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Blinded sample size re-estimation and information monitoring based on blindeddata has been suggested to mitigate risks due to planning uncertaintiesregarding nuisance parameters. Motivated by a randomized controlled trial inpediatric multiple sclerosis (MS), a continuous monitoring procedure foroverdispersed count data was proposed recently. However, this procedure assumedconstant event rates, an assumption often not met in practice. Here we extendthe procedure to accommodate time trends in the event rates considering twoblinded approaches: (a) the mixture approach modeling the number of events by amixture of two negative binomial distributions, and (b) the lumping approachapproximating the marginal distribution of the event counts by a negativebinomial distribution. Through simulations the operating characteristics of theproposed procedures are investigated under decreasing event rates. We find thatthe type I error rate is not inflated relevantly by either of the monitoringprocedures, with the exception of strong time dependencies where the procedureassuming constant rates exhibits some inflation. Furthermore, the procedureaccommodating time trends has generally favorable power properties compared tothe procedure based on constant rates which stops often too late. The proposedmethod is illustrated by the clinical trial in pediatric MS.

Blinded continuous information monitoring of recurrent event endpoints with time trends in clinical trials