The following is a summary of “Need for a clinical case definition in test-negative design studies estimating vaccine effectiveness,” published in the August 2023 issue of Infectious Diseases by Sullivan et al.
Test-negative studies are common markers to assess the effectiveness of COVID-19 vaccines against an illness that requires medical attention, given specific assumptions. Potential bias due to participation probabilities linked to vaccination or COVID-19 can be lessened by applying a clinical case definition for patient selection. Researchers performed a retrospective study to assess the potential negative impact of this bias on COVID-19 vaccine effectiveness. They re-analyzed Test-negative study reviews to identify studies disregarding clinical criteria.
Studies with a clinical case definition showed a lower pooled vaccine effectiveness estimate than those without. Simulations altered selection probability based on case and vaccination status. They used an HTML tool to analyze selection bias in their studies.
A positive bias away from the null (i.e., inflated VE consistent with the systematic review) appeared with a greater ratio of healthy vaccinated non-cases. This can be achieved when the dataset includes numerous outcomes from asymptomatic screening in areas with high vaccination rates.
The study concluded that all groups should be cautious about selection bias in vaccine effectiveness studies, especially when working with administrative data.