Iranian Center of Excellence in Health Management, School of Management and Medical Informatics, Health Economics Department, Tabriz University of Medical Sciences, Tabriz, Iran.
Cancer Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
Value Health Reg Issues. 2021 May;24:57-66. doi: 10.1016/j.vhri.2020.06.006. Epub 2021 Jan 25.
Many studies have mapped the QLQ-C30 onto the EQ-5D or the SF-6D utilities; however, these studies were limited to developed countries. So this study aimed to map QLQ-C30 onto the SF-6D version 2 (SF-6D-v2) and EQ-5D-5L using the data collected from patients with colorectal and breast cancer in a developing country.
A cross-sectional data set of 668 inpatient and outpatient patients with cancer was gathered from 4 teaching hospitals of cancer treatment in Tehran and Yazd from May 2017 to November 2018. The ordinary least squares (OLS) and censored least absolute deviations (CLAD) models were applied to estimate the utility values of both EQ-5D-5L and SF-6D-V2 using the QLQ-C30. Predicted R and adjusted R were used to evaluate the goodness of fit of the models. Moreover, the predictive performance of 2 models was assessed through estimating the mean absolute error (MAE), root mean square error (RMSE), intraclass correlation coefficients (ICC), and Spearman's rho. The 10-fold cross-validation method was also applied for validation of models.
The OLS Model E4 was the best-performing model for EQ-5D-5L (Adj R = 71.7%, Pred R = 71.15%, MAE = 0.0770, RMSE = 0.1026), and the OLS Model S4 performed best for SF-6D-V2 (Adj R = 74.64%, Pred R = 73.86%, MAE = 0.0465, RMSE = 0.0621).
The OLS Model E4 for EQ-5D-5L and the OLS Model S4 for SF-6D-V2 were the best models for policy makers to have more accurate evaluation of the healthcare interventions when the data are gathered through non-preference-based instruments.
许多研究已经将 QLQ-C30 映射到 EQ-5D 或 SF-6D 效用上；然而，这些研究仅限于发达国家。因此，本研究旨在使用发展中国家癌症患者的数据，将 QLQ-C30 映射到 SF-6D 版本 2（SF-6D-v2）和 EQ-5D-5L。
2017 年 5 月至 2018 年 11 月，从德黑兰和亚兹德的 4 家癌症治疗教学医院收集了 668 名住院和门诊癌症患者的横断面数据集。应用普通最小二乘法（OLS）和截尾最小绝对离差（CLAD）模型，使用 QLQ-C30 估计 EQ-5D-5L 和 SF-6D-V2 的效用值。采用预测 R 和调整 R 来评价模型的拟合优度。此外，通过估计平均绝对误差（MAE）、均方根误差（RMSE）、组内相关系数（ICC）和斯皮尔曼 rho 来评估两种模型的预测性能。还应用 10 倍交叉验证法对模型进行验证。
OLS 模型 E4 是 EQ-5D-5L 表现最佳的模型（调整 R=71.7%，预测 R=71.15%，MAE=0.0770，RMSE=0.1026），OLS 模型 S4 是 SF-6D-V2 表现最佳的模型（调整 R=74.64%，预测 R=73.86%，MAE=0.0465，RMSE=0.0621）。
对于决策者来说，当通过非偏好工具收集数据时，OLS 模型 E4 用于 EQ-5D-5L，OLS 模型 S4 用于 SF-6D-V2，这两个模型是更准确地评估医疗保健干预措施的最佳模型。
