Evidence map›Paper›PMID 38932308›Full record

ReviewVaccines2024

A Review of Protein-Based COVID-19 Vaccines: From Monovalent to Multivalent Formulations.

Gui Qian, Cuige Gao, Miaomiao Zhang, Yuanxin Chen, Liangzhi Xie

Abstract readReview
In one paragraph

Review in Vaccines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
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

5 authors.

Gui QianBeijing Engineering Research Center of Protein and Antibody, Sinocelltech Ltd., Beijing 100176, China.
Cuige GaoBeijing Engineering Research Center of Protein and Antibody, Sinocelltech Ltd., Beijing 100176, China.
Miaomiao ZhangBeijing Engineering Research Center of Protein and Antibody, Sinocelltech Ltd., Beijing 100176, China.
Yuanxin ChenBeijing Engineering Research Center of Protein and Antibody, Sinocelltech Ltd., Beijing 100176, China.
Liangzhi XieBeijing Engineering Research Center of Protein and Antibody, Sinocelltech Ltd., Beijing 100176, China.ORCID 0000-0003-4504-7622

Funding

National Key Research and Development Program of China 2023YFC3042100, 2022YFC0870600
6 · The paper itself

Abstract

The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in the COVID-19 pandemic, has profoundly impacted global healthcare systems and the trajectory of economic advancement. As nations grapple with the far-reaching consequences of this unprecedented health crisis, the administration of COVID-19 vaccines has proven to be a pivotal strategy in managing this crisis. Protein-based vaccines have garnered significant attention owing to their commendable safety profile and precise immune targeting advantages. Nonetheless, the unpredictable mutations and widespread transmission of SARS-CoV-2 have posed challenges for vaccine developers and governments worldwide. Monovalent and multivalent vaccines represent two strategies in COVID-19 vaccine development, with ongoing controversy surrounding their efficacy. This review concentrates on the development of protein-based COVID-19 vaccines, specifically addressing the transition from monovalent to multivalent formulations, and synthesizes data on vaccine manufacturers, antigen composition, pivotal clinical study findings, and other features that shape their distinct profiles and overall effectiveness. Our hypothesis is that multivalent vaccine strategies for COVID-19 could offer enhanced capability with broad-spectrum protection.

Indexed as

COVID-19 vaccinesmonovalent vaccinesmultivalent vaccinesprotein-based vaccines

Identifiers

PMID38932308
PMCPMC11209593

What OpenQuestion holds

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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.