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Mapping the Chinese Version of the EORTC QLQ-BR53 Onto the EQ-5D-5L and SF-6D Utility Scores

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Abstract

Objective

This study aimed to develop mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-BR53, including EORTC QLQ-C30 and QLQ-BR23) onto the 5-level EQ-5D (EQ-5D-5L) and Short Form 6D (SF-6D) utility scores.

Methods

The data were taken from 607 breast cancer patients in mainland China. The EQ-5D-5L and SF-6D instruments were scored using Chinese-specific tariffs. Three model specifications and seven statistical techniques were used to derive mapping algorithms, including ordinary least squares (OLS), Tobit, censored least absolute deviation (CLAD) model, generalized linear model (GLM), robust MM-estimator, finite mixtures of beta regression model for directly estimating health utility, and using ordered logit regression (OLOGIT) to predict response levels. A five-fold cross-validation approach was conducted to test the generalizability of each model. Two key goodness-of-fit statistics (mean absolute error and mean squared error) and three secondary statistics were employed to choose the optimal models.

Results

Participants had a mean ± standard deviation (SD) age of 49.0 ± 9.8 years. The mean ± SD health state utility scores were 0.828 ± 0.184 (EQ-5D-5L) and 0.646 ± 0.125 (SF-6D). Mapping performance was better when both the QLQ-C30 and QLQ-BR23 dimensions were considered rather than when either of these dimensions were used alone. The mapping functions from the optimal direct mapping and indirect mapping approaches were reported.

Conclusions

The algorithms reported in this paper enable EORTC QLQ-BR53 breast cancer data to be mapped into utilities predicted from the EQ-5D-5L and SF-6D. The algorithms allow for the calculation of quality-adjusted life years for use in breast cancer cost-effectiveness analyses studies.

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Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors thank all participants for their time and effort.

Author information

Authors and Affiliations

  1. School of Health Care Management, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China

    Tong Liu, Shunping Li & Qiang Sun

  2. NHC Key Laboratory of Health Economics and Policy Research (Shandong University), Jinan, 250012, China

    Tong Liu, Shunping Li & Qiang Sun

  3. Qingdao Municipal Hospital, Qingdao, 266011, China

    Min Wang

  4. Flinders Centre for Innovation in Cancer, Flinders University, Adelaide, SA, 5042, Australia

    Gang Chen

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  1. Tong Liu
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Contributions

SL and QS conceived and designed this study; MW participated in the acquisition of the data; TL analyzed the data, interpreted the results and wrote the first draft of the manuscript; and GC supervised the statistical analsyis, gave feedback on the manuscript and revised it critically for important intellectual content. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to Shunping Li.

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Funding

Financial support was received from Shandong Provincial Natural Science Foundation, China (ZR2013GM023).

Conflict of interest

Tong Liu, Shunping Li, Min Wang, Qiang Sun, and Gang Chen declare no conflicts of interest.

Ethical approval

Ethical approval (reference no. 20131002) was obtained from the Ethics Review Board of the School of Public Health, Shandong University. This research adhered to the tenets of the Declaration of Helsinki.

Informed consent

Informed consent was obtained from all individual participants included in the studies.

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Liu, T., Li, S., Wang, M. et al. Mapping the Chinese Version of the EORTC QLQ-BR53 Onto the EQ-5D-5L and SF-6D Utility Scores. Patient 13, 537–555 (2020). https://doi.org/10.1007/s40271-020-00422-x

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