Pimrapat Gebert, Anna Maria Hage, Felix Fischer, Christoph Paul Klapproth, Ulrike Grittner, Maria Margarete Karsten
{"title":"转移性乳腺癌患者EORTC CAT核心和QLQ-C30转化为EQ-5D-5L:直接和间接定位算法的比较","authors":"Pimrapat Gebert, Anna Maria Hage, Felix Fischer, Christoph Paul Klapproth, Ulrike Grittner, Maria Margarete Karsten","doi":"10.1007/s10198-025-01824-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>To enable the use of different non-preference-based patient-reported outcome measures to derive utility values for health economic evaluations in oncological trials, this study developed direct and indirect mapping algorithms for estimating the EQ-5D-5L utility index via the German value set from the EORTC CAT Core and the QLQ-C30 in metastatic breast cancer patients.</p><p><strong>Methods: </strong>We included 1,839 observations from 878 patients with metastatic breast cancer from the PRO B study. We compared direct mapping algorithms, including adjusted limited dependent variable mixture models (ALDVMM), Tobit regression, ordinal least squares regression, and adjusted beta regression, while indirect mapping employed a generalized ordered logit model. Visualization was used to assess model performance across the entire distribution, while quantitative evaluation was performed using mean absolute error (MAE), root mean squared error (RMSE), and mean prediction bias.</p><p><strong>Results: </strong>Among the direct algorithms, adjusted beta regression demonstrated the best performance. It had the lowest MAE of 0.07-0.08 and RMSE of 0.11-0.13, a mean prediction bias of -0.004, close to zero. The indirect mapping model also performed well, with a mean prediction bias of 0.04 and MAE of 0.07, showing performance comparable to the preferred direct mapping algorithm for both the EORTC CAT Core and the QLQ-C30.</p><p><strong>Conclusions: </strong>This study developed and validated robust direct and indirect algorithms for estimating the EQ-5D-5L utility index from the EORTC CAT Core and the QLQ-C30 based on the German tariff. In particular, using this indirect mapping algorithm, the EORTC CAT Core and QLQ-C30 can be translated into quality-adjusted life-years, facilitating health economic evaluations across different country tariffs.</p><p><strong>Trial registration: </strong>DRKS (German Clinical Trials Register) DRKS00024015. Registered on 15 February 2021, https//drks.de/search/de/trial/DRKS00024015.</p>","PeriodicalId":51416,"journal":{"name":"European Journal of Health Economics","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Translating the EORTC CAT core and the QLQ-C30 to the EQ-5D-5L in patients with metastatic breast cancer: A comparison of direct and indirect mapping algorithms.\",\"authors\":\"Pimrapat Gebert, Anna Maria Hage, Felix Fischer, Christoph Paul Klapproth, Ulrike Grittner, Maria Margarete Karsten\",\"doi\":\"10.1007/s10198-025-01824-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>To enable the use of different non-preference-based patient-reported outcome measures to derive utility values for health economic evaluations in oncological trials, this study developed direct and indirect mapping algorithms for estimating the EQ-5D-5L utility index via the German value set from the EORTC CAT Core and the QLQ-C30 in metastatic breast cancer patients.</p><p><strong>Methods: </strong>We included 1,839 observations from 878 patients with metastatic breast cancer from the PRO B study. We compared direct mapping algorithms, including adjusted limited dependent variable mixture models (ALDVMM), Tobit regression, ordinal least squares regression, and adjusted beta regression, while indirect mapping employed a generalized ordered logit model. Visualization was used to assess model performance across the entire distribution, while quantitative evaluation was performed using mean absolute error (MAE), root mean squared error (RMSE), and mean prediction bias.</p><p><strong>Results: </strong>Among the direct algorithms, adjusted beta regression demonstrated the best performance. It had the lowest MAE of 0.07-0.08 and RMSE of 0.11-0.13, a mean prediction bias of -0.004, close to zero. 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Translating the EORTC CAT core and the QLQ-C30 to the EQ-5D-5L in patients with metastatic breast cancer: A comparison of direct and indirect mapping algorithms.
Background: To enable the use of different non-preference-based patient-reported outcome measures to derive utility values for health economic evaluations in oncological trials, this study developed direct and indirect mapping algorithms for estimating the EQ-5D-5L utility index via the German value set from the EORTC CAT Core and the QLQ-C30 in metastatic breast cancer patients.
Methods: We included 1,839 observations from 878 patients with metastatic breast cancer from the PRO B study. We compared direct mapping algorithms, including adjusted limited dependent variable mixture models (ALDVMM), Tobit regression, ordinal least squares regression, and adjusted beta regression, while indirect mapping employed a generalized ordered logit model. Visualization was used to assess model performance across the entire distribution, while quantitative evaluation was performed using mean absolute error (MAE), root mean squared error (RMSE), and mean prediction bias.
Results: Among the direct algorithms, adjusted beta regression demonstrated the best performance. It had the lowest MAE of 0.07-0.08 and RMSE of 0.11-0.13, a mean prediction bias of -0.004, close to zero. The indirect mapping model also performed well, with a mean prediction bias of 0.04 and MAE of 0.07, showing performance comparable to the preferred direct mapping algorithm for both the EORTC CAT Core and the QLQ-C30.
Conclusions: This study developed and validated robust direct and indirect algorithms for estimating the EQ-5D-5L utility index from the EORTC CAT Core and the QLQ-C30 based on the German tariff. In particular, using this indirect mapping algorithm, the EORTC CAT Core and QLQ-C30 can be translated into quality-adjusted life-years, facilitating health economic evaluations across different country tariffs.
Trial registration: DRKS (German Clinical Trials Register) DRKS00024015. Registered on 15 February 2021, https//drks.de/search/de/trial/DRKS00024015.
期刊介绍:
The European Journal of Health Economics is a journal of Health Economics and associated disciplines. The growing demand for health economics and the introduction of new guidelines in various European countries were the motivation to generate a highly scientific and at the same time practice oriented journal considering the requirements of various health care systems in Europe. The international scientific board of opinion leaders guarantees high-quality, peer-reviewed publications as well as articles for pragmatic approaches in the field of health economics. We intend to cover all aspects of health economics:
• Basics of health economic approaches and methods
• Pharmacoeconomics
• Health Care Systems
• Pricing and Reimbursement Systems
• Quality-of-Life-Studies The editors reserve the right to reject manuscripts that do not comply with the above-mentioned requirements. The author will be held responsible for false statements or for failure to fulfill the above-mentioned requirements.
Officially cited as: Eur J Health Econ