Event-driven type design for clinical trials with recurrent events
Jingwen Zhang, Satoshi Hattori

TL;DR
This paper introduces an event-driven design for clinical trials involving recurrent events, ensuring target power and controlling type 1 error by monitoring robust variance in a blinded manner.
Contribution
It proposes a novel event-driven design for recurrent event outcomes that accounts for within-subject correlation and maintains statistical power.
Findings
The method controls power effectively in simulations.
It prevents inflation of type 1 error rate.
Demonstrated successful application on real data.
Abstract
It is a common practice in randomized clinical trials with the standard survival outcome to follow patients until a prespecified number of events have been observed, a type of trial known as the event-driven trial. The event-driven design ensures that the target power for a specified type 1 error rate is achieved to detect the target hazard ratio, regardless of the specification of other quantities. To understand the treatment effect for chronic conditions, the analysis of recurrent events has gained popularity in randomized controlled trials, particularly large-scale confirmatory trials. In the absence of within-subject correlation among multiple events, a similar event-driven design can be employed for recurrent event outcomes. On the other hand, in the presence of the within-subject correlation, one needs to model the correlation among recurrent events in evaluating power and setting…
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Taxonomy
TopicsStatistical Methods in Clinical Trials · Advanced Causal Inference Techniques · Statistical Methods and Inference
