Evidence map›Paper›PMID 31036459›Full record

ArticleVaccine2019

Effect of propensity of seeking medical care on the bias of the estimated effectiveness of rotavirus vaccines from studies using a test-negative case-control design.

Michael Haber, Benjamin A Lopman, Jacqueline E Tate, Meng Shi, Umesh D Parashar

Open access · greenAbstract read
In one paragraph

Article in Vaccine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 96% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Michael HaberDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA. Electronic address: mhaber@emory.edu.
Benjamin A LopmanDepartment of Epidemiology, Emory University, Atlanta, GA, USA; Centers for Disease Control and Prevention, Atlanta, GA, USA.
Jacqueline E TateCenters for Disease Control and Prevention, Atlanta, GA, USA.
Meng ShiDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
Umesh D ParasharCenters for Disease Control and Prevention, Atlanta, GA, USA.
Emory University · USCenters for Disease Control and Prevention · US

Funding

Modeling the impact and cost-effectiveness of next-generation rotavirus vaccine strategies in low- and middle-income countriesR01AI112970 · NIAID · YALE UNIVERSITY · PI PITZER, VIRGINIA E · 2015 to 2024
$4.1M
Intramural CDC HHS CC999999
6 · The paper itself

Abstract

backgroundRotavirus is the leading cause of severe diarrhea among children worldwide, and vaccines can reduce morbidity and mortality by 50-98%. The test-negative control (TNC) study design is increasingly used for evaluating the effectiveness of vaccines against rotavirus and other vaccine-preventable diseases. In this study design, symptomatic patients who seek medical care are tested for the pathogen of interest. Those who test positive (negative) are classified as cases (controls).

methodsWe use a probability model to evaluate the bias of estimates of rotavirus vaccine effectiveness (VE) against rotavirus diarrhea resulting in hospitalization in the presence of possible confounding and selection biases due to differences in the propensity of seeking medical care (PSMC) between vaccinated and unvaccinated children.

resultsThe TNC-based VE estimate corrects for confounding bias when the confounder's effects on the probabilities of rotavirus and non-rotavirus related hospitalizations are equal. If this condition is not met, then the estimated VE may be substantially biased. The bias is more severe in low-income countries, where VE is known to be lower. Under our model, differences in PSMC between vaccinated and unvaccinated children do not result in selection bias when the TNC study design is used.

conclusionsIn practice, one can expect the association of PSMC (or other potential confounders) with the probabilities of rotavirus and non-rotavirus related hospitalization to be similar, in which case the confounding effects will only result in small bias in the VE estimate from TNC studies. The results of this work, along with those of our previous paper, confirm the TNC design can be expected to provide reliable estimates of rotavirus VE in both high- and low-income countries.

Indexed as

Patient Acceptance of Health CareResearch DesignSelection BiasVaccine PotencyCase-Control StudiesChildConfounding Factors, EpidemiologicDiarrheaHospitalizationHumansMonte Carlo MethodProbabilityRotavirusRotavirus InfectionsRotavirus VaccinesVaccines, AttenuatedRotavirus VaccinesVaccines, AttenuatedConfounding biasProbability modelsRotavirus vaccinesSelection biasTest-negative designVaccine effectiveness

Identifiers

PMID31036459
PMCPMC8864477
OpenAlexW2941326430

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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.