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Continuous Versus Group Sequential Analysis for Post-Market Drug and Vaccine Safety Surveillance

    Basic Details

    This article describes the use of continuous and group statistical analysis for prospective post-market vaccine and drug safety surveillance based on observational electronic health data. The comparison focuses on 1) type 1 error, 2) statistical power, 3) the expected time to signal when the null hypothesis is rejected, and 4) the sample size required to end surveillance without rejecting the null. The two key conclusions from this article are (i) that any post-market safety surveillance system should attempt to obtain data as frequently as possible, and (ii) that sequential testing should always be performed when new data arrives without deliberately waiting for additional data.


    Ivair R. Silva PhD, Martin Kulldorff PhD

    Corresponding Author

    I. R Silva, Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA and Department of Statistics, Universidade Federal de Ouro Preto, Ouro Preto, Minas Gerais, Brazil. Email: