Mapping the <scp>EORTC QLQ‐C30</scp> and <scp>QLQ‐H</scp> & <scp>N35</scp> , onto <scp>EQ‐5D‐5L</scp> and <scp>HUI</scp> ‐3 indices in patients with head and neck cancer

Background We sought to develop mapping functions that use EORTC responses to approximate health utility (HU) scores for patients with head and neck cancer (HNC). Methods In total, 209 outpatients with HNC completed the EORTC QLQ-C30 & QLQ-H&N35 (EORTC), EQ-5D-5L and the HUI-3. Results of the EORTC were mapped onto both EQ-5D-5L and HUI-3 scores using ordinary least squares regression and two-part models. Results The OLS model mapping EORTC onto the EQ-5D-5L performed best (adjusted R2 = .75, 10-fold cross-validation RMSE = 0.064, MAE 0.050). The HUI-3 model mapping onto EORTC through OLS was more limited (adjusted R2 = .5746, 10-fold cross cross-validation RMSE = 0.168, MAE 0.080). The EQ-5D-5L model was able to discriminate between certain clinical indices of disease severity on subgroup analysis. Conclusion The EORTC to EQ-5D-5L mapping algorithm has good predictive validity and may enable researchers to translate EORTC scores into HU scores for head and neck patients with cancer.