Introduction to the Analysis of Survival Data in the Presence of Competing Risks
University of North Carolina at Chapel Hill · Sunnybrook Health Science Centre · +5 more institutions
Abstract
Competing risks occur frequently in the analysis of survival data. A competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. In a study examining time to death attributable to cardiovascular causes, death attributable to noncardiovascular causes is a competing risk. When estimating the crude incidence of outcomes, analysts should use the cumulative incidence function, rather than the complement of the Kaplan-Meier survival function. The use of the Kaplan-Meier survival function results in estimates of incidence that are biased upward, regardless of whether the competing events are independent of one another. When fitting regression models in the presence of…
Citation impact
- FWCI
- 150.74
- Percentile
- 100%
- References
- 28
Authors
3- PCPeter C. AustinCorresponding
University of North Carolina at Chapel Hill, Sunnybrook Health Science Centre, University Health Network, University of Toronto, Applied Physical Sciences (United States), Institute for Clinical Evaluative Sciences, Sunnybrook Research Institute
- DSDouglas S. Lee
University Health Network
- JPJason P. Fine
University Health Network
Topics & keywords
- Covariate
- Medicine
- Proportional hazards model
- Survival analysis
- Cumulative incidence
- Incidence (geometry)
- Survival function
- Event (particle physics)
- Good health and well-being