Have you ever heard of competing risks in clinical research? It’s a relevant concept that allows to estimate the probability of an event happening in the presence of other, mutually exclusive events. Imagine patients in a clinical study at risk for multiple, potential outcomes:

• A deceased patient cannot be rehospitalized. 
• Patients may have, in many case definitions, either an acute or chronic manifestation.
• After a death from myocardial infarction, one cannot die from cancer.

There are different methods in survival analysis to model competing events (e.g., sub-distribution and cause-specific hazard models). Still, only few studies account for competing events:

In a recent survey of 136 cardiovascular disease studies with composite endpoints, only 14 (10%) conducted a competing risk analysis and reported the corresponding results. Omission of competing risk analysis can reduce the precision and power, and lead to erroneous inferences.

-> DOI: https://doi.org/10.1016/j.jclinepi.2023.05.015

So, watch out😊