New publication on estimating the mean number of events

Estimates of the mean number of events provide a valuable summary measure for recurrent-event processes in the presence of competing risks. A recurrent event refers to an event that can occur multiple times for the same individual, which is common in medical research — examples include infections, cancer recurrences, hospitalisations, or childbirth. However, individuals may face, in addition to the recurrent event, competing events such as death, which may prevent them from experiencing the recurrent event and complicates the estimation.

The new model addresses this challenge of modelling both the recurrent-event and the competing-event process simultaneously. It provides a smooth estimation of the average number of events over time, offering an easily interpretable summary measure. For instance, estimating the average number of hospitalisations after colon cancer surgery could offer valuable insights into recovery patterns — patients with more hospitalisations likely face more severe complications, suggesting a slower or more complicated recovery.

While this model provides a useful and interpretable summary of the recurrent-event process, it is by nature a summary measure. For more detailed analysis of the recurrent-event process, other modelling approaches such as multi-state models may be more suitable, as they can explicitly model transitions between different states or event occurrences.