Keywords: estimands, recurrent event data, disease burden, time-to-event endpoints
Recurrent events are repeated occurrences of the same type of event. Endpoints capturing recurrent event information can lead to interpretable measures of treatment effect that better reflect disease burden and are more efficient than traditional time-to-first-event endpoints in the sense that they use the available information beyond the first event.
Recurrent event endpoints are well established in indications where recurrent events are clinically meaningful, treatments are expected to impact the first as well as subsequent events and where the rate of terminal events such as death is very low. Examples include: seizures in epilepsy; relapses in multiple sclerosis; and exacerbations in pulmonary diseases such as chronic obstructive pulmonary disease. More recently recurrent event data endpoints have also been proposed in other indications where the rate of terminal events is high, e.g. chronic heart failure, but experience in this setting is limited.
In trials using recurrent event endpoints, interest usually lies in understanding the underlying recurrent event process and how this is impacted by explanatory variables such as treatment. In this context, different endpoints and measures of treatment effect – that is, different estimands - can be considered. Depending on the specific setting some estimands may be more appropriate than others. For example, accounting for the interplay between the recurrent event process and the terminal event process is important in indications where the rate of terminal events is high. The choice of estimands has direct impact on trial design, conduct and statistical analyses.
A panel of experts including clinicians and statisticians from the FDA, academia and industry will discuss the value and possible limitations of using recurrent event estimands. The focus will lie on settings where the rate of disease related death is appreciable, e.g. chronic heart failure.
