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