Mapping EORTC QLQ-C30 and FACT-G onto EQ-5D-5L index for patients with cancer.
Mapping EORTC QLQ-C30 and FACT-G onto EQ-5D-5L index for patients with cancer.
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DOI：
10.1186/s12955-020-01611-w
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发表时间：
2020-11-03
影响因子：
3.6
通讯作者：
Shimozuma K
中科院分区：
文献类型：
--
作者：
Hagiwara Y;Shiroiwa T;Taira N;Kawahara T;Konomura K;Noto S;Fukuda T;Shimozuma K
开发欧洲癌症研究和治疗组织生活质量问卷核心30(EORTC QLQ-C30)和癌症治疗综合功能评估(FACT-G)到EQ-5D-5L指数的直接和间接(响应)映射算法。我们进行了QOL-MAC研究，在日本接受实体肿瘤药物治疗的患者中，对EQ-5D-5L、EORTC QLQ-C30和FACT-G进行了横断面评估。我们使用7种回归方法开发了直接和间接映射算法。直接映射基于日本的值集合。我们基于均方根误差(RMSE)、平均绝对误差以及观测和预测的EQ-5D-5L指数之间的相关性来评估预测性能。基于EORTC QLQ-C30和FACT-G的903名和908名患者的数据，我们建议对EORTC QLQ-C30和FACT-G进行直接映射的两部分贝塔回归和间接映射的有序Logistic回归。两种方法对EORTC QLQ-C30的交叉验证均方根误差为0.101，而对于FACT-G，两部分贝塔回归和有序Logistic回归的交叉验证RMSE分别为0.121和0.120。由推荐的测绘算法模拟的平均EQ-5D-5L指数和累积分布函数与观测结果基本吻合，但健康状况很好(两种来源的衡量标准)和较差的健康状况(只有FACT-G)。所开发的映射算法可用于在成本效果分析中从EORTC QLQ-C30或FACT-G生成EQ-5D-5L指数，其预测性能将与以前的算法相似或更好。
To develop direct and indirect (response) mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and the Functional Assessment of Cancer Therapy General (FACT-G) onto the EQ-5D-5L index. We conducted the QOL-MAC study where EQ-5D-5L, EORTC QLQ-C30, and FACT-G were cross-sectionally evaluated in patients receiving drug treatment for solid tumors in Japan. We developed direct and indirect mapping algorithms using 7 regression methods. Direct mapping was based on the Japanese value set. We evaluated the predictive performances based on root mean squared error (RMSE), mean absolute error, and correlation between the observed and predicted EQ-5D-5L indexes. Based on data from 903 and 908 patients for EORTC QLQ-C30 and FACT-G, respectively, we recommend two-part beta regression for direct mapping and ordinal logistic regression for indirect mapping for both EORTC QLQ-C30 and FACT-G. Cross-validated RMSE were 0.101 in the two methods for EORTC QLQ-C30, whereas they were 0.121 in two-part beta regression and 0.120 in ordinal logistic regression for FACT-G. The mean EQ-5D-5L index and cumulative distribution function simulated from the recommended mapping algorithms generally matched with the observed ones except for very good health (both source measures) and poor health (only FACT-G). The developed mapping algorithms can be used to generate the EQ-5D-5L index from EORTC QLQ-C30 or FACT-G in cost-effectiveness analyses, whose predictive performance would be similar to or better than those of previous algorithms.
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影响因子：
3.3
作者：
Brooks, R
通讯作者：
Brooks, R
影响因子：
45.3
作者：
Kemmler, G;Holzner, B;Sperner-Unterweger, B
通讯作者：
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影响因子：
2.2
作者：
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通讯作者：
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影响因子：
3.5
作者：
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通讯作者：
Badia, X.
影响因子：
3.6
作者：
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通讯作者：
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