Hwee Lin Wee1,2, Khung Keong Yeo3,4, Kok Joon Chong5, Eric Yin Hao Khoo5,6, Yin Bun Cheung7,8. 1. Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore. 2. Saw Swee Hock School of Public Health, National University of Singapore, Singapore. 3. National Heart Centre Singapore, Singapore. 4. Duke-NUS Medical School, Singapore. 5. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 6. Division of Endocrinology, University Medicine Cluster, National University Hospital, Singapore. 7. Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore. 8. Tampere Center for Child Health Research, University of Tampere and Tampere University Hospital, Finland.
Abstract
BACKGROUND: Existing methods to link preference-based and profile-based health-related quality of life (HRQoL) questionnaires have their limitations. Hence, we developed a new mapping method (the mean rank method, MRM) and applied it to map the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF) to the EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L). We then compared the new MRM with current methods; i.e., regression-mapped (OLS method) and equipercentile method (EPM). METHODS: Singapore residents, aged ≥21 y, were recruited from the general population and 2 outpatient clinics in acute care hospitals. Performance of the MRM was evaluated using both simulation and split-sample validation ( n = 658 in training and n = 657 in validation samples). Using the training sample, we derived 3 sets of mapped EQ-5D-5L utilities based on MRM, OLS method and EPM. Using simulation and the validation sample, we compared the performance of the mapping methods in terms of distribution parameters, mean utility by strata, association with health covariates, and prediction errors at the individual level, among others. RESULTS: The WHOQOL-BREF Physical Health domain is the only domain significantly associated with EQ-5D-5L utilities. Simulation showed that MRM more accurately reproduced the variance and percentiles of the distribution of the observed utilities than did the OLS method or EPM. OLS method tended to underestimate the mean utility of good health states, overestimate the mean utility of poor health states, and underestimate the association with covariates. An analysis of validation sample gave similar results. CONCLUSION: In scenarios similar to the mapping of WHOQOL-BREF to the EQ-5D-5L, the MRM outperformed the OLS method and EPM in important-though not all-aspects. The simplicity and reproducibility of the MRM makes it an attractive alternative to current methods.
BACKGROUND: Existing methods to link preference-based and profile-based health-related quality of life (HRQoL) questionnaires have their limitations. Hence, we developed a new mapping method (the mean rank method, MRM) and applied it to map the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF) to the EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L). We then compared the new MRM with current methods; i.e., regression-mapped (OLS method) and equipercentile method (EPM). METHODS: Singapore residents, aged ≥21 y, were recruited from the general population and 2 outpatient clinics in acute care hospitals. Performance of the MRM was evaluated using both simulation and split-sample validation ( n = 658 in training and n = 657 in validation samples). Using the training sample, we derived 3 sets of mapped EQ-5D-5L utilities based on MRM, OLS method and EPM. Using simulation and the validation sample, we compared the performance of the mapping methods in terms of distribution parameters, mean utility by strata, association with health covariates, and prediction errors at the individual level, among others. RESULTS: The WHOQOL-BREF Physical Health domain is the only domain significantly associated with EQ-5D-5L utilities. Simulation showed that MRM more accurately reproduced the variance and percentiles of the distribution of the observed utilities than did the OLS method or EPM. OLS method tended to underestimate the mean utility of good health states, overestimate the mean utility of poor health states, and underestimate the association with covariates. An analysis of validation sample gave similar results. CONCLUSION: In scenarios similar to the mapping of WHOQOL-BREF to the EQ-5D-5L, the MRM outperformed the OLS method and EPM in important-though not all-aspects. The simplicity and reproducibility of the MRM makes it an attractive alternative to current methods.
Authors: Yin Bun Cheung; Hui Xing Tan; Vivian Wei Wang; Nagaendran Kandiah; Nan Luo; Gerald C H Koh; Hwee Lin Wee Journal: Qual Life Res Date: 2018-09-01 Impact factor: 4.147
Authors: Yuan Shi; Jennifer Thompson; A Sarah Walker; Nicholas I Paton; Yin Bun Cheung Journal: Health Qual Life Outcomes Date: 2019-05-10 Impact factor: 3.186
Authors: Stephan T Egger; Godehard Weniger; Mario Müller; Julio Bobes; Erich Seifritz; Stefan Vetter Journal: Health Qual Life Outcomes Date: 2019-11-19 Impact factor: 3.186