Skip to main content
Top
Gepubliceerd in: Quality of Life Research 1/2013

01-02-2013

Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes

Auteurs: Mangala Rajan, Kuan-Chi Lai, Chin-Lin Tseng, Shirley Qian, Alfredo Selim, Lewis Kazis, Leonard Pogach, Anushua Sinha

Gepubliceerd in: Quality of Life Research | Uitgave 1/2013

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail

Abstract

Purpose

Using transformations of existing quality-of-life data to estimate utilities has the potential to efficiently provide investigators with utility information. We used within-method and across-method comparisons and estimated disutilities associated with increasing chronic kidney disease (CKD) severity.

Methods

In an observational cohort of veterans with diabetes (DM) and pre-existing SF-36/SF-12 responses, we used six transformation methods (SF-12 to EQ-5D, SF-36 to HUI2, SF-12 to SF-6D, SF-36 to SF-6D, SF-36 to SF-6D (Bayesian method), and SF-12 to VR-6D) to estimate unadjusted utilities. CKD severity was staged using glomerular filtration rate estimated from serum creatinines, with the modification of diet in renal disease formula. We then used multivariate regression to estimate disutilities specifically associated with CKD severity stage.

Results

Of 67,963 patients, 22,273 patients had recent-onset DM and 45,690 patients had prevalent DM. For the recent-onset group, the adjusted disutility associated with CKD derived from the six transformation methods ranged from 0.0029 to 0.0045 for stage 2; −0.004 to −0.0009 for early stage 3; −0.017 to −0.010 for late stage 3; −0.023 to −0.012 for stage 4; −0.078 to −0.033 for stage 5; and −0.012 to −0.001 for ESRD/dialysis.

Conclusion

Disutility did not increase monotonically as CKD severity increased. Differences in disutilities estimated using the six different methods were found. Both findings have implications for using such estimates in economic analyses.
Bijlagen
Alleen toegankelijk voor geautoriseerde gebruikers
Literatuur
1.
go back to reference Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (1996). Cost-effectiveness in health and medicine. Oxford: Oxford University Press. Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (1996). Cost-effectiveness in health and medicine. Oxford: Oxford University Press.
2.
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(2), 271–292.PubMedCrossRef 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.PubMedCrossRef
3.
go back to reference 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.PubMedCrossRef 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.PubMedCrossRef
4.
go back to reference 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.PubMedCrossRef 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.PubMedCrossRef
5.
go back to reference Brazier, J. E., Yang, Y., Tsuchiya, A., & Rowen, D. L. (2010). A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. European Journal of Health Economics, 11(2), 215–225.PubMedCrossRef Brazier, J. E., Yang, Y., Tsuchiya, A., & Rowen, D. L. (2010). A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. European Journal of Health Economics, 11(2), 215–225.PubMedCrossRef
6.
go back to reference Mortimer, D., & Segal, L. (2008). Comparing the incomparable? A systematic review of competing techniques for converting descriptive measures of health status into QALY-weights. Medical Decision Making, 28(1), 66–89.PubMedCrossRef Mortimer, D., & Segal, L. (2008). Comparing the incomparable? A systematic review of competing techniques for converting descriptive measures of health status into QALY-weights. Medical Decision Making, 28(1), 66–89.PubMedCrossRef
7.
go back to reference Nichol, M. B., Sengupta, N., & Globe, D. R. (2001). Evaluating quality-adjusted life years: Estimation of the Health Utility Index (HUI2) from the SF-36. Medical Decision Making, 21(2), 105–112.PubMed Nichol, M. B., Sengupta, N., & Globe, D. R. (2001). Evaluating quality-adjusted life years: Estimation of the Health Utility Index (HUI2) from the SF-36. Medical Decision Making, 21(2), 105–112.PubMed
8.
go back to reference Sullivan, P. W., & Ghushchyan, V. (2006). Mapping the EQ-5D index from the SF-12: US general population preferences in a nationally representative sample. Medical Decision Making, 26(4), 401–409.PubMedCrossRef Sullivan, P. W., & Ghushchyan, V. (2006). Mapping the EQ-5D index from the SF-12: US general population preferences in a nationally representative sample. Medical Decision Making, 26(4), 401–409.PubMedCrossRef
9.
go back to reference Donald-Sherbourne, C., Unutzer, J., Schoenbaum, M., Duan, N., Lenert, L. A., Sturm, R., et al. (2001). Can utility-weighted health-related quality-of-life estimates capture health effects of quality improvement for depression? Medical Care, 39(11), 1246–1259.PubMedCrossRef Donald-Sherbourne, C., Unutzer, J., Schoenbaum, M., Duan, N., Lenert, L. A., Sturm, R., et al. (2001). Can utility-weighted health-related quality-of-life estimates capture health effects of quality improvement for depression? Medical Care, 39(11), 1246–1259.PubMedCrossRef
10.
go back to reference Glasziou, P., Alexander, J., Beller, E., & Clarke, P. (2007). Which health-related quality of life score? A comparison of alternative utility measures in patients with type 2 diabetes in the ADVANCE trial. Health Quality of Life Outcomes, 5, 21.CrossRef Glasziou, P., Alexander, J., Beller, E., & Clarke, P. (2007). Which health-related quality of life score? A comparison of alternative utility measures in patients with type 2 diabetes in the ADVANCE trial. Health Quality of Life Outcomes, 5, 21.CrossRef
11.
go back to reference Hollingworth, W., Deyo, R. A., Sullivan, S. D., Emerson, S. S., Gray, D. T., & Jarvik, J. G. (2002). The practicality and validity of directly elicited and SF-36 derived health state preferences in patients with low back pain. Health Economics, 11(1), 71–85.PubMedCrossRef Hollingworth, W., Deyo, R. A., Sullivan, S. D., Emerson, S. S., Gray, D. T., & Jarvik, J. G. (2002). The practicality and validity of directly elicited and SF-36 derived health state preferences in patients with low back pain. Health Economics, 11(1), 71–85.PubMedCrossRef
12.
go back to reference Kaplan, R. M., Groessl, E. J., Sengupta, N., Sieber, W. J., & Ganiats, T. G. (2005). Comparison of measured utility scores and imputed scores from the SF-36 in patients with rheumatoid arthritis. Medical Care, 43(1), 79–87.PubMed Kaplan, R. M., Groessl, E. J., Sengupta, N., Sieber, W. J., & Ganiats, T. G. (2005). Comparison of measured utility scores and imputed scores from the SF-36 in patients with rheumatoid arthritis. Medical Care, 43(1), 79–87.PubMed
13.
go back to reference Lobo, F. S., Gross, C. R., & Matthees, B. J. (2004). Estimation and comparison of derived preference scores from the SF-36 in lung transplant patients. Quality of Life Research, 13(2), 377–388.PubMedCrossRef Lobo, F. S., Gross, C. R., & Matthees, B. J. (2004). Estimation and comparison of derived preference scores from the SF-36 in lung transplant patients. Quality of Life Research, 13(2), 377–388.PubMedCrossRef
14.
go back to reference 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.PubMedCrossRef 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.PubMedCrossRef
15.
go back to reference Pickard, A. S., Wang, Z., Walton, S. M., & Lee, T. A. (2005). Are decisions using cost-utility analyses robust to choice of SF-36/SF-12 preference-based algorithm? Health Quality of Life Outcomes, 3, 11.CrossRef Pickard, A. S., Wang, Z., Walton, S. M., & Lee, T. A. (2005). Are decisions using cost-utility analyses robust to choice of SF-36/SF-12 preference-based algorithm? Health Quality of Life Outcomes, 3, 11.CrossRef
17.
go back to reference Kharroubi, S. A., Brazier, J. E., Roberts, J., & O’Hagan, A. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics, 26(3), 597–612.PubMedCrossRef Kharroubi, S. A., Brazier, J. E., Roberts, J., & O’Hagan, A. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics, 26(3), 597–612.PubMedCrossRef
18.
go back to reference Selim, A. J., Rogers, W., Qian, S. X., Brazier, J., & Kazis, L. E. (2011). A preference-based measure of health: The VR-6D derived from the veterans RAND 12-item health survey. Quality of Life Research, 20(8),1337–1347. Selim, A. J., Rogers, W., Qian, S. X., Brazier, J., & Kazis, L. E. (2011). A preference-based measure of health: The VR-6D derived from the veterans RAND 12-item health survey. Quality of Life Research, 20(8),1337–1347.
19.
go back to reference Boyle, J. P., Thompson, T. J., Gregg, E. W., Barker, L. E., & Williamson, D. F. (2010). Projection of the year 2050 burden of diabetes in the US adult population: Dynamic modeling of incidence, mortality, and prediabetes prevalence. Population Health Metrics, 8, 29.PubMedCrossRef Boyle, J. P., Thompson, T. J., Gregg, E. W., Barker, L. E., & Williamson, D. F. (2010). Projection of the year 2050 burden of diabetes in the US adult population: Dynamic modeling of incidence, mortality, and prediabetes prevalence. Population Health Metrics, 8, 29.PubMedCrossRef
20.
go back to reference US Renal Data System. (2010). USRDS 2010 annual data report: Atlas of chronic kidney disease and end-stage renal disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2010. US Renal Data System. (2010). USRDS 2010 annual data report: Atlas of chronic kidney disease and end-stage renal disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2010.
21.
go back to reference Kazis, L. E., Ren, X. S., Lee, A., Skinner, K., Rogers, W., Clarke, J., et al. (1999). Health status in VA patients: Results from the Veterans Health Study. American Journal of Medical Quality, 14(1), 28–38.PubMedCrossRef Kazis, L. E., Ren, X. S., Lee, A., Skinner, K., Rogers, W., Clarke, J., et al. (1999). Health status in VA patients: Results from the Veterans Health Study. American Journal of Medical Quality, 14(1), 28–38.PubMedCrossRef
22.
go back to reference Miller, D. R., & Pogach, L. (2008). Longitudinal approaches to evaluate health care quality and outcomes: The Veterans Health Administration diabetes epidemiology cohorts. Journal of Diabetes Science Technology, 2(1), 24–32. Miller, D. R., & Pogach, L. (2008). Longitudinal approaches to evaluate health care quality and outcomes: The Veterans Health Administration diabetes epidemiology cohorts. Journal of Diabetes Science Technology, 2(1), 24–32.
23.
go back to reference Miller, D. R., Safford, M. M., & Pogach, L. M. (2004). Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data. Diabetes Care, 27(Suppl 2), b10–b21.PubMedCrossRef Miller, D. R., Safford, M. M., & Pogach, L. M. (2004). Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data. Diabetes Care, 27(Suppl 2), b10–b21.PubMedCrossRef
24.
go back to reference Damschroder, L. J., Zikmund-Fisher, B. J., & Ubel, P. A. (2008). Considering adaptation in preference elicitations. Health Psychology, 27(3), 394–399.PubMedCrossRef Damschroder, L. J., Zikmund-Fisher, B. J., & Ubel, P. A. (2008). Considering adaptation in preference elicitations. Health Psychology, 27(3), 394–399.PubMedCrossRef
25.
go back to reference Kostopoulou, O. (2006). The transient nature of utilities and health preferences. Medical Decision Making, 26(4), 304–306.PubMedCrossRef Kostopoulou, O. (2006). The transient nature of utilities and health preferences. Medical Decision Making, 26(4), 304–306.PubMedCrossRef
26.
go back to reference Menzel, P., Dolan, P., Richardson, J., & Olsen, J. A. (2002). The role of adaptation to disability and disease in health state valuation: A preliminary normative analysis. Social Science and Medicine, 55(12), 2149–2158.PubMedCrossRef Menzel, P., Dolan, P., Richardson, J., & Olsen, J. A. (2002). The role of adaptation to disability and disease in health state valuation: A preliminary normative analysis. Social Science and Medicine, 55(12), 2149–2158.PubMedCrossRef
27.
go back to reference Dolan, P. (1996). Modelling valuations for health states: The effect of duration. Health Policy, 38(3), 189–203.PubMedCrossRef Dolan, P. (1996). Modelling valuations for health states: The effect of duration. Health Policy, 38(3), 189–203.PubMedCrossRef
28.
go back to reference Kazis, L. E., Miller, D. R., Clark, J. A., Skinner, K. M., Lee, A., Ren, X. S., et al. (2004). Improving the response choices on the veterans SF-36 health survey role functioning scales: Results from the Veterans Health Study. The Journal of Ambulatory Care Management, 27(3), 263–280.PubMed Kazis, L. E., Miller, D. R., Clark, J. A., Skinner, K. M., Lee, A., Ren, X. S., et al. (2004). Improving the response choices on the veterans SF-36 health survey role functioning scales: Results from the Veterans Health Study. The Journal of Ambulatory Care Management, 27(3), 263–280.PubMed
29.
go back to reference Kazis, L. E., Miller, D. R., Skinner, K. M., Lee, A., Ren, X. S., Clark, J. A., et al. (2004). Patient-reported measures of health: The Veterans Health Study. The Journal of Ambulatory Care Management, 27(1), 70–83.PubMed Kazis, L. E., Miller, D. R., Skinner, K. M., Lee, A., Ren, X. S., Clark, J. A., et al. (2004). Patient-reported measures of health: The Veterans Health Study. The Journal of Ambulatory Care Management, 27(1), 70–83.PubMed
30.
go back to reference Tiwari, A., Tseng, C. L., Kern, E. F., Maney, M., Miller, D. R., & Pogach, L. (2007). Facility variation in utilization of angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers in patients with diabetes mellitus and chronic kidney disease. The American Journal of Managed Care, 13(2), 73–79.PubMed Tiwari, A., Tseng, C. L., Kern, E. F., Maney, M., Miller, D. R., & Pogach, L. (2007). Facility variation in utilization of angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers in patients with diabetes mellitus and chronic kidney disease. The American Journal of Managed Care, 13(2), 73–79.PubMed
31.
go back to reference Miller, W. G. (2009). Estimating glomerular filtration rate. Clinical Chemistry and Laboratory Medicine, 47(9), 1017–1019.PubMedCrossRef Miller, W. G. (2009). Estimating glomerular filtration rate. Clinical Chemistry and Laboratory Medicine, 47(9), 1017–1019.PubMedCrossRef
32.
go back to reference Levey, A. S., Coresh, J., Balk, E., Kausz, A. T., Levin, A., Steffes, M. W., et al. (2003). National Kidney Foundation practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Annals of Internal Medicine, 139(2), 137–147.PubMed Levey, A. S., Coresh, J., Balk, E., Kausz, A. T., Levin, A., Steffes, M. W., et al. (2003). National Kidney Foundation practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Annals of Internal Medicine, 139(2), 137–147.PubMed
33.
go back to reference Tseng, C. L., Kern, E. F., Miller, D. R., Tiwari, A., Maney, M., Rajan, M., et al. (2008). Survival benefit of nephrologic care in patients with diabetes mellitus and chronic kidney disease. Archives of Internal Medicine, 168(1), 55–62.PubMedCrossRef Tseng, C. L., Kern, E. F., Miller, D. R., Tiwari, A., Maney, M., Rajan, M., et al. (2008). Survival benefit of nephrologic care in patients with diabetes mellitus and chronic kidney disease. Archives of Internal Medicine, 168(1), 55–62.PubMedCrossRef
34.
go back to reference Khanna, D., Ahmed, M., Yontz, D., Ginsburg, S. S., Park, G. S., Leonard, A., et al. (2008). The disutility of chronic gout. Quality of Life Research, 17(5), 815–822.PubMedCrossRef Khanna, D., Ahmed, M., Yontz, D., Ginsburg, S. S., Park, G. S., Leonard, A., et al. (2008). The disutility of chronic gout. Quality of Life Research, 17(5), 815–822.PubMedCrossRef
35.
go back to reference 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.PubMedCrossRef 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.PubMedCrossRef
36.
go back to reference Green, C., Brazier, J., & Deverill, M. (2000). Valuing health-related quality of life. A review of health state valuation techniques. Pharmacoeconomics, 17(2), 151–165.PubMedCrossRef Green, C., Brazier, J., & Deverill, M. (2000). Valuing health-related quality of life. A review of health state valuation techniques. Pharmacoeconomics, 17(2), 151–165.PubMedCrossRef
37.
go back to reference Tsuchiya, A., Brazier, J., & Roberts, J. (2006). Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets. Journal of Health Economics, 25(2), 334–346.PubMedCrossRef Tsuchiya, A., Brazier, J., & Roberts, J. (2006). Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets. Journal of Health Economics, 25(2), 334–346.PubMedCrossRef
38.
go back to reference Kontodimopoulos, N., Pappa, E., Papadopoulos, A. A., Tountas, Y., & Niakas, D. (2009). Comparing SF-6D and EQ-5D utilities across groups differing in health status. Quality of Life Research, 18(1), 87–97.PubMedCrossRef Kontodimopoulos, N., Pappa, E., Papadopoulos, A. A., Tountas, Y., & Niakas, D. (2009). Comparing SF-6D and EQ-5D utilities across groups differing in health status. Quality of Life Research, 18(1), 87–97.PubMedCrossRef
39.
go back to reference Dale, P. L., Hutton, J., & Elgazzar, H. (2008). Utility of health states in chronic kidney disease: A structured review of the literature. Current Medical Research and Opinion, 24(1), 193–206.PubMedCrossRef Dale, P. L., Hutton, J., & Elgazzar, H. (2008). Utility of health states in chronic kidney disease: A structured review of the literature. Current Medical Research and Opinion, 24(1), 193–206.PubMedCrossRef
40.
go back to reference Gorodetskaya, I., Zenios, S., McCulloch, C. E., Bostrom, A., Hsu, C. Y., Bindman, A. B., et al. (2005). Health-related quality of life and estimates of utility in chronic kidney disease. Kidney International, 68(6), 2801–2808.PubMedCrossRef Gorodetskaya, I., Zenios, S., McCulloch, C. E., Bostrom, A., Hsu, C. Y., Bindman, A. B., et al. (2005). Health-related quality of life and estimates of utility in chronic kidney disease. Kidney International, 68(6), 2801–2808.PubMedCrossRef
41.
go back to reference Davison, S. N., Jhangri, G. S., & Feeny, D. H. (2009). Comparing the Health Utilities Index Mark 3 (HUI3) with the Short Form-36 preference-based SF-6D in chronic kidney disease. Value Health, 12(2), 340–345.PubMedCrossRef Davison, S. N., Jhangri, G. S., & Feeny, D. H. (2009). Comparing the Health Utilities Index Mark 3 (HUI3) with the Short Form-36 preference-based SF-6D in chronic kidney disease. Value Health, 12(2), 340–345.PubMedCrossRef
42.
go back to reference Chapman, B. P., Franks, P., Duberstein, P. R., & Jerant, A. (2009). Differences between individual and societal health state valuations: Any link with personality? Medical Care, 47(8), 902–907.PubMedCrossRef Chapman, B. P., Franks, P., Duberstein, P. R., & Jerant, A. (2009). Differences between individual and societal health state valuations: Any link with personality? Medical Care, 47(8), 902–907.PubMedCrossRef
43.
go back to reference Mann, R., Brazier, J., & Tsuchiya, A. (2009). A comparison of patient and general population weightings of EQ-5D dimensions. Health Economics, 18(3), 363–372.PubMedCrossRef Mann, R., Brazier, J., & Tsuchiya, A. (2009). A comparison of patient and general population weightings of EQ-5D dimensions. Health Economics, 18(3), 363–372.PubMedCrossRef
44.
go back to reference Ara, R., & Brazier, J. (2008). Deriving an algorithm to convert the eight mean SF-36 dimension scores into a mean EQ-5D preference-based score from published studies (where patient level data are not available). Value Health, 11(7), 1131–1143.PubMedCrossRef Ara, R., & Brazier, J. (2008). Deriving an algorithm to convert the eight mean SF-36 dimension scores into a mean EQ-5D preference-based score from published studies (where patient level data are not available). Value Health, 11(7), 1131–1143.PubMedCrossRef
45.
go back to reference Franks, P., Lubetkin, E. I., Gold, M. R., & Tancredi, D. J. (2003). Mapping the SF-12 to preference-based instruments: Convergent validity in a low-income, minority population. Medical Care, 41(11), 1277–1283.PubMedCrossRef Franks, P., Lubetkin, E. I., Gold, M. R., & Tancredi, D. J. (2003). Mapping the SF-12 to preference-based instruments: Convergent validity in a low-income, minority population. Medical Care, 41(11), 1277–1283.PubMedCrossRef
46.
go back to reference Franks, P., Lubetkin, E. I., Gold, M. R., Tancredi, D. J., & Jia, H. (2004). Mapping the SF-12 to the EuroQol EQ-5D index in a national US sample. Medical Decision Making, 24(3), 247–254.PubMedCrossRef Franks, P., Lubetkin, E. I., Gold, M. R., Tancredi, D. J., & Jia, H. (2004). Mapping the SF-12 to the EuroQol EQ-5D index in a national US sample. Medical Decision Making, 24(3), 247–254.PubMedCrossRef
47.
go back to reference Fryback, D. G., Lawrence, W. F., Martin, P. A., Klein, R., & Klein, B. E. (1997). Predicting Quality of Well-being scores from the SF-36: Results from the Beaver Dam Health Outcomes Study. Medical Decision Making, 17(1), 1–9.PubMedCrossRef Fryback, D. G., Lawrence, W. F., Martin, P. A., Klein, R., & Klein, B. E. (1997). Predicting Quality of Well-being scores from the SF-36: Results from the Beaver Dam Health Outcomes Study. Medical Decision Making, 17(1), 1–9.PubMedCrossRef
48.
go back to reference Gray, A. M., Rivero-Arias, O., & Clarke, P. M. (2006). Estimating the association between SF-12 responses and EQ-5D utility values by response mapping. Medical Decision Making, 26(1), 18–29.PubMedCrossRef Gray, A. M., Rivero-Arias, O., & Clarke, P. M. (2006). Estimating the association between SF-12 responses and EQ-5D utility values by response mapping. Medical Decision Making, 26(1), 18–29.PubMedCrossRef
49.
go back to reference Hawthorne, G., Densley, K., Pallant, J. F., Mortimer, D., & Segal, L. (2008). Deriving utility scores from the SF-36 health instrument using Rasch analysis. Quality of Life Research, 17(9), 1183–1193.PubMedCrossRef Hawthorne, G., Densley, K., Pallant, J. F., Mortimer, D., & Segal, L. (2008). Deriving utility scores from the SF-36 health instrument using Rasch analysis. Quality of Life Research, 17(9), 1183–1193.PubMedCrossRef
50.
go back to reference Lawrence, W. F., & Fleishman, J. A. (2004). Predicting EuroQoL EQ-5D preference scores from the SF-12 health survey in a nationally representative sample. Medical Decision Making, 24(2), 160–169.PubMedCrossRef Lawrence, W. F., & Fleishman, J. A. (2004). Predicting EuroQoL EQ-5D preference scores from the SF-12 health survey in a nationally representative sample. Medical Decision Making, 24(2), 160–169.PubMedCrossRef
51.
go back to reference Le, Q. A., & Doctor, J. N. (2011). Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: An empirical analysis converting SF-12 into EQ-5D utility index in a national US sample. Medical Care, 49(5), 451–460.PubMedCrossRef Le, Q. A., & Doctor, J. N. (2011). Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: An empirical analysis converting SF-12 into EQ-5D utility index in a national US sample. Medical Care, 49(5), 451–460.PubMedCrossRef
52.
go back to reference Lundberg, L., Johannesson, M., Isacson, D. G., & Borgquist, L. (1999). The relationship between health-state utilities and the SF-12 in a general population. Medical Decision Making, 19(2), 128–140.PubMedCrossRef Lundberg, L., Johannesson, M., Isacson, D. G., & Borgquist, L. (1999). The relationship between health-state utilities and the SF-12 in a general population. Medical Decision Making, 19(2), 128–140.PubMedCrossRef
53.
go back to reference Rowen, D., Brazier, J., & Roberts, J. (2009). Mapping SF-36 onto the EQ-5D index: How reliable is the relationship? Health Quality of Life Outcomes, 7, 27.CrossRef Rowen, D., Brazier, J., & Roberts, J. (2009). Mapping SF-36 onto the EQ-5D index: How reliable is the relationship? Health Quality of Life Outcomes, 7, 27.CrossRef
54.
go back to reference Sengupta, N., Nichol, M. B., Wu, J., & Globe, D. (2004). Mapping the SF-12 to the HUI3 and VAS in a managed care population. Medical Care, 42(9), 927–937.PubMedCrossRef Sengupta, N., Nichol, M. B., Wu, J., & Globe, D. (2004). Mapping the SF-12 to the HUI3 and VAS in a managed care population. Medical Care, 42(9), 927–937.PubMedCrossRef
55.
go back to reference Ferreira, L. N., Ferreira, P. L., Pereira, L. N., Brazier, J., & Rowen, D. (2010). A Portuguese value set for the SF-6D. Value Health, 13(5), 624–630.PubMedCrossRef Ferreira, L. N., Ferreira, P. L., Pereira, L. N., Brazier, J., & Rowen, D. (2010). A Portuguese value set for the SF-6D. Value Health, 13(5), 624–630.PubMedCrossRef
56.
go back to reference 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.PubMedCrossRef 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.PubMedCrossRef
57.
go back to reference Arnold, D., Girling, A., Stevens, A., & Lilford, R. (2009). Comparison of direct and indirect methods of estimating health state utilities for resource allocation: Review and empirical analysis. British Medical Journal, 339, b2688. Arnold, D., Girling, A., Stevens, A., & Lilford, R. (2009). Comparison of direct and indirect methods of estimating health state utilities for resource allocation: Review and empirical analysis. British Medical Journal, 339, b2688.
58.
go back to reference Schmidlin, M., Fritsch, K., Matthews, F., Thurnheer, R., Senn, O., & Bloch, K. E. (2010). Utility indices in patients with the obstructive sleep apnea syndrome. Respiration, 79(3), 200–208.PubMedCrossRef Schmidlin, M., Fritsch, K., Matthews, F., Thurnheer, R., Senn, O., & Bloch, K. E. (2010). Utility indices in patients with the obstructive sleep apnea syndrome. Respiration, 79(3), 200–208.PubMedCrossRef
Metagegevens
Titel
Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes
Auteurs
Mangala Rajan
Kuan-Chi Lai
Chin-Lin Tseng
Shirley Qian
Alfredo Selim
Lewis Kazis
Leonard Pogach
Anushua Sinha
Publicatiedatum
01-02-2013
Uitgeverij
Springer Netherlands
Gepubliceerd in
Quality of Life Research / Uitgave 1/2013
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-012-0139-1

Andere artikelen Uitgave 1/2013

Quality of Life Research 1/2013 Naar de uitgave