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

Abstract

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.

Keywords: QALYs; cross walking; head and neck cancer (HNC); health state utility values (HSUVs); health-related quality of life (HRQoL); mapping algorithms; multi-attribute utility instruments (MAUIs); preference-based measures.