title: Detectable Risks in Studies of the Fetal Benefits of Maternal Influenza Vaccination.
abstract: Maternal influenza vaccination prevents influenza illness in both mothers and newborns. Results from some recent studies have suggested that influenza vaccination might also prevent adverse pregnancy outcomes, such as preterm birth. However, it is challenging to conduct epidemiologic studies to evaluate the benefits to the fetus of maternal influenza vaccination because the causal benefit of vaccination is likely only experienced by the small fraction of the cohort in whom influenza illness is prevented by vaccination. The plausibility of detecting true differences in risks between groups under such conditions is rarely discussed. We aimed to inform the interpretation of studies in which the fetal benefits of maternal influenza vaccination are evaluated by estimating detectable risk ratios and necessary sample sizes for different study scenarios. Estimates of rates of influenza illness, vaccine effectiveness, vaccine uptake, and preterm birth and of the association of influenza illness with preterm birth were identified from the published literature. We calculated detectable risk ratios for preterm birth in vaccinated versus unvaccinated women and the associated sample size requirements. Our results demonstrated that under most scenarios, plausible differences between groups will be extremely challenging to detect (risk ratios for preterm birth of 0.9 to 1.0) and will require sample sizes infeasible for prospective epidemiologic research. This suggests that the large fetal benefits from influenza vaccination observed in epidemiologic studies are unlikely to be causal.
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Hutcheon
authors.forename: Deshayne B
authors.initials: DB
authors.lastname: Fell
authors.forename: Michael L
authors.initials: ML
authors.lastname: Jackson
authors.forename: Michael S
authors.initials: MS
authors.lastname: Kramer
authors.forename: Justin R
authors.initials: JR
authors.lastname: Ortiz
authors.forename: David A
authors.initials: DA
authors.lastname: Savitz
authors.forename: Robert W
authors.initials: RW
authors.lastname: Platt
mesh_terms: D015986:Confounding Factors, Epidemiologic; D015340:Epidemiologic Research Design; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology; D007252:Influenza Vaccines / Q000008:administration & dosage* / Q000009:adverse effects; D007251:Influenza, Human / Q000517:prevention & control*; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000592:standards*; D011247:Pregnancy; D011251:Pregnancy Complications, Infectious / Q000276:immunology / Q000517:prevention & control* / Q000821:virology; D011256:Pregnancy Outcome / Q000453:epidemiology*; D047928:Premature Birth / Q000453:epidemiology / Q000517:prevention & control; D018401:Sample Size
chemical_list: D007252:Influenza Vaccines
keywords: immunization; influenza illness; influenza vaccine; pregnancy; pregnancy complication; preterm birth; sample size; statistical power