Health variations among breast-cancer patients from different disease states: Evidence from China

Abstract

Background To obtain health utility data for different disease status of breast cancer in China in order to obtain important parameters in health economics modeling. To explore the feasibility of establishing a breast cancer health utility mapping model in China. Methods Multivariate regression models, including linear regression model, ordinal logistic regression model and Tobit model, were employed to analyz. Subgroup analyses were performed to analyze variations in sub-dimensional health attributes derived from FACT-B and EQ-5D-5L. A mapping function was used to estimate health utility from quality of life. Results 446 breast cancer patients with different disease states were analyzed. The utility of breast cancer patients with P state(without cancer recurrence and metastasis), R state(with cancer recurrence within a year), S state(with primary and recurrent breast cancer for the second year and above) and M state(metastasis cancer) were 0.81 (SD ±0.23), 0.90 (SD ±0.12), 0.78 (SD ±0.31), and 0.74 (SD ±0.27), respectively. All scores, including the FACT-B domain, showed a positive correlation( p <0.001). Multivariate analysis suggested that patients in R and M state had lower scores in overall quality of life (R,β = -9.45, p < 0.01; M, β = -6.72, P <0.05). Patients in M state had a lower probability of achieving higher health utility compared with patients in P state (β = -0.11, p < 0.05). Estimated health utilities derived from quality of life, using mapping function, were significantly correlated with directly measured health utilities ( p <0.001). Conclusions We obtained the health utility and HRQoL scores of Chinese breast cancer patients with different disease states. Mapping health utilities from quality of life in four disease states could be a plausible approach in health economic analysis, while the mapping function may need further revise.