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A metaresearch study revealed susceptibility of Covid-19 treatment research to white hat bias: first, do no harm

OBJECTIVE: To investigate the presence of white hat bias in Covid-19 treatment research by evaluating the effects of citation and reporting bias. STUDY DESIGN AND SETTING: Citation bias was investigated by assessing the degree of agreement between evidence provided by a remdesivir randomized control...

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Detalles Bibliográficos
Autor principal: Bellos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997163/
https://www.ncbi.nlm.nih.gov/pubmed/33775812
http://dx.doi.org/10.1016/j.jclinepi.2021.03.020
Descripción
Sumario:OBJECTIVE: To investigate the presence of white hat bias in Covid-19 treatment research by evaluating the effects of citation and reporting bias. STUDY DESIGN AND SETTING: Citation bias was investigated by assessing the degree of agreement between evidence provided by a remdesivir randomized controlled trial and its citing articles. The dissimilarity of outcomes derived from nonrandomized and randomized studies was tested by a meta-analysis of hydroxychloroquine effects on mortality. The differential influence of studies with beneficial over those with neutral results was evaluated by a bibliometric analysis. RESULTS: The articles citing the ACTT-1 remdesivir trial preferentially presented its positive outcomes in 55.83% and its negative outcomes in 6.43% of cases. The hydroxychloroquine indicated no significant effect by randomized studies, but a significant survival benefit by nonrandomized ones. Citation mapping revealed that the study reporting survival benefit from the hydroxychloroquine-azithromycin combination was the most influential, despite subsequent studies reporting potential harmful effects. CONCLUSION: The present study raises concerns about citation bias and a predilection of reporting beneficial over harmful effects in the Covid-19 treatment research, potentially in the context of white hat bias. Preregistration, data sharing and avoidance of selective reporting are crucial to ensure the credibility of future research.