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Trend in Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Serology One Year After Mild and Asymptomatic Coronavirus Disease 2019 (COVID-19): Unpacking Potential Bias in Seroprevalence Studies.

ABSTRACT: A key aim of serosurveillance during the coronavirus disease 2019 (COVID-19) pandemic has been to estimate the prevalence of prior infection, by correcting crude seroprevalence against estimated test performance for polymerase chain reaction (PCR)-confirmed COVID-19. We show that poor generalizability of sensitivity estimates to some target populations may lead to substantial underestimation of case numbers.

SUBMITTER: Bailie CR

PROVIDER: S-EPMC8807225 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Trend in Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Serology One Year After Mild and Asymptomatic Coronavirus Disease 2019 (COVID-19): Unpacking Potential Bias in Seroprevalence Studies.

Bailie Christopher R CR Tseng Yeu Yang YY Carolan Louise L Kirk Martyn D MD Nicholson Suellen S Fox Annette A Sullivan Sheena G SG

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20220801 1

A key aim of serosurveillance during the coronavirus disease 2019 (COVID-19) pandemic has been to estimate the prevalence of prior infection, by correcting crude seroprevalence against estimated test performance for polymerase chain reaction (PCR)-confirmed COVID-19. We show that poor generalizability of sensitivity estimates to some target populations may lead to substantial underestimation of case numbers. ...[more]

PMID: 35026841

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Project description:Background and objectiveObservational studies may provide valuable evidence on real-world causal effects of drug effectiveness in patients with coronavirus disease 2019 (COVID-19). As patients are usually observed from hospital admission to discharge and drug initiation starts during hospitalization, advanced statistical methods are needed to account for time-dependent drug exposure, confounding and competing events. Our objective is to evaluate the observational studies on the three common methodological pitfalls in time-to-event analyses: immortal time bias, confounding bias and competing risk bias.MethodsWe performed a systematic literature search on 23 October 2020, in the PubMed database to identify observational cohort studies that evaluated drug effectiveness in hospitalized patients with COVID-19. We included articles published in four journals: British Medical Journal, New England Journal of Medicine, Journal of the American Medical Association and The Lancet as well as their sub-journals.ResultsOverall, out of 255 articles screened, 11 observational cohort studies on treatment effectiveness with drug exposure-outcome associations were evaluated. All studies were susceptible to one or more types of bias in the primary study analysis. Eight studies had a time-dependent treatment. However, the hazard ratios were not adjusted for immortal time in the primary analysis. Even though confounders presented at baseline have been addressed in nine studies, time-varying confounding caused by time-varying treatment exposure and clinical variables was less recognized. Only one out of 11 studies addressed competing event bias by extending follow-up beyond patient discharge.ConclusionsIn the observational cohort studies on drug effectiveness for treatment of COVID-19 published in four high-impact journals, the methodological biases were concerningly common. Appropriate statistical tools are essential to avoid misleading conclusions and to obtain a better understanding of potential treatment effects.

Dataset Information

Trend in Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Serology One Year After Mild and Asymptomatic Coronavirus Disease 2019 (COVID-19): Unpacking Potential Bias in Seroprevalence Studies.

Publications

Trend in Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Serology One Year After Mild and Asymptomatic Coronavirus Disease 2019 (COVID-19): Unpacking Potential Bias in Seroprevalence Studies.

Similar Datasets

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