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.
Keywords: EQ-5D-3L; FACT-G; Health-related quality of life; Mapping; cancer; health utility.