ArticleStatistics in medicine2021
Avoiding bias in self-controlled case series studies of coronavirus disease 2019.
Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Risk of cardiovascular events following hemodialysis initiation: a self-controlled case series study.Kidney research and clinical practice · 2026Article
- Risk of stroke following SARS-CoV-2 infection in a nationwide self-controlled case series study in qatar.Scientific reports · 2026Observational
- Risk of myocardial infarction and stroke following bloodstream infection: a population-based self-controlled case series.Open heart · 2025Article
- Risk of neurologic or immune-mediated adverse events after COVID-19 diagnosis in the United States.PloS one · 2025Article
- Association between immune checkpoint inhibitors and cardiovascular risks: a nationwide self-controlled case series study.American journal of cancer research · 2025Article
- Risk of arrhythmias following COVID-19: nationwide self-controlled case series and matched cohort study.European heart journal open · 2023Article
- Article
- Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study.The Lancet regional health. Europe · 2023Article
- Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people in England.Nature communications · 2023Article
- An Increased Risk for Ischemic Stroke in the Short-Term Period following COVID-19 Infection: A Nationwide Population-Based Study.Neuroepidemiology · 2023Article
- Risk of thrombocytopenic, haemorrhagic and thromboembolic disorders following COVID-19 vaccination and positive test: a self-controlled case series analysis in Wales.Scientific reports · 2022Article
- Thromboembolic events and hemorrhagic stroke after mRNA (BNT162b2) and inactivated (CoronaVac) covid-19 vaccination: A self-controlled case series study.EClinicalMedicine · 2022Article
- A modified self-controlled case series method for event-dependent exposures and high event-related mortality, with application to COVID-19 vaccine safety.Statistics in medicine · 2022Article
- Risks of deep vein thrombosis, pulmonary embolism, and bleeding after covid-19: nationwide self-controlled cases series and matched cohort study.BMJ (Clinical research ed.) · 2022Article
- Association between covid-19 vaccination, SARS-CoV-2 infection, and risk of immune mediated neurological events: population based cohort and self-controlled case series analysis.BMJ (Clinical research ed.) · 2022Article
- COVID-19 and Risk of Acute Ischemic Stroke Among Medicare Beneficiaries Aged 65 Years or Older: Self-Controlled Case Series Study.Neurology · 2022Article
- Avoiding bias in self-controlled case series studies of coronavirus disease 2019.Statistics in medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Many studies, including self-controlled case series (SCCS) studies, are being undertaken to quantify the risks of complications following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). One such SCCS study, based on all COVID-19 cases arising in Sweden over an 8-month period, has shown that SARS-CoV-2 infection increases the risks of AMI and ischemic stroke. Some features of SARS-CoV-2 infection and COVID-19, present in this study and likely in others, complicate the analysis and may introduce bias. In the present paper we describe these features, and explore the biases they may generate. Motivated by data-based simulations, we propose methods to reduce or remove these biases.
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Registered trials
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