WHAT DO YOU BELIEVE? AN ONLINE TOOL FOR COST-EFFECTIVENESS ANALYSIS OF CIRCULATING TUMOR CELL DETECTION BASED ON USER BELIEFS

Purpose: Early HTA of new health technology is typically performed during technology development, when evidence on technology characteristics and performance is still very limited. Consequently, assumptions need to be made to evaluate the potential impact of the technology, which may not be acceptable, or supported, by all stakeholders. For example, we previously assessed the cost-effectiveness of circulating tumor cell (CTC) detection to guide systemic therapy in early breast cancer, compared to usual care, in a model based analysis. However, the lack of evidence required multiple assumptions on input parameters for this model. In this study we developed an online tool for clinicians and decision makers, allowing them to using their own beliefs and expertise as input for the cost-effectiveness analysis.

Methods: The online tool was based on the previous model based cost-effectiveness analysis and was built in R using the Shiny package. The mean estimated value and a range of uncertainty of several input parameters that have substantial influence on the outcome can be adjusted in the tool. Parameters classified as substantially influencing parameters are for example sensitivity, specificity and costs of CTC detection. Outcomes calculated by the tool are the base-case results (including the ICER) and an ICER plot of the probabilistic sensitivity analysis.

Results: The new tool allows easy and rapid reevaluation of the cost-effectiveness of CTCs compared to usual care under the user’s own beliefs. We found that different beliefs used as input for the analysis had substantial effect on the expected impact of CTC detection in terms of health benefits, cost savings and cost-effectiveness. However, as common in model based cost-effectiveness analysis, not all input parameters had substantial influence on the outcomes.

Conclusion: When evidence on new health technology is still limited, the outcomes of a cost-effectiveness analysis can vary widely with the assumptions and beliefs used as input for the model. Therefore, it may be valuable to have decision makers perform their ‘own’ analysis, that is, (re)calculating the cost-effectiveness under their own beliefs. Our tool enables such an approach and can facilitate discussion on different beliefs and their plausibility, recognizing that beliefs on some parameters affect cost-effectiveness more than beliefs on others. Research to further tailor the online tool to decision maker’s requirements is ongoing.