Competing Risks and Multistate models are widely used in medical research when survival data involve composite outcomes with absorbing events (competing risks) and possible intermediate events (multistate). These models can be used to obtain risk prediction on future outcome development and to assess the prognostic impact of patient characteristics and therapeutic interventions on the outcome development.
Prediction – The incidence function is generalized to competing risks data by its decomposition into absolute risks of each absorbing event. Absolute risks are called “crude probabilities” emphasizing the indirect protection that each absorbing event determines on the others. In the presence of multistate data, the intermediate events are included in the absolute risks which are called “state probabilities”, emphasizing that subjects may sojourn in intermediate states in the multistate process that takes to the absorbing events.
Prognostic Impact – The hazard function is generalized to competing risks data by its decomposition into cause specific hazard of each absorbing event. In the presence of multistate data, the intermediate events are included among the hazard functions that are called “transition hazard” between the states, to emphasize the motion among the intermediate and absorbing states.
The course will deal first with the clinical questions and corresponding theoretical quantities. This link will be crucial to guide the student in the approach to estimation and inference to be adopted.
Syllabus available at https://elearning.unimib.it/course/info.php?id=22057
To enroll please write to Laura Antolini laura.antolini@unimib.it
Host Organization: University of Milano Bicocca, School of Medicine – Monza via Cadore 48