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Estimating vaccine efficacy over time after a randomized study is unblinded

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  • Anastasios A. Tsiatis
  • Marie Davidian

Abstract

The COVID‐19 pandemic due to the novel coronavirus SARS CoV‐2 has inspired remarkable breakthroughs in the development of vaccines against the virus and the launch of several phase 3 vaccine trials in Summer 2020 to evaluate vaccine efficacy (VE). Trials of vaccine candidates using mRNA delivery systems developed by Pfizer‐BioNTech and Moderna have shown substantial VEs of 94–95%, leading the US Food and Drug Administration to issue Emergency Use Authorizations and subsequent widespread administration of the vaccines. As the trials continue, a key issue is the possibility that VE may wane over time. Ethical considerations dictate that trial participants be unblinded and those randomized to placebo be offered study vaccine, leading to trial protocol amendments specifying unblinding strategies. Crossover of placebo subjects to vaccine complicates inference on waning of VE. We focus on the particular features of the Moderna trial and propose a statistical framework based on a potential outcomes formulation within which we develop methods for inference on potential waning of VE over time and estimation of VE at any postvaccination time. The framework clarifies assumptions made regarding individual‐ and population‐level phenomena and acknowledges the possibility that subjects who are more or less likely to become infected may be crossed over to vaccine differentially over time. The principles of the framework can be adapted straightforwardly to other trials.

Suggested Citation

  • Anastasios A. Tsiatis & Marie Davidian, 2022. "Estimating vaccine efficacy over time after a randomized study is unblinded," Biometrics, The International Biometric Society, vol. 78(3), pages 825-838, September.
    • Handle: RePEc:bla:biomet:v:78:y:2022:i:3:p:825-838
    DOI: 10.1111/biom.13509
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    References listed on IDEAS

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    1. Ira M. Longini & M. Elizabeth Halloran, 1996. "A Frailty Mixture Model for Estimating Vaccine Efficacy," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(2), pages 165-173, June.
    2. Shu Yang & Anastasios A. Tsiatis & Michael Blazing, 2018. "Modeling survival distribution as a function of time to treatment discontinuation: A dynamic treatment regime approach," Biometrics, The International Biometric Society, vol. 74(3), pages 900-909, September.
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