Assessing the impact of confounding (measured and unmeasured) in a case-control study to examine the increased risk of pandemic A/H1N1 associated with receipt of the 2008-9 seasonal influenza vaccine

Abstract

Background: This study examines the role of measured and unmeasured confounding in the relationship between the 2008-9 seasonal influenza vaccine and pandemic H1N1 (pH1N1) influenza virus.

Methods: Data were taken from a test-negative case-control study of 462 lab confirmed pandemic A/H1N1 (pH1N1) cases and 484 test-negative controls. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were derived using multivariate logistic regression. The analysis was repeated using propensity matching. A sensitivity analysis was conducted to quantify the impact of a hypothetical unmeasured confounder.

Results: Cases were more likely to have received the seasonal influenza vaccine after adjusting for multiple confounders using multivariate regression (OR 1.82, 95% CI: 1.25-2.65), using propensity matching (OR 1.86, 95% CI: 1.19-2.92) and in subsequent sensitivity analyses. An unmeasured confounder would need a prevalence of 20%, an odds ratio with the vaccine and pH1N1 of ≥3.5 and ≥3.0 (respectively) to result in a non-significant association. Using a prevalence of 40% the respective associations were 3.0 and 2.5.

Conclusion: A significant positive association between the seasonal influenza vaccine and lab confirmed pH1N1 was observed after considering multiple confounders and using different methods for confounder adjustment. This was not likely explained by an unmeasured confounder given the prevalence and strength of association needed to result in a non-significant association.