Prognostic Factors and Predictions of Survival Data Using Cox PH Models and Random Survival Forest Approaches

Most if not all survival analysis approaches are focused on survival (or time-to-event) outcomes, which are usually associated with serious disease conditions, such as death, heart failures and recurrence of cancers. Typically, survival outcome includes one binary variable for occurrence(s) of the event(s) of interest and at least one continuous variable for the time of the occurrence(s) or the censoring time (2 time variables may be needed for the intervals within which the event occurs). The outcome is referred to as time-to-event, which has been one of the major endpoints for clinical studies.