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01-09-2018 | Uitgave 1/2019

Quality of Life Research 1/2019

Mapping the Alzheimer’s Disease Cooperative Study-Activities of Daily Living Inventory to the Health Utility Index Mark III

Quality of Life Research > Uitgave 1/2019
Yin Bun Cheung, Hui Xing Tan, Vivian Wei Wang, Nagaendran Kandiah, Nan Luo, Gerald C. H. Koh, Hwee Lin Wee
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Electronic supplementary material

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.

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