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Towards Recommendations for Cost-Effectiveness Analysis of Predictive, Prognostic, and Serial Biomarker Tests in Oncology

生活质量研究 医学 生物标志物 卫生经济学 预测值 肿瘤科 成本效益 卫生行政 公共卫生 内科学 医学物理学 风险分析(工程) 病理 生物化学 化学
作者
Astrid Kramer,Lucas Frederik van Schaik,Daan van den Broek,Gerrit A. Meijer,Iñaki Gutiérrez‐Ibarluzea,Lorea Galnares Cordero,Remond J.A. Fijneman,Marjolijn J. L. Ligtenberg,Ed Schuuring,Wim H. van Harten,Veerle M.H. Coupé,Valesca P. Retèl
出处
期刊:PharmacoEconomics [Adis, Springer Healthcare]
被引量:1
标识
DOI:10.1007/s40273-025-01470-7
摘要

Cost-effectiveness analysis (CEA) of biomarkers is challenging due to the indirect impact on health outcomes and the lack of sufficient fit-for-purpose data. Hands-on guidance is lacking. We aimed firstly to explore how CEAs in the context of three different types of biomarker applications have addressed these challenges, and secondly to develop recommendations for future CEAs. A scoping review was performed for three biomarker applications: predictive, prognostic, and serial testing, in advanced non-small cell lung cancer, early-stage colorectal cancer, and all-stage colorectal cancer, respectively. Information was extracted on the model assumptions and uncertainty, and the reported outcomes. An in-depth analysis of the literature was performed describing the impact of model assumptions in the included studies. A total of 43 CEAs were included (31 predictive, 6 prognostic, and 6 serial testing). Of these, 40 utilized different sources for test and treatment parameters, and three studies utilized a single source. Test performance was included in 78% of these studies utilizing different sources, but this parameter was differently expressed across biomarker applications. Sensitivity analyses for test performance was only performed in half of these studies. For the linkage of test results to treatments outcomes, a minority of the studies explored the impact of suboptimal adherence to test results, and/or explored potential differences in treatment effects for different biomarker subgroups. Intermediate outcomes were reported by 67% of studies. We identified various approaches for dealing with challenges in CEAs of biomarker tests for three different biomarker applications. Recommendations on assumptions, handling uncertainty, and reported outcomes were drafted to enhance modeling practices for future biomarker cost-effectiveness evaluations.

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