Competing risks: Concepts, methods and software

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Advanced course / School
From October 14, 2015
to October 16, 2015

This event is part of the ​IRP Statistical Advances for complex data​​

Course’s description

Competing risks: concepts, methods and software
Lecturer: Ronald Geskus, Academic Medical Center, Amsterdam, The Netherlands​ ​​
 
A competing risks analysis quantifies the occurrence of mutually exclusive event types over time. Furthermore, it is used to study the impact of different factors on this spectrum of event types. Competing risks methods are used increasingly more often in other fields of research. Yet, there is still a lot of confusion with respect to the quantities that can be estimated and their interpretation.
 
We describe two different approaches to analysis: the multi-state approach and the subdistribution approach. The first is based on the cause-specific hazard, and has a direct extension to Markov multi-state models. Estimation of the cause-specific hazard is completely standard: individuals leave the risk set when they experience a competing event. The cumulative quantity, the cause-specific cumulative incidence, is estimated via the Aalen-Johansen estimator. The subdistribution approach is based on the subdistribution hazard. Under general mechanisms of left truncation and right censoring, an estimator is defined that is based on inverse probability weights. It is used in a product-limit estimator of the cause-specific cumulative incidence that has the surprising property of being algebraically equivalent to the Aalen-Johansen estimator.
 
In the regression setting, we mainly consider proportional hazards models during the course. For the cause-specific hazard, this is a standard Cox model. The proportional subdistribution hazards model is known as the Fine and Gray model. We explain how the creation of a stacked data set allows for large flexibility in modeling effects on all competing risks in a single analysis.
 
The course will alternate sessions that are devoted to explanation of the theory with sessions in which the concepts learned can be practiced through exercises, mostly by using the R statistical computing environment. A good working knowledge of survival analysis and R is recommended.

 Scientific coordinators

Guadalupe Gómez  Universitat Politècnica de Catalunya
Montse Rue Universitat de Lleida

LIST OF PARTICIPANTS

Emma Arcos
Arantzazu Arrospide
Jordi Blanch IDIAP Jordi Gol
Marta Bofill
Roger Borràs Hospital Clínic de Barcelona
Alejandra Cabaña Universitat Autònoma de Barcelona
Jordi Comas
Marc Comas
Alvaro Corral Centre de Recerca Matemàtica
Anna Espinal Universitat Autònoma de Barcelona
Adriana Freitas
Olga García
Ronald Geskus Academic Medical Center
Guadalupe Gómez Universitat Politècnica de Catalunya
Moises Gómez MOISES GOMEZ MATEU
Olga Julià
KyungMann Kim University of Wisconsin-Madison
Klaus Langohr Universitat Politècnica de Catalunya
Mireia Morgades Institut Català d’Oncologia
Valentí Navarro Institut Català d’Oncologia
Montserrat Rue Universitat de Lleida
Isabel Serra Centre de Recerca Matemàtica
Isaac Subirana CIBER de Epidemiología y Salud Pública

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For inquiries about this event please contact the Scientific Events Coordinator Ms. Núria Hernández at nhernandez@crm.cat​​

 

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