UGent Campus De Sterre, S9
By Vanessa Didele from University of Bristol, U.K.
Causal Models for Optimal Dynamic Treatments with Survival Outcomes
A dynamic treatment is a set of rules that assigns for each time point when a treatment decision needs to be made what this should be, given the patient's history so far. An example in the context of HIV studies is "start treatment when CD4 count first drops below 600". An optimal dynamic treatment is such a set of rules that optimises a criterion reflecting better health for the patient.
I will give an overview of the main methods in this context (based on structural models), with particular attention to the case of survival outcomes. For instance we may use the g-computation approach or dynamic marginal structural models - the latter are becoming popular for HIV studies as mentioned above.
The particular difficulty with survival outcomes is that marginal and conditional models are typically not compatible. I will discuss and compare approaches, as well as the issue of simulating from structural models; this (hopefully) leads to additional insight and understanding of the models used in this context.