Swipe om te navigeren naar een ander artikel
The online version of this article (https://doi.org/10.1007/s11136-018-1991-4) contains supplementary material, which is available to authorized users.
To map the Alzheimer’s Disease Cooperative Study—Activities of Daily Living Inventory (ADCS-ADL) to the Health Utility Index Mark III (HUI3) in people living with dementia (PWD) and to compare the performance of five methods for mapping.
A cross-sectional study of 346 dyads of community-dwelling PWD and family caregiver was carried out in Singapore. ADCS-ADL and HUI3 were rated by the family caregivers. Disease severity ratings and Mini Mental State Examination (MMSE) results were retrieved from medical records. A recently proposed mapping method called the Mean Rank Method (MRM) was described and applied, and the results were compared with regression-based mapping, including ordinary least squares, censored least absolute deviation (CLAD), Tobit and response mapping.
The MRM produced a mapped utility distribution that closely resembled the observed utility distribution. The standard deviations (SDs) of the observed and MRM-mapped utility were both 0.340, whereas the SDs of the other mapped utilities ranged from 0.243 (response mapping) to 0.283 (CLAD). Regressing the MRM- and CLAD-mapped and observed utility values upon disease severity and MMSE gave similar regression lines (each P > 0.05). Regressing the other mapped utility values upon the covariates under- (over-) estimated the utility of good (poor) clinical states. However, regression-based mapping methods gave a better fit at the individual level, as measured by root mean square error, mean absolute error and R2. K fold cross-validation gave similar results.
The MRM is accurate at the group level. The regression-based mapping methods are more accurate for making individual-level prediction. In addition, CLAD also performed reasonably well at the group level.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Drummond, M. F., Sculpher, M. J., Claxton, K., et al. (2015). Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press.
Whitehead, S. J., & Ali, S. (2010). Health outcomes in economic evaluation: The QALY and utilities. British Medical Bulletin, 96, 5–21. CrossRef
Herdman, M., Gudex, C., Lloyd, A., 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. CrossRef
Horsman, J., Furlong, W., Feeny, D., et al. (2003). The Health Utilities Index (HUI): Concepts, measurement properties and applications. Health and Quality of Life Outcomes, 1, 54. CrossRef
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. CrossRef
Longworth, L., Yang, Y., Young, T., et al. (2014). Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic review, statistical modelling and survey. Health Technology Assessment. https://doi.org/10.3310/hta18090.
Fayers, P. M., & Hays, R. D. (2014). Should linking replace regression when mapping from profile-based measures to preference-based measures? Value in Health, 17(2), 261–265. CrossRef
Fayers, P. M., & Machin, D. (2016). Quality of life: The assessment, analysis and reporting of patient-reported outcomes (3rd ed.). Oxford: Wiley.
Whately-Smith, C., Watkins, C., Mann, H., Fletcher, C., & Ducournau, P. (2014). Utility values in health technology assessments: A statistician’s perspective. Pharmaceutical Statistics, 13(3), 184–195. CrossRef
Crott, R. (2014). Mapping algorithms from QLQ-C30 to EQ-5D utilities: No firm ground to stand on yet. Expert Review of Pharmacoeconomics and Outcomes Research, 14(4), 569–576. CrossRef
National Institute for Health and Care Excellence. (2013). Guide to the methods of technology appraisal. London: National Institute for Health and Care Excellence.
Longworth, L., & Rowen, D. (2013). Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value in Health, 16(1), 202–210. CrossRef
Brazier, J., 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, 215–225. CrossRef
Dakin, H. (2013). Review of studies mapping from quality of life or clinical measures to EQ-5D: An online database. Health and Quality of Life Outcomes, 11, 151. CrossRef
Singapore Ministry of Health. (2016). ElderShield fast facts. Singapore: Ministry of Health. http://www.eldershield.sg.
Galasko, D., Bennett, D., Sano, M., et al. (1997). An inventory to assess activities of daily living for clinical trials in Alzheimer’s disease. The Alzheimer’s Disease Cooperative Study. Alzheimer Disease and Associated Disorders, 11(Suppl. 2), S33–S39. CrossRef
Robert, P., Ferris, S., Gauthier, S., et al. (2010). Review of Alzheimer’s disease scales: Is there a need for a new multi-domain scale for therapy evaluation in medical practice? Alzheimer’s Research and Therapy, 26(2), 24. CrossRef
Wee, H. L., Yeo, K. K., Chong, K. J., Khoo, E. Y. H., & Cheung, Y. B. (2018). Mean rank, equipercentile and regression mapping of World Health Organization Quality of Life Brief (WHOQOL-BREF) to EuroQoL 5 Dimensions 5 Levels (EQ-5D–5L) utilities. Medical Decision Making, 38(3), 319–333. CrossRef
Cheung, Y. B., Thumboo, J., Gao, F., et al. (2009). Mapping the English and Chinese versions of the Functional Assessment of Cancer Therapy-General to the EQ-5D utility index. Value in Health, 12(2), 371–376. CrossRef
Cheung, Y. B., Luo, N., Ng, R., & Lee, C. F. (2014). Mapping the Functional Assessment of Cancer Therapy-Breast (FACT-B) to the 5-level EuroQoL Group’s 5-dimension questionnaire (EQ-5D–5L) utility index in a Multi-ethnic Asian Population. Health and Quality of Life Outcomes, 12, 180. CrossRef
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. CrossRef
Huang, I. C., Frangakis, C., Atkinson, M. J., et al. (2008). Addressing ceiling effects in health status measures: A comparison of techniques applied to measures for people with HIV disease. Health Services Research, 43, 327–339. CrossRef
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. CrossRef
Dorans, N. J. (2007). Linking scores from multiple health outcome instruments. Quality of Life Research, 16(Suppl. 1), 85–94. CrossRef
Holland, P. W., & Thayer, D. T. (1989). The kernel method of equating score distributions. Washington, DC: Educational Testing Service. CrossRef
Chan, A., Ostbye, T., Malhotra, R., & Hu, A. J. (2012). The survey on informal caregiving: The summary report for MCYS. Retrieved June 1, 2013, from https://app.msf.gov.sg/Portals/0/Informal%20Caregiver%20Survey%20Summary%20Report%20(upload).pdf.
Contador, I., Fernandez-Calvo, B., Palenzuela, D. L., Migueis, S., & Ramos, F. (2012). Prediction of burden in family caregivers of patients with dementia: A perspective of optimism based on generalized expectancies of control. Aging and Mental Health, 16(6), 675–682. CrossRef
Haro, J. M., Kahle-Wrobleski, K., Bruno, G., et al. (2014). Analysis of burden in caregivers of people with Alzheimer’s disease using self-report and supervision hours. Journal of Nutrition, Health and Aging, 18(7), 677–684. CrossRef
Reed, C., Belger, M., Dell’agnello, G., et al. (2014). Caregiver burden in Alzheimer’s disease: Differential associations in adult–child and spousal caregivers in the GERAS observational study. Dementia and Geriatric Cognitive Disorders Extra, 4(1), 51–64. CrossRef
Bhattacharya, S., Vogel, A., Hansen, M. L., et al. (2010). Generic and disease-specific measures of quality of life in patients with mild Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders Extra, 30, 327–333. CrossRef
Coucill, W., Bryan, S., Bentham, P., Buckley, A., & Laight, A. (2001). EQ-5D in patients with dementia: An investigation of inter-rater agreement. Medical Care, 39(8), 760–771. CrossRef
Karlawish, J. H., Zbrozek, A., Kinosian, B., Gregory, A., Ferguson, A., & Glick, H. A. (2008). Preference-based quality of life in patients with Alzheimer’s disease. Alzheimer’s and Dementia, 4(3), 193–202. CrossRef
Wang, W. (2016). Economic and health related quality of life outcomes among community-dwelling dementia patients in Singapore. PhD Dissertation, National University of Singapore, Singapore.
Feeny, D., Furlong, W., Torrance, G. W., et al. (2002). Multiattribute and single-attribute utility functions for the Health Utilities Index Mark 3 system. Medical Care, 40(2), 113–128. CrossRef
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 1975, 12(3), 189–198. CrossRef
Feng, L., Chong, M. S., Lim, W. S., & Ng, T. P. The Modified Mini-Mental State Examination test: Normative data for Singapore Chinese older adults and its performance in detecting early cognitive impairment. Singapore Medical Journal, 53(7), 458–462.
Morris, J. C. (1993). The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology, 43(11), 2412–2414. CrossRef
Royston, P., & Altman, D. G. (1994). Regression using fractional polynomials of continuous covariates: Parsimonious parametric modeling (with discussion). Applied Statistics, 43, 429–467. CrossRef
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning, with applications in R. New York: Springer. CrossRef
Greene, W. H. (2012). Econometric analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
Lee, C. F., Ng, R., Luo, N., & Cheung, Y. B. (2018) Development of conversion functions mapping the FACT-B total score to the EQ-5D–5L utility value by three linking methods and comparison with the ordinary least square method. Applied Health Economics and Health Policy. https://doi.org/10.1007/s40258-018-0404-8 (E-pub ahead of print).
- Mapping the Alzheimer’s Disease Cooperative Study-Activities of Daily Living Inventory to the Health Utility Index Mark III
Yin Bun Cheung
Hui Xing Tan
Vivian Wei Wang
Gerald C. H. Koh
Hwee Lin Wee
- Springer International Publishing