Objective: This study's objective was to develop an algorithm that mapping the Haem-A-QoL scores to EQ-5D-5L utility scores in patients with hemophilia in China.
Methods: A national sample of 862 patients with hemophilia completed both the EQ-5D-5L and Haem-A-QoL instruments. Eight regression models were selected to develop the mapping algorithm, they were: the ordinary least squares, general linear regression, Tobit regression, censored least absolute deviation, mixture beta regression, adjusted limited dependent variable mixture, the two-part, and robust MM-estimator model. Root mean squared error (RMSE), mean absolute error (MAE), and R-square (R2) calculated using the tenfold cross-validation and random sample validation methods were used to assess the predictive ability of the models.
Results: Based on RMSE, MAE, and R2, the mixture beta regression model with selected Haem-A-QoL subscale scores as the predicted variables showed the best performance.
Conclusions: Our mapping algorithm bolsters the calculation of QALYs while conducting an economic evaluation of hemophilia-related interventions when only Haem-A-QoL data are available. The external validity of the algorithm should be further assessed in the other populations.
Keywords: EQ-5D; Haem-A-QoL; Hemophilia; Mapping; Prediction.
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.