1 Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet2 Aarhus University3 Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet
The Importance of Multistate Models and Competing Risks Analysis
Multistate 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. Multistate models are highly relevant for studies of patients with cirrhosis; both the classical perception of cirrhosis as either compensated or decompensated and the recent, more complex models of cirrhosis progression are multistate models. Therefore, researchers who conduct clinical studies of patients with cirrhosis must realize that most of their research questions assume a multistate 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 multistate disease model may be called competing risks analysis, named after the competing risks disease model, which is the simplest multistate disease model. In this review article, we introduce multistate 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.