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Controversies around the statistical presentation of data on mRNA-COVID 19 vaccine safety in pregnant women
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.ORCID iD: 0000-0002-5816-4345
Univ Gdansk, Poland; Med Univ Gdansk, Poland.
2022 (English)In: Journal of Reproductive Immunology, ISSN 0165-0378, E-ISSN 1872-7603, Vol. 151, article id 103503Article in journal (Refereed) Published
Abstract [en]

The work entitled "Preliminary Findings of mRNA Covid-19 Vaccine Safety in Pregnant Persons" published on April 21, 2021, in The New England Journal of Medicine, presented data collected from American surveillance systems and registries. However, problems with an unanimous interpretation of those results appeared in the public debate and citing articles. Some stated that the risk of miscarriage in vaccinated women was similar to historical values reported before the vaccines approval. The others stated that risk was highly above-normative in women vaccinated during the first and second trimesters. We found several problems with the statistical treatment/interpretation of the originally presented values: a substantial percentage (up to 95.6%) of missing data, an incorrect denominator used for risk estimation, and too short follow-up that disabled the evaluation of the studys endpoint in numerous participants. Eventually, the Authors published a corrigendum on September 8, 2021, and pointed to updated data. Herein, we explain the statistical controversies raised by the original presentation and stress that analyzing the trade-off between knowledge and confusion brought by the release of incomplete results of such a high social interest, should aid in solving the dilemma of whether to publish preliminary data or none.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD , 2022. Vol. 151, article id 103503
Keywords [en]
COVID-19; mRNA vaccine; Spontaneous abortion; Drug safety; Statistics
National Category
Endocrinology and Diabetes
Identifiers
URN: urn:nbn:se:liu:diva-184517DOI: 10.1016/j.jri.2022.103503ISI: 000776070600002PubMedID: 35276571OAI: oai:DiVA.org:liu-184517DiVA, id: diva2:1654051
Note

Funding Agencies|Swedish Research Council (Vetenskapsradet)Swedish Research Council [2017-04951]; ELLIIT Call C grant

Available from: 2022-04-26 Created: 2022-04-26 Last updated: 2022-05-19

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