DAVID M. KURTZ (STANFORD)
DYNAMIC RISK PROFILING USING SERIAL TUMOR BIOMARKERS FOR
PERSONALIZED OUTCOME PREDICTION
Recent advances in diagnostic approaches including liquid biopsies and minimal residual
disease monitoring are changing the way patients with malignancies are diagnosed and
monitored. Due to the ease of collection, these non-invasive tools allow for serial tumor
assessments over time during a course of disease. This allows for the development of novel
prognostic risk-models, which can provide a picture of likely outcomes for an individual
patient that can dynamically update over time. We developed the Continuous Individualized
Risk Index, or CIRI, as a method to construct such dynamic risk models. By applying CIRI to
patients with diffuse large B-cell lymphoma and chronic lymphocytic leukemia, we
demonstrate how integrating serial biomarkers acquired over time can lead to better outcome
predictions and the development of prognostic and predictive biomarkers.
