Background: Diagnostic biomarkers have multiple applications along the care process and have a large potential in optimizing treatment decisions. However, many diagnostic biomarkers struggle to gain market access and obtain appropriate coverage because of a lack of evidence on their health economic impact.
Objectives: The aim was to review the (methodological) characteristics of recent economic evaluations on diagnostic biomarkers and examine whether these studies dealt with specific issues such as different payer perspectives, preference heterogeneity, and multiple applications in subpopulations.
Methods: The PubMed database and the National Health Service Economic Evaluation Database were searched. Full economic evaluations published after 2009 assessing diagnostic biomarkers for the main non-communicable diseases in middle-income or high-income countries were considered eligible. Empirical and methodological study characteristics were summarized, as was the handling of specific issues related to the economic evaluation of personalized medicine.
Results: Thirty-three economic evaluations were included, of which 25 were model-based analyses. The number of strategies compared ranged from two to 17 per study, and was especially large in studies assessing genetic testing in patients and their relatives. Cost-effectiveness results were most sensitive to test accuracy and costs of the biomarker (N = 7), the relative risk of an event (N = 4), and the proportion of people accepting genetic testing (N = 2). One study incorporated patient preferences, and none of the studies considered different payer perspectives, cost sharing arrangements or variable opportunity costs due to population density variability.
Conclusions: Published health economic evaluations of biomarkers used for diagnosing, staging diseases, and guiding treatment selection are characterized by a large number of comparators to model the potential clinical applications and to determine their value. Assessing outcomes beyond health as well as specific issues, such as different payer perspectives and patient preferences, is crucial to fully capture the potential health economic impact of diagnostic biomarkers and to inform value-based reimbursement.