Evidence map›Paper›PMID 30422840›Full record

ArticleMedical care2019

Assessing Residual Bias in Estimating Influenza Vaccine Effectiveness: Comparison of High-dose Versus Standard-dose Vaccines.

Anne M Butler, J Bradley Layton, Whitney S Krueger, Abhijit V Kshirsagar, Leah J McGrath

Abstract read
In one paragraph

Article in Medical care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Public preference for COVID-19 vaccines in China: A discrete choice experiment.Health expectations : an international journal of public participation in health care and health policy · 2020
    Article
  7. Article
  8. Comparative Effectiveness of High-Dose Versus Standard-Dose Influenza Vaccine Among Patients Receiving Maintenance Hemodialysis.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2020
    Article
  9. Influenza vaccine effectiveness against laboratory-confirmed influenza in hospitalised adults aged 60 years or older, Valencia Region, Spain, 2017/18 influenza season.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019
    Observational
  10. 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.

Anne M ButlerDepartments of Internal Medicine, Division of Infectious Diseases.
J Bradley LaytonDepartment of Epidemiology, University of North Carolina, Chapel Hill.
Whitney S KruegerRTI Health Solutions, Research Triangle Park.
Abhijit V KshirsagarDepartment of Medicine, Division of Nephrology and Hypertension, University of North Carolina, Chapel Hill.
Leah J McGrathNoviSci Durham, NC.

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational & Clinical Sciences Institute (NC TraCS)UL1TR001111 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$43.9M
NCATS NIH HHS UL1 TR001111NCATS NIH HHS UL1 TR002489
6 · The paper itself

Abstract

backgroundEstimating influenza vaccine effectiveness using an unvaccinated comparison group may result in biased effect estimates.

objectivesTo explore the reduction of confounding bias in an active comparison of high-dose versus standard-dose influenza vaccines, as compared with vaccinated versus unvaccinated comparisons.

methodsUsing Medicare data from the United States end-stage renal disease program (2009-2013), we compared the risk of all-cause mortality among recipients of high-dose vaccine (HDV) versus standard-dose vaccine (SDV), HDV versus no vaccine, and SDV versus no vaccine. To quantify confounding bias, analyses were restricted to the preinfluenza season, when the protective effect of vaccination should not yet be observed. We estimated the standardized mortality ratio-weighted cumulative incidence functions using Kaplan-Meier methods and calculated risk ratios (RRs) and risk differences between groups.

resultsAmong 350,921 eligible patients contributing 825,642 unique patient preinfluenza seasons, 0.8% received HDV, 70.5% received SDV, and 28.7% remained unvaccinated. Comparisons with unvaccinated patients yielded spurious decreases in mortality risk during the preinfluenza period, for HDV versus none [RR, 0.60; 95% confidence interval (CI), 0.51-0.70)] and SDV versus none (RR, 0.72; 95% CI, 0.70-0.75). The effect estimate was attenuated in the HDV versus SDV comparison (RR, 0.89; 95% CI, 0.77-1.03). Estimates on the absolute scale followed a similar pattern.

conclusionsThe HDV versus SDV comparison yielded less-biased estimates of the all-cause mortality before influenza season compared to those with nonuser comparison groups. Vaccine effectiveness and safety researchers should consider the active comparator design to reduce bias due to differences in underlying health status between vaccinated and unvaccinated individuals.

Indexed as

BiasAgedFemaleHumansInfluenza, HumanInfluenza VaccinesInsurance Claim ReviewKidney Failure, ChronicMaleMedicareMiddle AgedSeasonsUnited StatesVaccinationInfluenza Vaccines

Identifiers

PMID30422840
PMCPMC7310582

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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.