ReviewHuman vaccines & immunotherapeutics2018
The establishment of surrogates and correlates of protection: Useful tools for the licensure of effective influenza vaccines?
Review in Human vaccines & immunotherapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparative Immunogenicity of Enhanced Seasonal Influenza Vaccines in Older Adults: A Systematic Review and Meta-analysis.The Journal of infectious diseases · 2019Pooled it
- An mRNA-based seasonal influenza vaccine in adults: Results of two phase 3 randomized clinical trials and correlate of protection analysis of hemagglutination inhibition titers.Human vaccines & immunotherapeutics · 2025Trial
- Effect of Repeat Vaccination on Immunogenicity of Quadrivalent Cell-Culture and Recombinant Influenza Vaccines Among Healthcare Personnel Aged 18-64 Years: A Randomized, Open-Label Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Trial
- Induction of Cross-Reactive Hemagglutination Inhibiting Antibody and Polyfunctional CD4+ T-Cell Responses by a Recombinant Matrix-M-Adjuvanted Hemagglutinin Nanoparticle Influenza Vaccine.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Trial
- Trial
- T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.Archives of microbiology · 2026Review
- Article
- Development of an intranasal, universal influenza vaccine in an EU-funded public-private partnership: the FLUniversal consortium.Frontiers in immunology · 2025Article
- Seasonal influenza vaccines: Variability of immune responses to B lineage viruses.Human vaccines & immunotherapeutics · 2024Review
- Article
- A Recombinant Mosaic HAs Influenza Vaccine Elicits Broad-Spectrum Immune Response and Protection of Influenza a Viruses.Vaccines · 2024Article
- Review
- Article
- Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity.Vaccines · 2022Article
- Sex-specific effects of aging on humoral immune responses to repeated influenza vaccination in older adults.NPJ vaccines · 2021Article
- Vaccination of older adults: Influenza, pneumococcal disease, herpes zoster, COVID-19 and beyond.Immunity & ageing : I & A · 2021Review
- The evolution and future of influenza pandemic preparedness.Experimental & molecular medicine · 2021Review
- The Relationship Between the Global Burden of Influenza From 2017 to 2019 and COVID-19: Descriptive Epidemiological Assessment.JMIR public health and surveillance · 2021Article
- Aging and Options to Halt Declining Immunity to Virus Infections.Frontiers in immunology · 2021Review
- Navigating the Quagmire: Comparison and Interpretation of COVID-19 Vaccine Phase 1/2 Clinical Trials.Vaccines · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The search for a test that can predict vaccine efficacy is an important part of any vaccine development program. Although regulators hesitate to acknowledge any test as a true 'correlate of protection', there are many precedents for defining 'surrogate' assays. Surrogates can be powerful tools for vaccine optimization, licensure, comparisons between products and development of improved products. When such tests achieve 'reference' status however, they can inadvertently become barriers to new technologies that do not work the same way as existing vaccines. This is particularly true when these tests are based upon circularly-defined 'reference' or, even worse, proprietary reagents. The situation with inactivated influenza vaccines is a good example of this phenomenon. The most frequently used tests to define vaccine-induced immunity are all serologic assays: hemagglutination inhibition (HI), single radial hemolysis (SRH) and microneutralization (MN). The first two, and particularly the HI assay, have achieved reference status and criteria have been established in many jurisdictions for their use in licensing new vaccines and to compare the performance of different vaccines. However, all of these assays are based on biological reagents that are notoriously difficult to standardize and can vary substantially by geography, by chance (i.e. developing reagents in eggs that may not antigenitically match wild-type viruses) and by intention (ie: choosing reagents that yield the most favorable results). This review describes attempts to standardize these assays to improve their performance as surrogates, the dangers of over-reliance on 'reference' serologic assays, the ways that manufacturers can exploit the existing regulatory framework to make their products 'look good' and the implications of this long-established system for the introduction of novel influenza vaccines.
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Registered trials
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.