The rapid spread of severe acute respiratory syndrome coronavirus 2 infection across the globe triggered an unprecedented increase in research activities that resulted in an astronomical publication output of observational studies. However, most studies failed to apply fully the necessary methodological techniques that systematically deal with different biases and confounding, which not only limits their scientific merit but may result in harm through misleading information. In this article, we address a few important biases that can seriously threaten the validity of observational studies of coronavirus disease 2019 (COVID-19). We focus on treatment selection bias due to patients' preference on goals of care, medical futility and disability bias, survivor bias, competing risks, and the misuse of propensity score analysis. We attempt to raise awareness and to help readers assess shortcomings of observational studies of interventions in COVID-19.
Keywords: bias; confounding; observational studies.
© The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America.