Abbreviations
infection
INFECTION, RESPIRATORY SYNCYTIAL VIRUS (RSV)
average causal effectconfidence intervalHospital Treatment Insights databasemissing at randommissing completely at randommultiple imputationmissing not at randomrandomized controlled trialrespiratory syncytial virustarget trialRandomized controlled trials (RCTs) are commonly used for estimating causal effects of point interventions. However, in many epidemiologic settings, an RCT may be infeasible or ethically nonviable. Hence, observational data are also used to compare effectiveness, with various strategies adopted to address the lack of randomization and indication bias, for example, by controlling for measured confounders. Analysis of observational data suffers from various additional sources of bias, such as selection bias, indication bias, and immortal time bias (Target trial emulation aims to avoid some of these biases by adopting the design principles of RCTs. Individuals in an observational database, such as administrative health records, are selected according to a set of eligibility criteria that mirror those that would be used in an RCT (One solution is to impute missing eligibility prior to selection into a target trial. However, we could find only one precedent of imputation of eligibility criteria prior to the creation of a target trial in (In this paper we investigate biases in the average causal effect (ACE) of a point exposure, in a target trial with missing eligibility data. Our simulations consider realistic scenarios where the eligibility variables modify the true causal effect. We consider two strategies of analysis: 1) conditioning on variables that drive missingness eligibility, and 2) recovering the missing eligibility data via MI. A study of palivizumab, a monoclonal antibody for prevention of symptoms of severe respiratory syncytial virus (RSV) infection in high-risk infants, based on administrative hospital and pharmacy dispensing data is used to illustrate these alternative approaches.