Evidence map›Paper›PMID 26474974›Full record

SynthesisBMC infectious diseases2015

Frequency and impact of confounding by indication and healthy vaccinee bias in observational studies assessing influenza vaccine effectiveness: a systematic review.

Cornelius Remschmidt, Ole Wichmann, Thomas Harder

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 6 pooled it
–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

112 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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52 more citing papers are in PubMed but not listed here.

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

3 authors.

Cornelius RemschmidtImmunization Unit, Robert Koch Institute, Seestrasse 10, 13353, Berlin, Germany. remschmidtc@rki.de.
Ole WichmannImmunization Unit, Robert Koch Institute, Seestrasse 10, 13353, Berlin, Germany. wichmanno@rki.de.
Thomas HarderImmunization Unit, Robert Koch Institute, Seestrasse 10, 13353, Berlin, Germany. hardert@rki.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvidence on influenza vaccine effectiveness (VE) is commonly derived from observational studies. However, these studies are prone to confounding by indication and healthy vaccinee bias. We aimed to systematically investigate these two forms of confounding/bias.

methodsSystematic review of observational studies reporting influenza VE and indicators for bias and confounding. We assessed risk of confounding by indication and healthy vaccinee bias for each study and calculated ratios of odds ratios (crude/adjusted) to quantify the effect of confounder adjustment. VE-estimates during and outside influenza seasons were compared to assess residual confounding by healthy vaccinee effects.

resultsWe identified 23 studies reporting on 11 outcomes. Of these, 19 (83 %) showed high risk of bias: Fourteen due to confounding by indication, two for healthy vaccinee bias, and three studies showed both forms of confounding/bias. Adjustment for confounders increased VE on average by 12 % (95 % CI: 7-17 %; all-cause mortality), 9 % (95 % CI: 4-14 %; all-cause hospitalization) and 7 % (95 % CI: 4-10 %; influenza-like illness). Despite adjustment, nine studies showed residual confounding as indicated by significant off-season VE-estimates. These were observed for five outcomes, but more frequently for all-cause mortality as compared to other outcomes (p = 0.03) and in studies which indicated healthy vaccinee bias at baseline (p = 0.01).

conclusionsBoth confounding by indication and healthy vaccinee bias are likely to operate simultaneously in observational studies on influenza VE. Although adjustment can correct for confounding by indication to some extent, the resulting estimates are still prone to healthy vaccinee bias, at least as long as unspecific outcomes like all-cause mortality are used. Therefore, cohort studies using administrative data bases with unspecific outcomes should no longer be used to measure the effects of influenza vaccination.

Indexed as

Cause of DeathDatabases, FactualHospitalizationHumansInfluenza, HumanInfluenza VaccinesOdds RatioRiskVaccinationInfluenza Vaccines

Identifiers

PMID26474974
PMCPMC4609091

What OpenQuestion holds

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Registered trials

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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.