Comparison of alpha-spending plans for near real-time monitoring for Guillain-Barré Syndrome after influenza vaccination during the 2010/11 influenza season

Abstract

BackgroundNear real-time surveillance of the influenza vaccine, which is administered to a large proportion of the US population every year, is essential to ensure safety of the vaccine. For efficient near real-time surveillance, it is key to select appropriate parameters such as monitoring start date, number of interim tests and a scheme for spending a pre-defined total alpha across the entire influenza season. Guillain-Barré Syndrome, shown to be associated with the 1976 influenza vaccine, is used to evaluate how choices of these parameters can affect whether or not a signal is detected and the time to signal. FDA has been monitoring for the risk of GBS after influenza vaccination for every influenza season since 2008. MethodsUsing Medicare administrative data and the Updating Sequential Probability Ratio Test methodology to account for claims delay, we evaluated a number of different alpha-spending plans by varying several parameters. ResultsFor relative risks of 5 or greater, almost all alpha-spending plans have 100% power; however, for relative risks of 1.5 or lower, the constant and O’Brien-Fleming plans have increasingly more power. For RRs of 1.5 and greater, the Pocock plan signals earliest but would not signal at a RR of 1.25, as observed in prior influenza seasons. There were no remarkable differences across the different plans in regards to monitoring start dates defined by the number of vaccinations; reducing the number of interim tests improves performance only marginally. ConclusionsA constant alpha-spending plan appears to be robust, in terms of power and time to detect a signal, across a range of these parameters, including alternate monitoring start dates based on either cumulative vaccinations or GBS claims observed, frequency of monitoring, hypothetical relative risks, and vaccine uptake patterns.