Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma

Empirical evidence for the EORTC QLQ C30 scale in thyroid cancer mapping algorithms has not been found in China, which limits the cost-utility analysis of patients with papillary thyroid carcinoma (PTC) population. We developed mapping algorithms that use the EORTC QLQ-C30 and QLQ H&N35 to predict EQ-5D-5L and SF-6D health utility scores for PTC patients.

Data from 1050 Chinese PTC patients who completed the EORTC QLQ-C30, QLQ H&N35, EQ-5D-5L and SF-6D instruments were collected. Direct mapping (OLS, Tobit, Betamix) and indirect mapping functions (Order Probit) were used to estimate algorithms. The goodness-of-fit of mapping performance was assessed by MAE, RMSE, AIC, BIC, AE, and ICC. A fivefold cross-validation and random sample validation approach were used to test the stability of the models.

The mean EQ-5D-5L and SF-6D utility scores were 0.8704 and 0.6368, respectively. We recommend the Betamix model for the EQ-5D-5L (MAE = 0.0363, RMSE = 0.0505, AIC = -3458.73, BIC = -3096.91, AE > 0.05(%) = 48.38, AE > 0.1(%) = 8.67, ICC = 0.8288 for the full sample dataset) and the Betamix model for the SF-6D (MAE = 0.0328, RMSE = 0.0417, AIC = -2788.91, BIC = -2605.51, AE > 0.05(%) = 42.76, AE > 0.1(%) = 3.62, ICC = 0.8657 for the full sample dataset), with EORTC QLQ-C30 all items, QLQ H&N35 all items, age and gender as the predicted variables showing the best performance.

In the absence of preference-based quality of life tools, the mapping algorithms reported here are effective alternative for predicting the health utility of PTC patients, contributing to the cost-utility analysis studies.