ArticleEuropean journal of pediatrics2018
Effectiveness of inactivated quadrivalent influenza vaccine in the 2015/2016 season as assessed in both a test-negative case-control study design and a traditional case-control study design.
Article in European journal of pediatrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Test-negative Controls to Monitor Vaccine Effectiveness: A Systematic Review of Methodology.Epidemiology (Cambridge, Mass.) · 2020Pooled it
- Effectiveness of seasonal influenza vaccine in elementary and middle schools: a 10-year follow-up investigation.BMC infectious diseases · 2022Article
- Article
- Article
- Effectiveness of Partial and Full Influenza Vaccination Among Children Aged <9 Years in Hong Kong, 2011-2019.The Journal of infectious diseases · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Both traditional case-control studies (TCCSs) and test-negative case-control studies (TNCCSs) are commonly used to assess influenza vaccine effectiveness (VE). To compensate for the fact that observational studies are susceptible to bias, we combined both methods to assess VE in one geographical area during the 2015/2016 season, when influenza A (H1N1)pdm was dominant. Our TNCCS covered 331 children aged 6 months to 15 years who visited our hospital with fever, including 182 with influenza, and our TCCS covered 812 pediatric outpatients aged 6 months to 15 years, including 214 with influenza. Influenza infection and vaccination history were reviewed, and VE was calculated as (1 - odds ratio) × 100. In the TNCCS, VE against influenza A was 68% (95% CI 47-81) overall, and 70% (48-83) for those given two doses; against influenza B, VE was 37% (- 12-64) overall and 49% (2-74) for two doses. In the TCCS, VE against influenza A was 44% (15-63) overall and 44% (13-64) for two doses, and VE against influenza B was 24% (- 19-52) overall and 41% (3-64) for two doses.
conclusionBoth studies confirmed significant VE against influenza A, significant two-dose VE against influenza B, and better two-dose VE than one-dose VE. What is Known: • Influenza vaccine effectiveness (VE) varies from year to year. • Observational studies are conventionally used for VE assessment. However, they are inherently susceptible to bias and confounding. What is New: • This is the first report of influenza VE assessment using more than one observational study and performed in a specific area during the same season. • VE estimates obtained in our traditional case-control study were lower than those in our test-negative case-control study, but both studies found significant VE against influenza.
Indexed as
Identifiers
29680993What OpenQuestion holds
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.