CORECT (Competing Risks and Endpoints in Clinical Trials)
The goal of this project is to develop personalized methods to risk-stratify populations with competing risks. We have shown that standard risk models are suboptimal, reducing efficiency and leading to mismatch in assigning proper intensity of therapy for patients. We have developed a novel method
(generalized competing event (GCE) regression) to stratify patients according to their relative risk for competing events, known as the omega ratio. This ratio is critically linked to the benefit of cancer treatments. Our research lab was the first to show that patients with higher omega ratios preferentially benefit from treatment. This theory is being tested prospectively in the
international Phase II/III NRG HN004 trial.