Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

ABSTRACT: Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demon

SUBMITTER: Kurtz DM 

PROVIDER: S-EPMC7380118 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature