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Estimating Influenza Vaccine Effectiveness With the Test-Negative Design Using Alternative Control Groups: A Systematic Review and Meta-Analysis.

ABSTRACT: One important assumption in case-control studies is that control selection should be independent of exposure. Nevertheless, it has been hypothesized that virus interference might lead to a correlation between receipt of influenza vaccination and increased risk of infection with other respiratory viruses. We investigated whether such a phenomenon might affect a study design commonly used to estimate influenza vaccine effectiveness (VE). We searched publications in MEDLINE, PubMed, and Web of Science. We identified 12 studies using the test-negative design (2011-2017) that reported VE estimates separately derived by 3 alternative control groups: 1) all patients testing negative for influenza (FLU), VEFLU-; 2) patients who tested positive for other/another respiratory virus (ORV), VEORV+; and 3) patients who tested negative for all viruses in the panel (PAN), VEPAN-. These included VE estimates from 7 countries for all age groups from 2003/2004 to 2013/2014. We observed no difference in vaccination coverage between the ORV-positive and PAN-negative control groups. A total of 63 VEFLU- estimates, 62 VEORV+ estimates, and 33 VEPAN- estimates were extracted. Pooled estimates of the difference in VE (ΔVE) were very similar between groups. In meta-regression, no association was found between the selection of control group and VE estimates. In conclusion, we did not find any differences in VE estimates based on the choice of control group.

SUBMITTER: Feng S

PROVIDER: S-EPMC5860156 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Influenza Vaccine Effectiveness in the Inpatient Setting: Evaluation of Potential Bias in the Test-Negative Design by Use of Alternate Control Groups.

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| S-EPMC8567846 | biostudies-literature

Effectiveness of Trivalent Inactivated Influenza Vaccine in Children Estimated by a Test-Negative Case-Control Design Study Based on Influenza Rapid Diagnostic Test Results.

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Potential of the test-negative design for measuring influenza vaccine effectiveness: a systematic review.

Project description:The test-negative design is a variant of the case-control study being increasingly used to study influenza vaccine effectiveness (VE). In these studies, patients with influenza-like illness are tested for influenza. Vaccine coverage is compared between those testing positive versus those testing negative to estimate VE.We reviewed features in the design, analysis and reporting of 85 published test-negative studies.Studies were identified from PubMed, reference lists and email updates. Study eligibility: All studies using the test-negative design reporting end-of-season estimates were included.Design features that may affect the validity and comparability of reported estimates were reviewed, including setting, study period, source population, case definition, exposure and outcome ascertainment and statistical model.There was considerable variation in the analytic approach, with 68 unique statistical models identified among the studies.Harmonization of analytic approaches may improve the potential for pooling VE estimates.

| S-EPMC4277796 | biostudies-literature

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Project description:Aim: It is important to assess if clinical trial efficacy translates into real-world effectiveness for COVID-19 vaccines. Materials & methods: We conducted a modified test-negative design (TND) to evaluate the real-world effectiveness of three COVID-19 vaccines. We defined cases in two ways: self-reported COVID-19-positive tests, and self-reported positive tests with ≥1 moderate/severe COVID-19 symptom. Results: Any vaccination was associated with a 95% reduction in subsequently reporting a positive COVID-19 test, and a 71% reduction in reporting a positive test and ≥1 moderate/severe symptom. Conclusion: We observed high effectiveness across all three marketed vaccines, both for self-reported positive COVID-19 tests and moderate/severe COVID-19 symptoms. This innovative TND approach can be implemented in future COVID-19 vaccine and treatment real-world effectiveness studies. Clinicaltrials.gov identifier: NCT04368065.

| S-EPMC9504802 | biostudies-literature

Covid-19 Vaccine Effectiveness and the Test-Negative Design.

Project description: Not available

| S-EPMC8451180 | biostudies-literature

The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings.

Project description:BackgroundThe test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting.MethodsWe derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies.ResultsVE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates.ConclusionsThe inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis.

| S-EPMC5025336 | biostudies-literature

A Retrospective Test-Negative Case-Control Study to Evaluate Influenza Vaccine Effectiveness in Preventing Hospitalizations in Children.

Project description:BackgroundVaccination is the primary strategy to reduce influenza burden. Influenza vaccine effectiveness (VE) can vary annually depending on circulating strains.MethodsWe used a test-negative case-control study design to estimate influenza VE against laboratory-confirmed influenza-related hospitalizations among children (aged 6 months-17 years) across 5 influenza seasons in Atlanta, Georgia, from 2012-2013 to 2016-2017. Influenza-positive cases were randomly matched to test-negative controls based on age and influenza season in a 1:1 ratio. We used logistic regression models to compare odds ratios (ORs) of vaccination in cases to controls. We calculated VE as [100% × (1 - adjusted OR)] and computed 95% confidence intervals (CIs) around the estimates.ResultsWe identified 14 596 hospitalizations of children who were tested for influenza using the multiplex respiratory molecular panel; influenza infection was detected in 1017 (7.0%). After exclusions, we included 512 influenza-positive cases and 512 influenza-negative controls. The median age was 5.9 years (interquartile range, 2.7-10.3), 497 (48.5%) were female, 567 (55.4%) were non-Hispanic Black, and 654 (63.9%) children were unvaccinated. Influenza A accounted for 370 (72.3%) of 512 cases and predominated during all 5 seasons. The adjusted VE against influenza-related hospitalizations during 2012-2013 to 2016-2017 was 51.3% (95% CI, 34.8% to 63.6%) and varied by season. Influenza VE was 54.7% (95% CI, 37.4% to 67.3%) for influenza A and 37.1% (95% CI, 2.3% to 59.5%) for influenza B.ConclusionsInfluenza vaccination decreased the risk of influenza-related pediatric hospitalizations by >50% across 5 influenza seasons.

| S-EPMC8599178 | biostudies-literature

Correction of vaccine effectiveness derived from test-negative case-control studies.

Project description:BackgroundDetermining the vaccine effectiveness (VE) is an important part of studying every new vaccine. Test-negative case-control (TNCC) studies have recently been used to determine the VE. However, the estimated VE derived from a TNCC design depends on the test sensitivity and specificity. Herein, a method for correction of the value of VE derived from a TNCC study is presented.MethodsAn analytical method is presented to compute the corrected VE based on the sensitivity and specificity of the diagnostic test utilized. To show the application of the method proposed, a hypothetical TNCC study is presented. In this in silico study, 100 000 individuals referring to a healthcare system for COVID-19-like illness were tested with diagnostic tests with sensitivities of 0.6, 0.8, and 1.0, and specificities ranging from 0.85 to 1.00. A vaccination coverage of 60%, an attack rate of 0.05 for COVID-19 in unvaccinated group, and a true VE of 0.70, were assumed. In this simulation, a COVID-19-like illness with an attack rate of 0.30 could also affect all the studied population regardless of their vaccination status.ResultsThe observed VE ranged from 0.11 (computed for a test sensitivity of 0.60 and specificity of 0.85) to 0.71 (computed for a test sensitivity and specificity of 1.0). The mean computed corrected VE derived from the proposed method was 0.71 (the standard deviation of 0.02).ConclusionsThe observed VE derived from TNCC studies can be corrected easily. An acceptable estimate for VE can be computed regardless of the diagnostic test sensitivity and specificity used in the study.

| S-EPMC10257167 | biostudies-literature

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