ArticlePharmacoEconomics2025
Towards Recommendations for Cost-Effectiveness Analysis of Predictive, Prognostic, and Serial Biomarker Tests in Oncology.
Article in PharmacoEconomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- The End of 'Pay-and-Hope': Managing Accelerated Approvals with Outcomes-Based Reimbursement in the Era of Routinely Collected Health Data.PharmacoEconomics · 2026Article
- Liquid Biopsy and Multi-Omic Biomarkers in Breast Cancer: Innovations in Early Detection, Therapy Guidance, and Disease Monitoring.Biomedicines · 2025Review
- CLDN18.2 expression in gastroesophageal adenocarcinoma: prevalence, heterogeneity, and prognostic implications in Spanish patients.Virchows Archiv : an international journal of pathology · 2025Article
- Economic Evaluation of Comprehensive Genomic Profiling in an Advanced Solid Cancer Population.JAMA network open · 2025Observational
- Value-based health care frameworks for the health technology assessments of "omics" technologies: an international survey.International journal of technology assessment in health care · 2025Article
- Histopathological and Molecular Predictors of the First Site of Dissemination in Non-Small Cell Lung Cancer.Current oncology (Toronto, Ont.) · 2025Article
- Innovation Headroom for a Highly Accurate PD-L1 Companion Diagnostic in Non-small Cell Lung Cancer.PharmacoEconomics · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundCost-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.
objectiveWe 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.
methodsA 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.
resultsA 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.
conclusionsWe 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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