H1N1 and Seasonal Influenza Vaccine Safety in the Vaccine Safety Datalink Project
ABSTRACT The emergence of pandemic H1N1 influenza virus in early 2009 prompted the rapid licensure and use of H1N1 monovalent inactivated (MIV) and live, attenuated (LAMV) vaccines separate from seasonal trivalent inactivated (TIV) and live, attenuated (LAIV) influenza vaccines. A robust influenza immunization program in the U.S. requires ongoing monitoring of potential adverse events associated with vaccination.
To prospectively conduct safety monitoring of H1N1 and seasonal influenza vaccines during the 2009-2010 season.
The Vaccine Safety Datalink (VSD) Project monitors ∼9.2 million members in eight U.S. medical care organizations. Electronic data on vaccines and pre-specified adverse events were updated and analyzed weekly for signal detection from November 2009 to April 2010 using either a self-controlled design or a current versus historical comparison. Statistical signals were further evaluated using alternative approaches to identify temporal clusters and to control for time-varying confounders.
As of May 1, 2010, a total of 1,345,663 MIV, 267,715 LAMV, 2,741,150 TIV, and 157,838 LAIV doses were administered in VSD. No significant associations were noted during sequential analyses for Guillain-Barré syndrome, most other neurologic outcomes, and allergic and cardiac events. For MIV, a statistical signal was observed for Bell's palsy for adults aged ≥25 years on March 31, 2010, using the self-controlled approach. Subsequent analyses revealed no significant temporal cluster. Case-centered logistic regression adjusting for seasonality demonstrated an OR for Bell's palsy of 1.26 (95% CI=0.97, 1.63).
No major safety problems following H1N1 or seasonal influenza vaccines were detected in the 2009-2010 season in weekly sequential analyses. Seasonality likely contributed to the Bell's palsy signal following MIV. Prospective safety monitoring followed by rigorous signal refinement is critical to inform decision-making by regulatory and public health agencies.
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ABSTRACT: Sequential methods are well established for randomized clinical trials (RCTs), and their use in observational settings has increased with the development of national vaccine and drug safety surveillance systems that monitor large healthcare databases. Observational safety monitoring requires that sequential testing methods be better equipped to incorporate confounder adjustment and accommodate rare adverse events. New methods designed specifically for observational surveillance include a group sequential likelihood ratio test that uses exposure matching and generalized estimating equations approach that involves regression adjustment. However, little is known about the statistical performance of these methods or how they compare to RCT methods in both observational and rare outcome settings. We conducted a simulation study to determine the type I error, power and time-to-surveillance-end of group sequential likelihood ratio test, generalized estimating equations and RCT methods that construct group sequential Lan–DeMets boundaries using data from a matched (group sequential Lan–DeMets-matching) or unmatched regression (group sequential Lan–DeMets-regression) setting. We also compared the methods using data from a multisite vaccine safety study. All methods had acceptable type I error, but regression methods were more powerful, faster at detecting true safety signals and less prone to implementation difficulties with rare events than exposure matching methods. Method performance also depended on the distribution of information and extent of confounding by site. Our results suggest that choice of sequential method, especially the confounder control strategy, is critical in rare event observational settings. These findings provide guidance for choosing methods in this context and, in particular, suggest caution when conducting exposure matching. Copyright © 2014 John Wiley & Sons, Ltd.Statistics in Medicine 12/2014; DOI:10.1002/sim.6398 · 2.04 Impact Factor
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ABSTRACT: Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system. We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons. Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior. The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior.PLoS ONE 12/2014; 9(12):e115553. DOI:10.1371/journal.pone.0115553 · 3.53 Impact Factor
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ABSTRACT: The Vaccine Safety Datalink (VSD) is a collaborative project between the Centers for Disease Control and Prevention (CDC) and 9 health care organizations. Established in 1990, VSD is a vital resource informing policy makers and the public about the safety of vaccines used in the United States. Large linked databases are used to identify and evaluate adverse events in over 9 million individuals annually. VSD generates rapid, important safety assessments for both routine vaccinations and emergency vaccination campaigns. VSD monitors safety of seasonal influenza vaccines in near-real time, and provided essential information on the safety of monovalent H1N1 vaccine during the 2009 pandemic. VSD investigators have published important studies demonstrating that childhood vaccines are not associated with autism or other developmental disabilities. VSD prioritizes evaluation of new vaccines; searches for possible unusual health events after vaccination; monitors vaccine safety in pregnant women; and has pioneered development of biostatistical research methods.Vaccine 08/2014; 32(42). DOI:10.1016/j.vaccine.2014.07.073 · 3.49 Impact Factor