The clinical course of cirrhosis: The importance of multi-state models and competing risks analysis. Jepsen P, Vilstrup H, Andersen PK. Hepatology. 2014 Nov 5. [Epub ahead of print]
Multi-state models are models of disease progression that for a patient group define multiple outcome events, each of which may affect the time to develop another outcome event. Multi-state models are highly relevant for studies of cirrhosis patients; both the classical perception of cirrhosis as either compensated or decompensated and the recent more complex models of cirrhosis progression are multi-state models.
Therefore, researchers who conduct clinical studies of cirrhosis patients must realize that most of their research questions assume a multi-state disease model. Failure to do so can result in severely biased results and bad clinical decisions. The analyses that can be used to study disease progression in a multi-state disease model may be called competing risks analysis, named after the competing risks disease model which is the simplest multi-state disease model. In this review article we introduce multi-state disease models and competing risks analysis and explain why the standard armamentarium of Kaplan-Meier survival estimates and Cox regression sometimes gives bad answers to good questions. We also use real data to answer typical research questions about the course of cirrhosis and illustrate biases resulting from inadequate methods. Finally, we suggest statistical software packages that are helpful and accessible to the clinician-researcher.