Alpha spending for historical versus surveillance Poisson data with CMaxSPRT.
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Date
2019
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Abstract
Sequential analysis hypothesis testing is now an important tool for postmarket
drug and vaccine safety surveillance. When the number of adverse events
accruing in time is assumed to follow a Poisson distribution, and if the baseline
Poisson rate is assessed only with uncertainty, the conditional maximized
sequential probability ratio test, CMaxSPRT, is a formal solution. CMaxSPRT is
based on comparing monitored data with historical matched data, and it was
primarily developed under a flat signaling threshold. This paper demonstrates
that CMaxSPRT can be performed under nonflat thresholds too.We pose the discussion
in the light of the alpha spending approach. In addition, we offer a rule
of thumb for establishing the best shape of the signaling threshold in the sense
of minimizing expected time to signal and expected sample size. An example
involving surveillance for adverse events after influenza vaccination is used to
illustrate the method.
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Keywords
Clinical trials, Postmarket vaccine safety surveillance, Sample size, Time to signal
Citation
SILVA, I. R. et al. Alpha spending for historical versus surveillance Poisson data with CMaxSPRT. Statistics in Medicine, v. 38, p. 2126– 2138, 2019. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1002/sim.8097>. Acesso em: 19 mar. 2019.