Real-world comparison of counterfactual inference methods for evaluating impact of antidepressants on COVID outcomes

Abstract In order to discover drugs that could be repurposed for a public health emergency like the COVID-19 pandemic, the National COVID Cohort Collaborative (N3C) database compiles health records including 22 millions individuals and 8.9 million cases of COVID-19. Here, we sought to use this data to systematically investigate whether antidepressants could impact COVID-19 outcomes, adjusting for known risk factors for severe outcome. We conducted large scale target trial emulation, comparing all pairs of 18 antidepressants to each other. Because the best approach for discovering such drug effects from observational data is not known, we applied a series of methods for identifying drug effects by estimating the counterfactual outcome that would be observed in a randomized trial. We found that all methods for counterfactual outcome estimation were prone to bias due to poorly controlled unmeasured confounding. We describe this bias, which appears to be induced partly by conditioning on treatment exposure, opening a back door path, via collider effects, between treatment and exposure via unmeasured confounders. Via empirical simulations, we show that our approach is able to detect this bias. In result, we state that we are not able to confidently identify any antidepressant impacting COVID-19 outcomes. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work was supported by the National Institute of General Medicine Sciences (NIGMS R35 GM151001-01) to RDM. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used ONLY openly available human data that were originally located at: https://covid.cd2h.org/enclave/ I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data analyzed are available online at https://covid.cd2h.org/enclave/ No data were generated by this study.