Mapping the EORTC QLQ‐C30 and QLQ‐H&N35, onto EQ‐5D‐5L and HUI‐3 indices in patients with head and neck cancer. Issue 9 (25th April 2020)

• Record Type: Journal Article
• Authors: Noel, Christopher W.; Stephens, Robert F.; Su, Jie (Susie); Xu, Wei; Krahn, Murray; Monteiro, Eric; Goldstein, David P.; Giuliani, Meredith; Hansen, Aaron R.; de Almeida, John R.
• Is Part Of: Head & neck. Volume 42:Issue 9(2020)
• Page Start: 2277
• Page End: 2286
• Publication Date: 2020-04-25
• Subjects: 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 -- QALYs; Head -- Diseases -- Periodicals; Neck -- Diseases -- Periodicals; Head -- Periodicals; Neck -- Periodicals; Face -- Periodicals; 617.51059
• DOI: 10.1002/hed.26181
• Languages: English
• ISSNs: 1043-3074

Abstract

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 R 2 = .75, 10‐fold cross‐validation RMSE = 0.064, MAE 0.050). The HUI‐3 model mapping onto EORTC through OLS was more limited (adjusted R 2 = .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.