Use of multi-state models for time-to-event data

Received 06.05.2017 Revised 18.08.2017 Accepted 23.08.2017 Published 01.10.2017 Background & Aim: In medical sciences, the outcome is the time until the occurrence of an event of interest. A multi-state model (MSM) is used to model a process where subjects’ transition takes place from one state to the next. For instance, a standard survival curve can be thought of as a simple MSM with two states (alive and dead) and the transition between these two-state models is a method used to analyze time to event data. The most important aspect of this model is that it considers intermediate events and models the effect of covariates on each transition intensity. Some diseases like cancer, human immunodeficiency virus (HIV), etc. have several stages. In the present study, these models were reviewed using cardiac allograft vasculopathy (CAV) data focusing on different approaches.

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