Mapping the cancer-specific QLQ-C30 onto the generic EQ-5D-5L and SF-6D in colorectal cancer patients

Introduction: Economic evaluation of healthcare interventions usually needs accurate data on utility and health-related quality-of-life scores. The aim of this study is to map QLQ-C30 scale score onto EQ-5D-5L and SF-6D utility values in colorectal cancer (CRC) patients.

Methods: EQ-5D-5L, SF-6D, and QLQ-C30 were completed by 252 patients with CRC who were referred to three cancer centers in Tehran between May and September 2017. Moreover, OLS, Tobit, and CLAD models were used to predict EQ-5D-5L and SF-6D values. The goodness of fit of models was evaluated using Pred R2 and Adj R2. In addition, their predictive performance was assessed by MAE, RMSE, ICC, MID, and Spearman’s correlation coefficients between observed and predicted EQ-5D-5L and SF-6D values. Models were validated using a 10-fold cross-validation method.

Results: Considering the goodness of fit and predictive ability of models, the OLS Model 2 performed best for EQ-5D-5L (Adj R2 = 58.09%, Pred R2 = 58.93%, MAE = 0.0932, RMSE = 0.129) and the OLS Model 3 performed best for SF-6D (Adj R2 = 54.90%, Pred R2 = 55.62%, MAE = 0.0485, RMSE = 0.0634).

Conclusion: Our results demonstrated that algorithms developed based on OLS Models 1 and 2 are the best for predicted EQ-5D-5L and SF-6D values, respectively.