Department of Thoracic Surgery Sichuan Clinical Research Center for Cancer Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Nursing Department, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Qual Life Res. 2024 Mar;33(3):805-816. doi: 10.1007/s11136-023-03567-y. Epub 2023 Dec 26.
This study aimed to develop a mapping algorithm to evaluate the EQ-5D-5L according to the FACT-L when the EQ-5D-5L is not available.
EQ-5D-5L and FACT-L data were collected from patients with lung cancer in Departments of Thoracic Surgery, Medical Oncology, Radiation Oncology, Sichuan Cancer Hospital. We used the ordinary least squares model (OLS), Tobit model (Tobit), two-part model (TPM), beta mixture regression (BM), and censored least absolute deviation model (CLAD) to map the results of the FACT-L according to EQ-5D-5L scores. To establish these models, the total score, dimension scores, squared items, and interaction items were introduced. Performance metrics including Adjusted R, root mean square error (RMSE), and mean absolute error (MAE) were used to select the optimized model.
The model with the best mapping performance was the BM model (BETAMIX4) with the PWB (physical well-being) dimension, FWB (functional well-being) dimension, the squared term of the PWB dimension, and the squared term of the FWB dimension as covariates. The final prediction metrics were Adjusted R = 0.695, RMSE = 0.206, and MAE = 0.109. Fivefold cross-validation (CV) results also demonstrated that the BM model had the best mapping power.
This study developed an optimized mapping algorithm to predict the utility index from the FACT-L to the EQ-5D-5L, which provides an effective alternative reference for EQ-5D-5L estimation when the preference-based health utility values were unavailable.
本研究旨在开发一种映射算法，以根据 FACT-L 评估 EQ-5D-5L，当 EQ-5D-5L 不可用时。
在四川省肿瘤医院胸外科、肿瘤内科、放疗科收集肺癌患者的 EQ-5D-5L 和 FACT-L 数据。我们使用普通最小二乘法（OLS）、Tobit 模型（Tobit）、两部分模型（TPM）、β混合回归（BM）和截尾最小绝对偏差模型（CLAD）根据 EQ-5D-5L 评分映射 FACT-L 的结果。为了建立这些模型，引入了总评分、维度评分、平方项和交互项。使用调整后的 R、均方根误差（RMSE）和平均绝对误差（MAE）等性能指标来选择优化模型。
具有最佳映射性能的模型是 BM 模型（BETAMIX4），其协变量为 PWB（身体幸福感）维度、FWB（功能幸福感）维度、PWB 维度的平方项和 FWB 维度的平方项。最终预测指标为调整后的 R=0.695、RMSE=0.206 和 MAE=0.109。五折交叉验证（CV）结果也表明，BM 模型具有最佳的映射能力。
本研究开发了一种优化的映射算法，以从 FACT-L 预测 EQ-5D-5L 的效用指数，当偏好健康效用值不可用时，为 EQ-5D-5L 估计提供了有效的替代参考。
