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B0635
Title: Time-varying survivor average causal effects with semicompeting risks Authors:  Fabrizia Mealli - University of Florence (Italy) [presenting]
Abstract: In semicompeting risks problems, nonterminal time-to-event outcomes such as time to hospital readmission are subject to truncation by death. These settings are often modeled with parametric illness-death models, but evaluating causal treatment effects with hazard models is problematic due to the evolution of incompatible risk sets over time. To combat this problem, we introduce two new causal estimands: the time-varying survivor average causal effect (TV-SACE) and the restricted mean survivor average causal effect (RM-SACE). These principal stratum causal effects are defined among units that would survive regardless of assigned treatment. We adopt a Bayesian estimation procedure that is anchored to parameterization of illness-death models for both treatment arms but maintains causal interpretability. We outline a frailty specification that can accommodate within-person correlation between nonterminal and terminal event times. The method is demonstrated in the context of hospital readmission among newly diagnosed late-stage pancreatic patients. Joint work with Leah Comment and Cory Zigler.