Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/11458
Title: Alpha spending for historical versus surveillance Poisson data with CMaxSPRT.
Authors: Silva, Ivair Ramos
Lopes, Wilson Araujo
Dias, Philipe
Yih, W. Katherine
Keywords: Clinical trials
Postmarket vaccine safety surveillance
Sample size
Time to signal
Issue Date: 2019
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.
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.
URI: http://www.repositorio.ufop.br/handle/123456789/11458
metadata.dc.identifier.uri2: https://onlinelibrary.wiley.com/doi/10.1002/sim.8097
metadata.dc.identifier.doi: https://doi.org/10.1002/sim.8097
ISSN: 1097-0258
Appears in Collections:DEEST - Artigos publicados em periódicos

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