Evidence map›Paper›PMID 28718786›Full record

ReviewVaccines2017

Egg-Independent Influenza Vaccines and Vaccine Candidates.

Ilaria Manini, Claudia Maria Trombetta, Giacomo Lazzeri, Teresa Pozzi, Stefania Rossi, Emanuele Montomoli

Abstract readReview
In one paragraph

Review in Vaccines, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed.

  1. Review
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  14. PeerJ · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ilaria ManiniDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. ilaria.manini@unisi.it.
Claudia Maria TrombettaDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. trombetta@unisi.it.
Giacomo LazzeriDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. giacomo.lazzeri@unisi.it.
Teresa PozziDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. teresa.pozzi@unisi.it.
Stefania RossiDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. stefania.rossi@unisi.it.
Emanuele MontomoliDepartment of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy. emanuele.montomoli@unisi.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccination remains the principal way to control seasonal infections and is the most effective method of reducing influenza-associated morbidity and mortality. Since the 1940s, the main method of producing influenza vaccines has been an egg-based production process. However, in the event of a pandemic, this method has a significant limitation, as the time lag from strain isolation to final dose formulation and validation is six months. Indeed, production in eggs is a relatively slow process and production yields are both unpredictable and highly variable from strain to strain. In particular, if the next influenza pandemic were to arise from an avian influenza virus, and thus reduce the egg-laying hen population, there would be a shortage of embryonated eggs available for vaccine manufacturing. Although the production of egg-derived vaccines will continue, new technological developments have generated a cell-culture-based influenza vaccine and other more recent platforms, such as synthetic influenza vaccines.

Indexed as

cell-culturesynthetic influenza vaccinevaccination

Identifiers

PMID28718786
PMCPMC5620549

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.