Competing Risks and Multi-State Models [EL001]
Prof.dr. Hein Putter
Erasmus MC, Rotterdam NL
Participants should have working knowledge of survival analysis and not feel uncomfortable with mathematical formulas. Knowledge of R is highly recommended.
Detailed information about this course:
Competing risks and multi-state models play an increasingly important role in the analysis of time to event data. Regarding competing risks, there is a lot of confusion regarding the proper analysis. The most important reason for the confusion is conceptual: which quantities can be estimated and what do they represent. Once the concepts are understood and the proper type of analysis has been chosen, most analyses are straightforward and can be performed with standard software for survival analysis. For multi-state models with exactly observed transition times, estimation is reasonably straightforward and the real challenge is in (dynamic) prediction.
The overarching goal of the course is to provide a solid introduction to these topics and thereby increase the analytical validity in this field.
In the first part of the course we cover competing risks analysis: what are competing risks and when do we need to take them into account; the independence assumption; cause-specific cumulative incidence; cause-specific hazard and subdistribution hazard; competing risks as a multi-state model. We will also cover regression models on both cause-specific and subdistribution hazard (Fine-Gray model) and discuss the difference in interpretation. We show how analyses can be performed with standard software. In the second part of the course, the extension to multi-state models is discussed. The course will cover topics including transition intensities and transition probabilities, nonparametric estimation and regression models, as well as methods to obtain predictions of future events, given the event history and clinical characteristics of a patient. With right censored and/or left truncated data, we show that it is possible to perform many types of analyses using standard software, using the same techniques as in multi-state representation of the competing risks model.
After successfully completing the course, the student will be able to:
- Describe the quantities that can be estimated in a competing risks framework, how they are interpreted, and the assumptions that must be made.
- Understand the relationship between the cause-specific hazard and cumulative incidence and describe why it is no longer one-to-one in a competing risks framework.
- Propose a suitable statistical model for assessing a specific research hypothesis in a competing risks situation, fit the model using standard statistical software, and interpret the results.
- Recognise when a multi-state model is appropriate, fit a multi-state model using standard statistical software, evaluate the fit of the model, and interpret the results.
Reduction on fees
PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 EC points)
No fees are charged for participation of Erasmus MC PhD candidates
Please note that in case of cancellation or no show, the cancellation policy applies based on the full course fee.
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.
25% reduction on our fees for Erasmus MC employees
For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above and Erasmus MC PhD candidates).
25% reduction for all (international) PhD students without formal appointment at Erasmus MC
Upon receipt of your application you will receive a request to upload proof of enrollment as a PhD student.