Survival analysis involves statistical assessment time to death or time to relapse. Clinical trials in cancer commonly have survival as an endpoint, and frequently have progression-free survival as a secondary endpoint.
Progression-free survival refers to patients whose cancer remits or who do not relapse after treatment. It is reasonable to assume that survival and progression-free survival should be correlated. When this correlate is established, accurate estimates about survival should be possible for patients who progress with their cancer.
This in turn can be used in the design of clinical trials, possibly lowering the number of patients required for a given trial.
Yimei Li, PhD, and researchers at the Center for Childhood Cancer Research are taking data available from other cancer clinical trials to construct a statistical model that quantifies correlations between the two endpoints. Using results from this statistical survival analysis, they’re creating a model that can be used both for patient prognosis and clinical trial design.
Findings from these studies will be used to create a model that should become immediately available to researchers who are designing trials. Its application will also provide validation for the model as it starts to be used in clinical trial design more frequently.