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Abstract:
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Competing risks are common phenomena in time-to-event analysis for cardiac surgery long-term outcomes. A competing risk when occurring before the event of interest can exclude the possibility of event occurrence. For example, in the study of acute type-A aortic dissection patients, death is a competing risk for reoperation as it eliminates a patient’s chance to receive reoperation after arch replacement. Ignoring competing risks, for example, the use of standard Kaplan-Meier estimators, will result in biased estimates for the event of interest. Cumulative incidence function that estimates the probability of event of interest over time, and cause-specific hazard function that models the effect of covariates on the event of interest, are two main approaches to perform time-to-event analysis in the presence of competing risk. This study provides rational, implementation and interpretation for competing risks methods.
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