Modelling recurrent events: a tutorial for analysis in epidemiology

Abstract

In many biomedical studies, the event of interest can occur more than once in a participant. These events are termed recurrent events. However, the majority of analyses focus only on time to the first event, ignoring the subsequent events. Several statistical models have been proposed for analysing multiple events. In this paper we explore and illustrate several modelling techniques for analysis of recurrent time-to-event data, including conditional models for multivariate survival data (AG, PWP-TT and PWP-GT), marginal means/rates models, frailty and multi-state models. We also provide a tutorial for analysing such type of data, with three widely used statistical software programmes. Different approaches and software are illustrated using data from a bladder cancer project and from a study on lower respiratory tract infection in children in Brazil. Finally, we make recommendations for modelling strategy selection for analysis of recurrent event data.

Keywords: Recurrent events; survival modelling; time-to-event data.

© The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Figures

Figure 1.

Schematic plot for recurrent time-to-event data for five hypothetical subjects.

Figure 2.

Schematic for full multi-state model for recurrent events.

Figure 3.

Predicted transition probabilities for four patients using the AG multi-state model fitted to bladder study.

Figure 4.

Predicted transition probabilities for two girls using the AG multi-state model fitted to ALRI study.