Mapping the FACT-G to EQ-5D-3L utility index in cancer: data from a cross-sectional study in in Guangxi, China

ObjectiveThis study aimed to develop a function for mapping the cancer-specific instrument (FACT–G) to a preference-based measure (EQ-5D-3L) utility index for HRQoL, in which the utility scores were generated using the Chinese value set.MethodThe data are based on a cross-sectional survey of 243 patients in China with different cancer types. Cancer patients who completed the EQ-5D-3L and the FACT-G questionnaire, and patient demographics and clinical characteristics were included in this study. Regression models were used to predict the EQ-5D-3L utility index values based on four subscale scores of the FACT-G using the ordinary least squares (OLS) model, generalized linear models (GLM), censored least absolute deviations (CLAD), Tobit model, and two-part model (TPM) regression approaches. The performance and predictive power of each model were also evaluated using r2 and adj- r2, mean absolute error (MAE) and root mean squared error (RMSE). Linear equating is a mapping technique that avoids regression to the mean.ResultsThe introduction of the square term and the interaction term improves the accuracy of the model. The social well-being subscale of the FACT-G was not associated with the EQ-5D-3L utility index, whereas, the physical, emotional, functional well-being, and FACT-G total scores were derived when mapping the FACT-G to the EQ-5D-3L utility index. For the FACT-G, the OLS model was the best at predicting mean EQ-5D-3L values among all the regression models and has 70% explanatory power for the observed EQ-5D-3L variation. Nevertheless, the OLS model overpredicted utilities for poorer health states and underestimated utilities for those with better health. The result of the OLS model, GLM, and CLAD models were similar to the MAE, MSE, and RMSE. The results showed that the mean prediction accuracy of the OLS models was higher than that of the other models, and the OLS model's linear equating predicted values were much closer to the observed values.ConclusionThe algorithm based on Chinese population development for mapping the FACT-G into the EQ-5D-3L utility index can be realized. We also recommend that OLS models be used to assess the economic evaluation of patients' health-related quality of life when the population is in moderate to good health for further cost-utility analysis in China.