The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings

Details

• Alternative Title:
  Int J Epidemiol
• Personal Author:
  Foppa, Ivo M. ; Ferdinands, Jill M. ; Chaves, Sandra S. ; Haber, Michael J. ; Reynolds, Sue B. ; Flannery, Brendan ; Fry, Alicia M.
• Description:
  Background
  
  The test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting.
  
  Methods
  
  We derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies.
  
  Results
  
  VE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates.
  
  Conclusions
  
  The inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis.
  
  
• Subjects:
  Bias Computer Simulation Epidemiologic Research Design Humans Influenza, Human Influenza Vaccines Inpatients Patient Acceptance Of Health Care Population Surveillance Treatment Outcome Vaccination

  More +
• Source:
  Int J Epidemiol. 45(6):2052-2059.
• Pubmed ID:
  26979985
• Pubmed Central ID:
  PMC5025336
• Document Type:
  Journal Article
• Volume:
  45
• Issue:
  6
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:77f2b4e10ffaafcb47ecf3c288ab53bf3c0bb76655ee5efb8f87c8abeae5e0aa
• Download URL:
  https://stacks.cdc.gov/view/cdc/41344/cdc_41344_DS1.pdf
• File Type:
  [PDF - 332.62 KB ]