Inhaled corticosteroids (ICS) are anti-inflammatory medications commonly used as routine medications in asthma and chronic obstructive pulmonary disease (COPD). At the beginning of the COVID-19 pandemic, it was thought that people with asthma or COPD might be at a higher risk of severe COVID-19 but this was not observed early in the pandemic. It was not clear why, but it was suggested that lung disease, patients’ behaviour or their treatment may have a protective effect against severe COVID-19.
In this study, we will examine the association between ICS use and SARS-CoV-2 infection, COVID-19 hospital admission, and COVID-19 death among people who have either asthma or COPD. We will also examine, using a set of methods called quantitative bias analysis, how systematic biases may have affected any observed association between ICS use and COVID-19 outcomes. This could include addressing errors relating to e.g., undetected COVID-19 cases, or systematic differences between patients who were prescribed ICS and those who were not.
This project will help understand the role of ICS in COVID-19 and the systematic biases that can affect observational studies of medications and COVID-19. This will in turn help researchers to conduct more reliable observational studies, and contribute to more robust results and interpretations of observational drug studies during a pandemic.
Inhaled corticosteroids (ICS) are anti-inflammatory drugs widely used as regular maintenance medications in asthma and chronic obstructive pulmonary disease (COPD). At the beginning of the COVID-19 pandemic, there was interest in ICS as potential disease-modifying drugs in COVID-19. Several observational studies investigated the effects of ICS on COVID-19 outcomes but found inconsistent results that may be affected by biases.
The aim of this study is to investigate the effects of ICS at different stages of the COVID-19 disease pathway among patients with asthma or COPD, and apply methods of quantitative bias analysis (QBA) to these effect estimates to account for potential biases arising in these estimates of association.
This study will use cohorts of patients with asthma and COPD, respectively, to investigate the association between ICS use compared to use of a non-ICS active comparator and SARS-CoV-2 infection, COVID-19 hospitalisation, and COVID-19 death. All analyses will be conducted separately for an asthma and COPD cohort, and for the first and second wave of COVID-19. CPRD data will be linked to HES data to determine COVID-19 related hospitalisations, and to the ONS death registry to determine COVID-19 related deaths. The association between ICS prescription and each outcome will be estimated using a Cox regression model to calculate hazard ratios and 95% confidence intervals, with confounding adjustment using multivariable regression and propensity scores. Subsequently, QBA will be used to account for potential sources of bias in these estimates of association, including exposure and outcome misclassification, residual confounding and selection bias.
This project will allow an evaluation of whether and how more widespread use of QBA might have allowed researchers to make better inferences using observational data about the role of ICS in COVID-19. Outputs from this project will provide recommendations and tools to help researchers implement QBA in pharmacoepidemiologic studies.
COVID-19 positive test result; hospitalisation with COVID-19; death with COVID-19, as defined in the Exposure, Outcomes and Covariates section.
Ian Douglas - Chief Investigator - London School of Hygiene & Tropical Medicine ( LSHTM )
Marleen Bokern - Corresponding Applicant - London School of Hygiene & Tropical Medicine ( LSHTM )
Anna Schultze - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Christopher Rentsch - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Elizabeth Williamson - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Jacob Hunnicutt - Collaborator - GlaxoSmithKline LLC (USA)
Jennifer Quint - Collaborator - Imperial College London
John Tazare - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Elizabeth Williamson - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
John Tazare - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation