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Influenza vaccine efficacy trials: a simulation approach to understand failures from the past

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Benoit, Anne Legrand, Catherine [UCL] Dewé, Walthère

The success of a seasonal influenza vaccine efficacy trial depends not only upon the design but also upon the annual epidemic characteristics. In this context, simulation methods are an essential tool in evaluating the performances of study designs under various circumstances. However, traditional methods for simulating time-to-event data are not suitable for the simulation of influenza vaccine efficacy trials because of the seasonality and heterogeneity of influenza epidemics. Instead, we propose a mathematical model parameterized with historical surveillance data, heterogeneous frailty among the subjects, survey-based heterogeneous number of daily contact, and a mixed vaccine protection mechanism. We illustrate our methodology by generating multiple-trial data similar to a large phase III trial that failed to show additional relative vaccine efficacy of an experimental adjuvanted vaccine compared with the reference vaccine. We show that small departures from the designing assumptions, such as a smaller range of strain protection for the experimental vaccine or the chosen endpoint, could lead to smaller probabilities of success in showing significant relative vaccine efficacy.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès restreint
Publication date 2015
Language Anglais
Journal information "Pharmaceutical Statistics : the journal of applied statistics in the pharmaceutical industry" - Vol. 14, no.4, p. 294-301 (2015)
Peer reviewed yes
Publisher JohnWiley & Sons Ltd. (Chichester)
issn 1539-1604
e-issn 1539-1612
Publication status Publié
Affiliation UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
Links
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Bibliographic reference Benoit, Anne ; Legrand, Catherine ; Dewé, Walthère. Influenza vaccine efficacy trials: a simulation approach to understand failures from the past. In: Pharmaceutical Statistics : the journal of applied statistics in the pharmaceutical industry, Vol. 14, no.4, p. 294-301 (2015)
Permanent URL http://hdl.handle.net/2078.1/183237