11: Estimation of state occupation probabilities for the illness-death model via multiple imputation

Thomas M. Menino Convention & Exhibition Center 

In clinical research, multi-state models can provide a more granular description of disease progression than traditional outcomes such as overall survival or composite endpoints. State occupation probabilities for multi-state models can be derived from the Aalan-Johansen estimator, which also yields unbiased estimates of transition probabilities for data satisfying the Markov property. Recent work has employed multiple imputations of event times in right censored data to unbiasedly estimate survival and cumulative incidence functions, which are straightforwardly calculated as proportions after censored times have been imputed. In this talk, we extend these ideas to estimate state occupation probabilities and joint confidence regions for the three-state irreversible illness-death model, including when the Markov property does not hold. Through simulation, we empirically demonstrate that our imputation-based estimator unbiasedly estimates state occupation probabilities in both Markov and non-Markov settings, and corresponding pointwise confidence regions exhibit nominal coverage.

Multiple imputation

Survival analysis

Multi-state model

Illness-death model

Non-Markov model 

Biometrics Section