OBJECTIVES: Predictive biomarkers testing approach in the oncology field could represent a virtuous model to invest in for the treatment optimization and improvement in the patients' quality of life. However, in an era of clearly limited resources the debate about the value of immunotherapy in cancer care is deepen discussed. We aimed to describe literature evidence about the cost-effectiveness of biomarkers use in solid tumours and evaluated the opportunity cost of testing by discounting the detected costs.

METHODS: A two-step approach was designed: i) a systematic literature review (PROSPERO ID: CRD42020201549) according to the PRISMA statement guidelines querying PubMed and Embase (2010-2020), using PICO Model to identify economic evaluations (EE) on biomarker testing in oncology; ii) uncertainty evaluation: addressing the issue of EEs-uncertainty in terms of parameters used such as type of cost outcomes and discount rate.

RESULTS: After the abstracts and full-text screenings, 60 articles met the inclusion criteria identified with PICO Model. 74% of them were cost-effectiveness analysis, and more than half of those analyses were based on a Markov model. More than half (65%) of the included EEs rated predictive-biomarker testing as cost-effective in their current scenario. The EEs-cost analysis process will allow for uniform unit currency of cost outcomes considering the actual discount rate having an assessment of cost-efficacy of predictive-biomarkers profiles.

CONCLUSIONS: Despite the critical role of the cost-effectiveness of predictive biomarkers in decision making, no systematic review has compared the cost-effectiveness by discounting the costs in the current scenario and assessing its feasibility in terms of resource allocation.