title: Adaptive and repeated cumulative meta-analyses of safety data during a new drug development process.
abstract: During a new drug development process, it is desirable to timely detect potential safety signals. For this purpose, repeated meta-analyses may be performed sequentially on accumulating safety data. Moreover, if the amount of safety data from the originally planned program is not enough to ensure adequate power to test a specific hypothesis (e.g., the noninferiority hypothesis of an event of interest), the total sample size may be increased by adding new studies to the program. Without appropriate adjustment, it is well known that the type I error rate will be inflated because of repeated analyses and sample size adjustment. In this paper, we discuss potential issues associated with adaptive and repeated cumulative meta-analyses of safety data conducted during a drug development process. We consider both frequentist and Bayesian approaches. A new drug development example is used to demonstrate the application of the methods.
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Quan
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Yingqiu
authors.initials: Y
authors.lastname: Ma
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zheng
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Meehyung
authors.initials: M
authors.lastname: Cho
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Christelle
authors.initials: C
authors.lastname: Lorenzato
authors.affiliation: Department of Biostatistics and Programming, Sanofi, Bridgewater, NJ, USA.
authors.forename: Carole
authors.initials: C
authors.lastname: Hecquet
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000379:methods* / Q000592:standards; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis / Q000453:epidemiology*; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D013223:Statistics as Topic / Q000379:methods* / Q000592:standards
keywords: combination test; conditional power; fixed and random effects models; noninferiority; type I error rate control