POTENTIAL ECONOMIC VALUE OF BIOMARKERS IN PERSONALIZED MEDICINE: AN EXEMPLARY ASSESSMENT STUDY IN HEART FAILURE DISEASE MANAGEMENT

Purpose: A large amount of biomarkers have been currently identified, whereas their emerging role to improve personalized care at affordable cost has hardly been investigated. The aim of the current research was to show how potential economic value of biomarkers can be evaluated based on evidence from clinical studies regarding heart failure (HF) disease management.

Method(s): Patient-level 18-month mortality risks were predicted by both a prediction model which contains demographic and clinical predictors for HF-related outcomes and a model which contains three additional biomarkers: NT-proBNP, galectine, and troponin. A previously derived cut-off value of 0.16 was adopted to allocate an intensive form of disease management program (DMP) to low-risk patients and a moderate form of DMP to intermediate to high-risk patients. The improved ability of risk classification after the incorporation of biomarkers was evaluated using the net reclassification improvement (NRI). Subsequently, a continuous-time semi-Markov model was developed to evaluate the potential economic value of the biomarkers through presenting the commercial headroom available, a price ceiling for which the future clinical application of the new medical technology may be deemed cost-effective. Such a conceptual technology considered in this study was a biomarker-based test-kit that aims to ultimately improve personalized HF disease management.

Result(s): A significantly (P<0.001) improved risk stratification was established with 0.1814 (95% confidence interval: 0.0926~0.2703) as the NRI estimate. Extending this finding for the base-case values of the decision model parameters, we found the commercial headroom available for the biomarkers to be €256 within a 5-year time horizon. This value was rather sensitive to the alteration of the risk thresholds to 0.1 and 0.2.

Conclusion(s): The estimates of the available commercial headroom in several scenario analyses indicate considerable economic potential of the biomarkers to support personalized disease management in HF.