Abstract
Introduction: Vaccine safety surveillance commonly includes a serial testing approach with a sensitive method for ‘signal generation’ and specific method for ‘signal validation.’ The extent to which serial testing in real-world studies improves or hinders overall performance in terms of sensitivity and specificity remains unknown. Methods: We assessed the overall performance of serial testing using three administrative claims and one electronic health record database. We compared type I and II errors before and after empirical calibration for historical comparator, self-controlled case series (SCCS), and the serial combination of those designs against six vaccine exposure groups with 93 negative control and 279 imputed positive control outcomes. Results: The historical comparator design mostly had fewer type II errors than SCCS. SCCS had fewer type I errors than the historical comparator. Before empirical calibration, the serial combination increased specificity and decreased sensitivity. Type II errors mostly exceeded 50%. After empirical calibration, type I errors returned to nominal; sensitivity was lowest when the methods were combined. Conclusion: While serial combination produced fewer false-positive signals compared with the most specific method, it generated more false-negative signals compared with the most sensitive method. Using a historical comparator design followed by an SCCS analysis yielded decreased sensitivity in evaluating safety signals relative to a one-stage SCCS approach. While the current use of serial testing in vaccine surveillance may provide a practical paradigm for signal identification and triage, single epidemiological designs should be explored as valuable approaches to detecting signals.
| Original language | English |
|---|---|
| Pages (from-to) | 797-807 |
| Number of pages | 11 |
| Journal | Drug Safety |
| Volume | 46 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Aug 2023 |
Bibliographical note
Funding Information:This work was supported by US National Institutes of Health [grant number R01AI153044], a contract from the US Food and Drug Administration and an Intergovernmental Personnel Act agreement with the US Department of Veterans Affairs.
Publisher Copyright:
© 2023, The Author(s).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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