Bokern, Marleen; Rentsch, Christopher T; Quint, Jennifer K; Hunnicutt, Jacob; Douglas, Ian; Schultze, Anna; (2025) Using Quantitative Bias Analysis to Adjust for Misclassification of COVID-19 Outcomes: An Applied Example of Inhaled Corticosteroids and COVID-19 Outcomes. Pharmacoepidemiology and drug safety, 34 (1). e70086-. ISSN 1053-8569 DOI: https://doi.org/10.1002/pds.70086
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Abstract
BACKGROUND: During the pandemic, there was concern that underascertainment of COVID-19 outcomes may impact treatment effect estimation in pharmacoepidemiologic studies. We assessed the impact of outcome misclassification on the association between inhaled corticosteroids (ICS) and COVID-19 hospitalisation and death in the United Kingdom during the first pandemic wave using probabilistic bias analysis (PBA). METHODS: Using data from the Clinical Practice Research Datalink Aurum, we defined a cohort with chronic obstructive pulmonary disease (COPD) on 1 March 2020. We compared the risk of COVID-19 hospitalisation and death among users of ICS/long-acting β-agonist (LABA) and users of LABA/LAMA using inverse probability of treatment weighted (IPTW) logistic regression. We used PBA to assess the impact of non-differential outcome misclassification. We assigned beta distributions to sensitivity and specificity and sampled from these 100 000 times for summary-level and 10 000 times for record-level PBA. Using these values, we simulated outcomes and applied IPTW logistic regression to adjust for confounding and misclassification. Sensitivity analyses excluded ICS + LABA + LAMA (triple therapy) users. RESULTS: Among 161 411 patients with COPD, ICS users had increased odds of COVID-19 hospitalisations and death compared with LABA/LAMA users (OR for COVID-19 hospitalisation 1.59 (95% CI 1.31-1.92); OR for COVID-19 death 1.63 (95% CI 1.26-2.11)). After IPTW and exclusion of people using triple therapy, ORs moved towards the null. All implementations of QBA, both record- and summary-level PBA, modestly shifted the ORs away from the null and increased uncertainty. CONCLUSIONS: We observed increased risks of COVID-19 hospitalisation and death among ICS users compared to LABA/LAMA users. Outcome misclassification was unlikely to change the conclusions of the study, but confounding by indication remains a concern.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology |
Research Centre |
Covid-19 Research EHR Research Group |
PubMed ID | 39776023 |
Elements ID | 234515 |
Official URL | https://doi.org/10.1002/pds.70086 |
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Filename: Bokern-etal-2024-Using-Quantitative-Bias-Analysis-to-Adjust-for-Misclassification-of-COVID-19-Outcomes-An-Applied-Example-of-Inhaled-Corticosteroids-and-COVID-19-Outcomes.pdf
Licence: Creative Commons: Attribution 4.0
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