Competing Risk In Survival Analysis

When several different types of failures exist and the occurrence of one type of failure may prevent the observation of the other types of failures, the probabilities of these failures are often referred to as “competing risks.”  The standard Kaplan Meier product limit method and Cox proportional hazard model are often not adequate estimations of these risks.

Competing risk analysis aims to properly estimate the marginal probability of an event in the presence of competing events. We will review some fundamental statistical concepts of competing risk analysis and its application in clinical and cancer genomic research. These methods will be illustrated with examples using R packages.

ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.

CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)TM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.