OBJECTIVES: The translation of diagnostic biomarker tests into clinical practice demands significant investment in time and resource, and thus early economic evaluation is useful to prioritize tests with the greatest potential for successful adoption in clinical settings. We conduct an early economic analysis to identify the necessary characteristics of novel biomarker tests for GCA to be cost effective in the NHS.

METHODS: A combined decision tree and Markov model was developed to assess the potential cost-utility of biomarker tests for patients with symptoms suggestive of GCA at secondary care. Input parameters were based on secondary data sources and expert opinions. A lifetime horizon and the NHS and Personal Social Services (PSS) perspective were adopted for the analysis. Sensitivity analyses were undertaken to figure out how accurate the biomarker tests need to be, and at what price, for them to be cost effective.

RESULTS: The results show the maximum price of a hypothetical biomarker test at varying levels of specificity and sensitivity needed to achieve cost-effectiveness, according to the decision threshold at £20,000 per QALY. For a biomarker test to be more cost-effective than standard care, it must exhibit higher specificity. A test with perfect accuracy (100% sensitivity and specificity) could be priced as high as £3,924.

CONCLUSIONS: The analysis shows the potential for the hypothetical biomarker tests to improve diagnosis of GCA and reduce risks of glucocorticoid toxicity, along with the market potential of developing the tests for clinical use in the NHS. Our study shows that economic models can provide vital information for developers at an early stage, although with limited evidence available.