 447–456. doi:10.1002/hec.688.PubMedCrossRef

55.

Green, C., Brazier, J., & Deverill, M. (2000). Valuing health-related quality of life. A review of health state valuation techniques. PharmacoEconomics, 17, 151–165. doi:10.2165/00019053-200017020-00004.PubMedCrossRef

56.

Dolan, P., Gudex, C., Kind, P., & Williams, A. (1996). Valuing health states: A comparison of methods. Journal of Health Economics, 15, 209–231. doi:10.1016/0167-6296(95)00038-0.PubMedCrossRef

57.

Dolan, P., & Sutton, M. (1997). Mapping visual analogue scale health state valuations onto standard gamble and time trade-off values. Social Science and Medicine, 44, 1519–1530. doi:10.1016/S0277-9536(96)00271-7.PubMedCrossRef

58.

Fortin, M., Hudon, C., Dubois, M. F., Almirall, J., Lapointe, L., & Soubhi, H. (2005). Comparative assessment of three different indices of multimorbidity for studies on health-related quality of life. Health and Quality of Life Outcomes, 3, 74. doi:10.1186/1477-7525-3-74.PubMedCrossRef

59.

Tokmakidis, S. P., Christodoulos, A. D., & Mantzouranis, N. I. (2007). Validity of self-reported anthropometric values used to assess body mass index and estimate obesity in Greek school children. The Journal of Adolescent Health, 40, 305–310. doi:10.1016/j.jadohealth.2006.10.001.PubMedCrossRef

60.

Stergiou, G. S., Thomopoulou, G. C., Skeva, I. I., & Mountokalakis, T. D. (1999). Prevalence, awareness, treatment, and control of hypertension in Greece: the Didima study. American Journal of Hypertension, 12, 959–965. doi:10.1016/S0895-7061(99)00136-3.PubMedCrossRef

Titel: Comparing SF-6D and EQ-5D utilities across groups differing in health status
Auteurs: Nick Kontodimopoulos
Evelina Pappa
Angelos A. Papadopoulos
Yannis Tountas
Dimitris Niakas
Publicatiedatum: 01-02-2009
Uitgeverij: Springer Netherlands
Gepubliceerd in: Quality of Life Research / Uitgave 1/2009
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-008-9420-8

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Objectives

Methods

Results

Conclusions

Log in om toegang te krijgen

Andere artikelen Uitgave 1/2009

The applications of PROs in clinical practice: what are they, do they work, and why?

Logistics of collecting patient-reported outcomes (PROs) in clinical practice: an overview and practical examples

Psychological insulin resistance: patient beliefs and implications for diabetes management

A conceptual framework for patient–provider communication: a tool in the PRO research tool box

Using patient-reported outcomes in clinical practice: challenges and opportunities

Impact of family income and sickle cell disease on the health-related quality of life of children