Mapping the FACT-B instrument to EQ-5D-3L in patients with breast cancer using adjusted limited dependent variable mixture models versus response mapping

Objectives Preference based measures (PBMs) of health, such as EQ-5D-3L, are required to calculate QALYs for use in cost-effectiveness analysis, but are often not recorded in clinical studies. In these cases, mapping can be used to estimate PBMs. We model the relationship between EQ-5D-3L and Functional Assessment of Cancer Therapy - Breast Cancer (FACT-B), comparing indirect and direct mapping methods, and the use of FACT-B summary score verses subscale scores. Methods We use data from 3 clinical studies for advanced breast cancer providing 11,958 observations with full information on FACT-B and EQ-5D-3L. We compare direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) with indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of FACT-B and other patient related covariates. Results The use of FACT-B subscales was better than using total FACT-B score. A good fit to the observed data was observed across the range of disease severity in all models. ALDVMMs outperform the indirect mapping. The breast cancer specific scale significantly predicts EQ-5D-3L and this subscale has large influences on pain and self-care dimensions of EQ-5D-3L. Conclusion This paper adds to the growing literature that demonstrates the performance of the ALDVMM method for mapping. Regardless of which model is used, the subscales of FACT-B should be included as independent variables wherever possible. The breast cancer specific subscales of FACT-B are important in predicting EQ-5D-3L. This suggests that generic cancer measures should not be used for utility mapping in patients with breast cancer