Raising the Bar for Launching Biomarker Utility Trial Design with Muti-stage Incidence and Mortality Modeling

Music City Center 

Before implementing a biomarker test for early cancer detection into routine clinical care, the test must demonstrate clinical utility, i.e., the test results should lead to clinical actions that positively affect patient-relevant outcomes. Unlike therapeutical trials for patients diagnosed with cancer, designing a randomized controlled trial (RCT) to demonstrate the clinical utility of an early detection biomarker with mortality and related endpoints poses unique challenges. We propose a generic multistate disease history model. The model links key performance metrics of the test, such as sensitivity, to primary endpoints like the incidence of late-stage cancer and mortality. It also incorporates the practical implementation of the biomarker-testing program in real-world scenarios. Multiple pathways from diagnosis to mortality endpoint were considered to accommodate differential and time-varying screening effects. We show how such a model can be used to calculate justified target accuracy levels for launching a utility trial based on the model's projected cost-benefit ratio of a screening program. We use numerical examples from the National Lung Screening Trial (NLST) to demonstrate the method.

Clinical Utility Trial

Biomarker

Math Modeling