对于中国甲状腺癌患者群体，目前对于将临床工具映射到基于偏好的通用工具的证据有限。本研究旨在将FACT-H&N（头颈癌的癌症治疗功能评估）与SF-6D（8项短表六维）进行映射，以便为甲状腺癌治疗相关的未来成本效益分析提供信息。分析纳入了完成FACT-H&N和SF-6D问卷调查的1050名参与者。估计了四种直接和间接映射方法：最小二乘回归、截尾回归、有序概率回归和β混合回归。我们以均方根误差（RMSE）、平均绝对误差（MAE）、协方差相关系数（CCC）、阿卡迪克信息准则（AIC）和贝叶斯信息准则（BIC）以及观测与预测的SF-6D得分之间的相关性来评估预测性能。SF-6D的均值为0.690（标准差= 0.128）。本研究中多个模型的五折交叉验证和30%随机样本验证的RMSE值为0.0833-0.0909，MAE值为0.0676-0.0782，CCC值为0.6940-0.7161。 SF-6D效用分数最佳预测模型为由FACT-H&N每个维度的总得分、每个维度总得分的平方以及包括年龄和性别在内的协变量组成的回归模型。我们提议使用直接映射（最小二乘回归）和间接映射（有序概率回归）建立FACT-H&N到SF-6D的映射模型。从推荐的映射算法模拟得到的平均SF-6D和累计分布函数与观察到的基本一致。在缺乏基于偏好的生活质量工具的情况下，从直接映射的OLS回归和间接映射的有序概率回归中获取甲状腺癌患者的健康状态效用是一种有效的替代方法。©2023杨、黄、江、汤、曾。

There is limited evidence for mapping clinical tools to preference-based generic tools in the Chinese thyroid cancer patient population. The current study aims to map the FACT-H&N (Functional Assessment of Cancer Therapy-Head and Neck Cancer) to the SF-6D (Short Form Six-Dimension), which will inform future cost-utility analyses related to thyroid cancer treatment.A total of 1050 participants who completed the FACT-H&N and SF-6D questionnaires were included in the analysis. Four methods of direct and indirect mapping were estimated: OLS regression, Tobit regression, ordered probit regression, and beta mixture regression. We evaluated the predictive performance in terms of root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), Akaike information criterion (AIC) and Bayesian information criterion (BIC) and the correlation between the observed and predicted SF-6D scores.The mean value of SF-6D was 0.690 (SD = 0.128). The RMSE values for the fivefold cross-validation as well as the 30% random sample validation for multiple models in this study were 0.0833-0.0909, MAE values were 0.0676-0.0782, and CCC values were 0.6940-0.7161. SF-6D utility scores were best predicted by a regression model consisting of the total score of each dimension of the FACT-H&N, the square of the total score of each dimension, and covariates including age and gender. We proposed to use direct mapping (OLS regression) and indirect mapping (ordered probit regression) to establish a mapping model of FACT-H&N to SF-6D. The mean SF-6D and cumulative distribution functions simulated from the recommended mapping algorithm generally matched the observed ones.In the absence of preference-based quality of life tools, obtaining the health status utility of thyroid cancer patients from directly mapped OLS regression and indirectly mapped ordered probit regression is an effective alternative.Copyright © 2023 Yang, Huang, Jiang, Tang and Zeng.