ABSTRACT
Objective
The purpose of this research was to create a function for mapping the cancer-specific instrument (FACT-G) to a preference-based measure (EQ-5D-3 L) utility index for health-related quality of life, with utility scores generated using the Chinese value set.
Method
A cross-sectional study among 243 Chinese patients with cancer was conducted through EQ-5D-3 L and FACT-G questionnaires survey. The EQ-5D-3 L utility index values were predicted based on OLS, GLM, CLAD, and Tobit model regression approaches. The performance and predictive power of each model were also evaluated using r2 and adj- r2, MAE, RMSE, ICC, and MID. Linear equating was used to avoid regression of the OLS model to mean. The model was validated using a 10-fold cross-validation method.
Results
Among all regression models for the FACT-G, the OLS 5 model predicted mean EQ-5D-3 L values the best, in terms of model goodness of fit (r2 = 0.6230, MAE = 0.0448, RMSE = 0.0624). The OLS model proved to be the most accurate for the mean, and the linear equating scores were much closer to the observed scores.
Conclusion
Our results suggest that the best algorithm for FACT-G mapping to EQ-5D-3 L utility index is OLS model, based on the survey of Chinese patients with cancer.
Acknowledgments
The authors sincerely thank all the members of the Cancer Screening Program in Urban China from the National Cancer Center of China, provinces, and external expert panels. We are also grateful to the participants for this study. This report was funded by the National Key Public Health Program of China (Cancer Screening Program in Urban China). The study protocol was approved by the Institutional Review Board of the Cancer Hospital of the Chinese Academy of Medical Sciences (Approval No. 15-071/998). All participants gave their [written] informed consent.
Author contributions
L Yang is in charge of the project. Z He drafted the manuscript. W Liang, W Xu, and W Huang conducted the data collection. L Yang, X Wang, and K Huang provided critical comments in revising the manuscript. All authors approved the final version of the manuscript for publication.
Data availability
The datasets used and/or analyzed during the current study are available.
Declaration of interest
The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14737167.2022.2091546