Validity of Routine Health Data To Identify Safety Outcomes of Interest For Covid-19 Vaccines and Therapeutics in the Context of the Emerging Pandemic: A Comprehensive Literature Review

Abstract

Introduction Regulatory guidance encourages transparent reporting of information on the quality and validity of electronic health record data being used to generate real-world benefit-risk evidence for vaccines and therapeutics. We aimed to provide an overview of the availability of validated diagnostic algorithms for selected safety endpoints for Coronavirus disease 2019 (COVID-19) vaccines and therapeutics in the context of the emerging pandemic prior to December 2020. Methods We reviewed the literature up to December 2020 to identify validation studies for various safety events of interest, including myocardial infarction, arrhythmia, myocarditis, acute cardiac injury, vasculitis/vasculopathy, venous thromboembolism, stroke, respiratory distress syndrome (RDS), pneumonitis, cytokine release syndrome (CRS), multiple organ dysfunction syndrome, and renal failure. We included studies published between 2015 and 2020 that were considered high quality assessed with QUADAS and that reported positive predictive values (PPVs). Results Out of 43 identified studies, we found that diagnostic algorithms for cardiovascular outcomes were supported by the highest number of validation studies (n=17). Accurate algorithms are available for myocardial infarction (median PPV 80%; IQR 22%), arrhythmia (PPV range >70%), venous thromboembolism (median PPV: 73%) and ischaemic stroke (PPV range ≥85%). We found a lack of validation studies for less common respiratory and cardiac safety outcomes of interest (eg, pneumonitis and myocarditis), as well as for COVID-specific complications (CRS, RDS). Conclusion There is a need for better understanding of barriers to conducting validation studies, including data governance restrictions. Regulatory guidance should promote embedding validation within real-world EHR research used for decision-making.