Leora R Feldstein1, Jill M Ferdinands1, Wesley H Self2, Adrienne G Randolph3,4, Michael Aboodi5, Adrienne H Baughman2, Samuel M Brown6, Matthew C Exline7, D Clark Files8, Kevin Gibbs8, Adit A Ginde9, Michelle N Gong10,11, Carlos G Grijalva2, Natasha Halasa12, Akram Khan13, Christopher J Lindsell2, Margaret Newhams3,4, Ithan D Peltan6, Matthew E Prekker14,15, Todd W Rice2, Nathan I Shapiro16, Jay Steingrub17, H Keipp Talbot2, M Elizabeth Halloran18,19, Manish Patel1. 1. Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. 2. Vanderbilt University Medical Center, Nashville, Tennessee, USA. 3. Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts, USA. 4. Departments of Anesthesia and Pediatrics, Harvard Medical School, Boston, Massachusetts, USA. 5. Division of Critical Care Medicine, Albert Einstein College of Medicine, Bronx, New York, USA. 6. Division of Pulmonary/Critical Care, Department of Medicine, Intermountain Medical Center and University of Utah, Murray, Utah, USA. 7. The Ohio State University, College of Nursing, Columbus, Ohio, USA. 8. Pulmonary Critical Care Allergy and Immunological Diseases, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 9. Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA. 10. Department of Medicine, Montefiore Healthcare System, Albert Einstein College of Medicine, Bronx, New York, USA. 11. Department of Epidemiology and Population Health Montefiore Healthcare System, Albert Einstein College of Medicine, Bronx, New York, USA. 12. Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 13. Department of Pulmonary and Critical Care, Oregon Health & Science University, Portland, Oregon, USA. 14. Department of Medicine, Division of Pulmonary and Critical Care, Hennepin County Medical Center and the University of Minnesota Medical School, Minneapolis, Minnesota, USA. 15. Department of Emergency Medicine, Hennepin County Medical Center and the University of Minnesota Medical School, Minneapolis, Minnesota, USA. 16. Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA. 17. Division of Critical Care Pulmonary Medicine, Baystate Medical Center, Springfield, Massachusetts, USA. 18. Department of Biostatistics, University of Washington, Seattle, Washington, USA. 19. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Abstract
BACKGROUND: Test-negative design studies for evaluating influenza vaccine effectiveness (VE) enroll patients with acute respiratory infection. Enrollment typically occurs before influenza status is determined, resulting in over-enrollment of influenza-negative patients. With availability of rapid and accurate molecular clinical testing, influenza status could be ascertained before enrollment, thus improving study efficiency. We estimate potential biases in VE when using clinical testing. METHODS: We simulate data assuming 60% vaccinated, 25% of those vaccinated are influenza positive, and VE of 50%. We show the effect on VE in 5 scenarios. RESULTS: Vaccine effectiveness is affected only when clinical testing preferentially targets patients based on both vaccination and influenza status. Vaccine effectiveness is overestimated by 10% if nontesting occurs in 39% of vaccinated influenza-positive patients and 24% of others. VE is also overestimated by 10% if nontesting occurs in 8% of unvaccinated influenza-positive patients and 27% of others. Vaccine effectiveness is underestimated by 10% if nontesting occurs in 32% of unvaccinated influenza-negative patients and 18% of others. CONCLUSIONS: Although differential clinical testing by vaccine receipt and influenza positivity may produce errors in estimated VE, bias in testing would have to be substantial and overall proportion of patients tested would have to be small to result in a meaningful difference in VE. Published by Oxford University Press for the Infectious Diseases Society of America 2021.
BACKGROUND: Test-negative design studies for evaluating influenza vaccine effectiveness (VE) enroll patients with acute respiratory infection. Enrollment typically occurs before influenza status is determined, resulting in over-enrollment of influenza-negative patients. With availability of rapid and accurate molecular clinical testing, influenza status could be ascertained before enrollment, thus improving study efficiency. We estimate potential biases in VE when using clinical testing. METHODS: We simulate data assuming 60% vaccinated, 25% of those vaccinated are influenza positive, and VE of 50%. We show the effect on VE in 5 scenarios. RESULTS: Vaccine effectiveness is affected only when clinical testing preferentially targets patients based on both vaccination and influenza status. Vaccine effectiveness is overestimated by 10% if nontesting occurs in 39% of vaccinated influenza-positive patients and 24% of others. VE is also overestimated by 10% if nontesting occurs in 8% of unvaccinated influenza-positive patients and 27% of others. Vaccine effectiveness is underestimated by 10% if nontesting occurs in 32% of unvaccinated influenza-negative patients and 18% of others. CONCLUSIONS: Although differential clinical testing by vaccine receipt and influenza positivity may produce errors in estimated VE, bias in testing would have to be substantial and overall proportion of patients tested would have to be small to result in a meaningful difference in VE. Published by Oxford University Press for the Infectious Diseases Society of America 2021.
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