Competing risks in survival analysis

Survival analysis is interested in the study of the time until the occurrence of an event of interest (e.g., time to death). A competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. For instance, in a study of cardiovascular death, death due to non-cardiovascular causes is a competing risk, as subjects who die of non-cardiovascular causes are no longer at risk of cardiovascular death. In this seminar we will discuss statistical methods for the analysis of survival data in the presence of competing risks. Examples and code will be used to illustrate the use of these methods.

[@mohamedabo-aly7634]

Excellent, one of the best lectures ever on survival analysis and competing risks. Thanks Peter.

[@free23456]

an excellent lecture that saved me during epidemiology class. Thank you !

[@AbhayShuklaSilpara]

This is one of the best lectures on Survival Analysis.

[@dobrinkostov4840]

ppo

[@johnryan7616]

Outstanding presentation - thank you for posting!

[@railzip]

I love this! Thank you so much

[@michaelzamani3523]

Thank you so much! great lecture

[@23andrelopes]

Excellent lecture

[@rechellejacobs3315]

Thanks for this presentation.
In the context of bank credit risk: If the primary event is time to loan default and say the the client closes and repays the loan account prior to loan maturity, i.e. loan is repaid and the account is closed (this event happened prior to loan default) and default is thus no longer possible. Is the account closure event a competing risk?

[@amrendrasingh7140]

Yes, because default and prepayment are terminal states.

[@xinlu82]

very nice presentation. I have a question about the competing risk in multi-state model. what kind of method is used in multi-state model, cause-specific or sub-distribution hazard model? Or another method?

[@populationdatabc1184]

Multistate models are a framework by which to examine event transitions over time.
Survival models are simply a 2-state unidirectional multistate model.
Competing risks models are also multistate models.
If the question is about regression methods under a multistate framework, then both cause-specific and sub-distribution models may be implemented (similar to other multistate models, such as competing risks models).

[@shumetmebrat3043]

how can we calculate sample size for computing risk regression model is it differ from survival technique or different? 2. can we apply competing risk with prediction model in asingle study?

[@anngreenwoodeducationandtr1630]

The following is a reply from Dr. Peter Austin. 1. For a cause-specific hazard model, you can use methods that you would for a conventional Cox model. I haven’t seen examples of power calculations for subdistribution hazard models. 2. Can we apply competing risk with prediction model in a single study?
I’m not entirely clear on what is meant by this question. One can develop and internally validate a model in a single study. However, one would want to subsequently validate the model in an external sample.