Variations in Seasonal Influenza Vaccine Effectiveness due to Study Characteristics: A Systematic Review and Meta-analysis of Test-Negative Design Studies

Abstract Background Study characteristics influence vaccine effectiveness (VE) estimation. We examined the influence of some of these on seasonal influenza VE estimates from test-negative design (TND) studies. Methods We systematically searched bibliographic databases and websites for full-text publications of TND studies on VE against laboratory-confirmed seasonal influenza in outpatients after the 2009 pandemic influenza. We followed the Cochrane Handbook for Systematic Reviews of Interventions guidelines. We examined influence of source of vaccination information, respiratory specimen swab time, and covariate adjustment on VE. We calculated pooled adjusted VE against H1N1 and H3N2 influenza subtypes, influenza B, and all influenza using an inverse-variance random-effects model. Results We included 70 full-text articles. Pooled VE against H1N1 and H3N2 influenza subtypes, influenza B, and all influenza was higher for studies that used self-reported vaccination than for those that used medical records. Pooled VE was higher with respiratory specimen collection within ≤7 days vs ≤4 days of symptom onset, but the opposite was observed for H1N1. Pooled VE was higher for studies that adjusted for age but not for medical conditions compared with those that adjusted for both. There was, however, a lack of statistical significance in almost all differences in pooled VE between compared groups. Conclusions The available evidence is not strong enough to conclude that influenza VE from TND studies varies by source of vaccination information, respiratory specimen swab time, or adjustment for age/medical conditions. The evidence is, however, indicative that these factors ought to be considered while designing or evaluating TND studies of influenza VE.

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Evaluating the Effectiveness of Influenza Vaccine in People With At-Risk Medical Conditions: A Test-Negative Design Case-Control Study for the Seasonal Influenza Vaccine Effectiveness II (SIVE II) Project

SSRN Electronic Journal ◽

10.2139/ssrn.3716865 ◽

2020 ◽

Author(s):

Eleftheria Vasileiou ◽

Tanya Englishby ◽

Kimberley Kavanagh ◽

Chris Robertson ◽

Nazir Lone ◽

...

Keyword(s):

At Risk ◽

Influenza Vaccine ◽

Seasonal Influenza ◽

Case Control Study ◽

Case Control ◽

Vaccine Effectiveness ◽

Medical Conditions ◽

Seasonal Influenza Vaccine ◽

Design Case ◽

Control Study

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The Impact of Prior Season Vaccination on Subsequent Influenza Vaccine Effectiveness to Prevent Influenza-related Hospitalizations Over 4 Influenza Seasons in Canada

Clinical Infectious Diseases ◽

10.1093/cid/ciy1009 ◽

2018 ◽

Vol 69 (6) ◽

pp. 970-979 ◽

Cited By ~ 5

Author(s):

M K Nichols ◽

M K Andrew ◽

L Ye ◽

T F Hatchette ◽

A Ambrose ◽

...

Keyword(s):

Influenza Vaccine ◽

Negative Impact ◽

Conditional Logistic Regression ◽

Vaccine Effectiveness ◽

Influenza B ◽

Current Season ◽

Vaccination Recommendations ◽

Vaccine Impact ◽

H3n2 Influenza ◽

The Impact

Abstract Background Recent studies have demonstrated the possibility of negative associations between prior influenza vaccines and subsequent influenza vaccine effectiveness (VE), depending on season and strain. We investigated this association over 4 consecutive influenza seasons (2011–2012 through 2014–2015) in Canada. Methods Using a matched test-negative design, laboratory-confirmed influenza cases and matched test-negative controls admitted to hospitals were enrolled. Patients were stratified into 4 groups according to influenza vaccine history (not vaccinated current and prior season [referent], vaccinated prior season only, vaccinated current season only, and vaccinated both current and prior season). Conditional logistic regression was used to estimate VE; prior vaccine impact was assessed each season for overall effect and effect stratified by age (<65 years, ≥65 years) and type/subtype (A/H1N1, A/H3N2, influenza B). Results Overall, mainly nonsignificant associations were observed. Trends of nonsignificant decreased VE among patients repeatedly vaccinated in both prior and current season relative to the current season only were observed in the A/H3N2-dominant seasons of 2012–2013 and 2014–2015. Conversely, in 2011–2012, during which B viruses circulated, and in 2013–2014, when A/H1N1 circulated, being vaccinated in both seasons tended to result in a high VE in the current season against the dominant circulating subtype. Conclusions Prior vaccine impact on subsequent VE among Canadian inpatients was mainly nonsignificant. Even in circumstances where we observed a trend of negative impact, being repeatedly vaccinated was still more effective than not receiving the current season’s vaccine. These findings favor continuation of annual influenza vaccination recommendations, particularly in older adults. Clinical Trials Registration NCT01517191.

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Concordance of interim and final estimates of influenza vaccine effectiveness: a systematic review

Eurosurveillance ◽

10.2807/1560-7917.es.2016.21.16.30202 ◽

2016 ◽

Vol 21 (16) ◽

Cited By ~ 13

Author(s):

Vivian K Leung ◽

Benjamin J Cowling ◽

Shuo Feng ◽

Sheena G Sullivan

Keyword(s):

Influenza Vaccine ◽

Influenza A ◽

Seasonal Influenza ◽

Vaccine Effectiveness ◽

World Health ◽

Absolute Difference ◽

Influenza Surveillance ◽

Influenza B ◽

Surveillance And Response ◽

Influenza A H1n1

The World Health Organization's Global Influenza Surveillance and Response System meets twice a year to generate a recommendation for the composition of the seasonal influenza vaccine. Interim vaccine effectiveness (VE) estimates provide a preliminary indication of influenza vaccine performance during the season and may be useful for decision making. We reviewed 17 pairs of studies reporting 33 pairs of interim and final estimates using the test-negative design to evaluate whether interim estimates can reliably predict final estimates. We examined features of the study design that may be correlated with interim estimates being substantially different from their final estimates and identified differences related to change in study period and concomitant changes in sample size, proportion vaccinated and proportion of cases. An absolute difference of no more than 10% between interim and final estimates was found for 18 of 33 reported pairs of estimates, including six of 12 pairs reporting VE against any influenza, six of 10 for influenza A(H1N1)pdm09, four of seven for influenza A(H3N2) and two of four for influenza B. While we identified inconsistencies in the methods, the similarities between interim and final estimates support the utility of generating and disseminating preliminary estimates of VE while virus circulation is ongoing.

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Estimating Vaccine-Driven Selection in Seasonal Influenza

Viruses ◽

10.3390/v10090509 ◽

2018 ◽

Vol 10 (9) ◽

pp. 509 ◽

Cited By ~ 2

Author(s):

Frank Wen ◽

Sidney Bell ◽

Trevor Bedford ◽

Sarah Cobey

Keyword(s):

Influenza A ◽

Seasonal Influenza ◽

Size Variation ◽

Vaccine Effectiveness ◽

Epidemiological Surveillance ◽

Influenza B ◽

Human Populations ◽

Type B ◽

Phylogenetic Groups ◽

Spatial Differences

Vaccination could be an evolutionary pressure on seasonal influenza if vaccines reduce the transmission rates of some (“targeted”) strains more than others. In theory, more vaccinated populations should have a lower prevalence of targeted strains compared to less vaccinated populations. We tested for vaccine-induced selection in influenza by comparing strain frequencies between more and less vaccinated human populations. We defined strains in three ways: first as influenza types and subtypes, next as lineages of type B, and finally as clades of influenza A/H3N2. We detected spatial differences partially consistent with vaccine use in the frequencies of subtypes and types and between the lineages of influenza B, suggesting that vaccines do not select strongly among all these phylogenetic groups at regional scales. We did detect a significantly greater frequency of an H3N2 clade with known vaccine escape mutations in more vaccinated countries during the 2014–2015 season, which is consistent with vaccine-driven selection within the H3N2 subtype. Overall, we find more support for vaccine-driven selection when large differences in vaccine effectiveness suggest a strong effect size. Variation in surveillance practices across countries could obscure signals of selection, especially when strain-specific differences in vaccine effectiveness are small. Further examination of the influenza vaccine’s evolutionary effects would benefit from improvements in epidemiological surveillance and reporting.

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Waning Vaccine Effectiveness Against Influenza-Associated Hospitalizations Among Adults, 2015–2016 to 2018–2019, United States Hospitalized Adult Influenza Vaccine Effectiveness Network

Clinical Infectious Diseases ◽

10.1093/cid/ciab045 ◽

2021 ◽

Author(s):

Jill M Ferdinands ◽

Manjusha Gaglani ◽

Emily T Martin ◽

Arnold S Monto ◽

Donald Middleton ◽

...

Keyword(s):

United States ◽

Influenza Vaccine ◽

Influenza A ◽

Vaccine Effectiveness ◽

Influenza B ◽

Influenza A H1n1 ◽

H3n2 Influenza

Abstract We observed decreased effectiveness of influenza vaccine with increasing time since vaccination for prevention of influenza A(H3N2), influenza A(H1N1)pdm09, and influenza B/Yamagata–associated hospitalizations among adults. Maximum vaccine effectiveness (VE) was observed shortly after vaccination, followed by an absolute decline in VE of about 8%–9% per month postvaccination.

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Next generation methodology for updating HA vaccines against emerging human seasonal influenza A(H3N2) viruses

Scientific Reports ◽

10.1038/s41598-020-79590-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

James D. Allen ◽

Ted M. Ross

Keyword(s):

Influenza Virus ◽

Immune Responses ◽

Influenza A ◽

Seasonal Influenza ◽

Influenza Viruses ◽

Next Generation ◽

Virus Infections ◽

Wild Type ◽

Influenza Hemagglutinin ◽

H3n2 Influenza

AbstractWhile vaccines remain the best tool for preventing influenza virus infections, they have demonstrated low to moderate effectiveness in recent years. Seasonal influenza vaccines typically consist of wild-type influenza A and B viruses that are limited in their ability to elicit protective immune responses against co-circulating influenza virus variant strains. Improved influenza virus vaccines need to elicit protective immune responses against multiple influenza virus drift variants within each season. Broadly reactive vaccine candidates potentially provide a solution to this problem, but their efficacy may begin to wane as influenza viruses naturally mutate through processes that mediates drift. Thus, it is necessary to develop a method that commercial vaccine manufacturers can use to update broadly reactive vaccine antigens to better protect against future and currently circulating viral variants. Building upon the COBRA technology, nine next-generation H3N2 influenza hemagglutinin (HA) vaccines were designed using a next generation algorithm and design methodology. These next-generation broadly reactive COBRA H3 HA vaccines were superior to wild-type HA vaccines at eliciting antibodies with high HAI activity against a panel of historical and co-circulating H3N2 influenza viruses isolated over the last 15 years, as well as the ability to neutralize future emerging H3N2 isolates.

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Cross-sectional study of preprints and final journal publications from COVID-19 studies: discrepancies in results reporting and spin in interpretation

BMJ Open ◽

10.1136/bmjopen-2021-051821 ◽

2021 ◽

Vol 11 (7) ◽

pp. e051821

Author(s):

Lisa Bero ◽

Rosa Lawrence ◽

Louis Leslie ◽

Kellia Chiu ◽

Sally McDonald ◽

...

Keyword(s):

Statistical Significance ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Journal Publication ◽

Reporting Practices ◽

Subgroup Analyses ◽

Journal Publications ◽

Study Characteristics ◽

Results Reporting

ObjectiveTo compare results reporting and the presence of spin in COVID-19 study preprints with their finalised journal publications.DesignCross-sectional study.SettingInternational medical literature.ParticipantsPreprints and final journal publications of 67 interventional and observational studies of COVID-19 treatment or prevention from the Cochrane COVID-19 Study Register published between 1 March 2020 and 30 October 2020.Main outcome measuresStudy characteristics and discrepancies in (1) results reporting (number of outcomes, outcome descriptor, measure, metric, assessment time point, data reported, reported statistical significance of result, type of statistical analysis, subgroup analyses (if any), whether outcome was identified as primary or secondary) and (2) spin (reporting practices that distort the interpretation of results so they are viewed more favourably).ResultsOf 67 included studies, 23 (34%) had no discrepancies in results reporting between preprints and journal publications. Fifteen (22%) studies had at least one outcome that was included in the journal publication, but not the preprint; eight (12%) had at least one outcome that was reported in the preprint only. For outcomes that were reported in both preprints and journals, common discrepancies were differences in numerical values and statistical significance, additional statistical tests and subgroup analyses and longer follow-up times for outcome assessment in journal publications.At least one instance of spin occurred in both preprints and journals in 23/67 (34%) studies, the preprint only in 5 (7%), and the journal publications only in 2 (3%). Spin was removed between the preprint and journal publication in 5/67 (7%) studies; but added in 1/67 (1%) study.ConclusionsThe COVID-19 preprints and their subsequent journal publications were largely similar in reporting of study characteristics, outcomes and spin. All COVID-19 studies published as preprints and journal publications should be critically evaluated for discrepancies and spin.

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Molecular Characterization of Seasonal Influenza A and B from Hospitalized Patients in Thailand in 2018–2019

Viruses ◽

10.3390/v13060977 ◽

2021 ◽

Vol 13 (6) ◽

pp. 977

Author(s):

Kobporn Boonnak ◽

Chayasin Mansanguan ◽

Dennis Schuerch ◽

Usa Boonyuen ◽

Hatairat Lerdsamran ◽

...

Keyword(s):

Amino Acid ◽

Influenza A ◽

Seasonal Influenza ◽

Influenza Viruses ◽

Surface Proteins ◽

Antigenic Drift ◽

Influenza B ◽

Receptor Binding Site ◽

Antigenic Sites ◽

Ha Protein

Influenza viruses continue to be a major public health threat due to the possible emergence of more virulent influenza virus strains resulting from dynamic changes in virus adaptability, consequent of functional mutations and antigenic drift in surface proteins, especially hemagglutinin (HA) and neuraminidase (NA). In this study, we describe the genetic and evolutionary characteristics of H1N1, H3N2, and influenza B strains detected in severe cases of seasonal influenza in Thailand from 2018 to 2019. We genetically characterized seven A/H1N1 isolates, seven A/H3N2 isolates, and six influenza B isolates. Five of the seven A/H1N1 viruses were found to belong to clade 6B.1 and were antigenically similar to A/Switzerland/3330/2017 (H1N1), whereas two isolates belonged to clade 6B.1A1 and clustered with A/Brisbane/02/2018 (H1N1). Interestingly, we observed additional mutations at antigenic sites (S91R, S181T, T202I) as well as a unique mutation at a receptor binding site (S200P). Three-dimensional (3D) protein structure analysis of hemagglutinin protein reveals that this unique mutation may lead to the altered binding of the HA protein to a sialic acid receptor. A/H3N2 isolates were found to belong to clade 3C.2a2 and 3C.2a1b, clustering with A/Switzerland/8060/2017 (H3N2) and A/South Australia/34/2019 (H3N2), respectively. Amino acid sequence analysis revealed 10 mutations at antigenic sites including T144A/I, T151K, Q213R, S214P, T176K, D69N, Q277R, N137K, N187K, and E78K/G. All influenza B isolates in this study belong to the Victoria lineage. Five out of six isolates belong to clade 1A3-DEL, which relate closely to B/Washington/02/2009, with one isolate lacking the three amino acid deletion on the HA segment at position K162, N163, and D164. In comparison to the B/Colorado/06/2017, which is the representative of influenza B Victoria lineage vaccine strain, these substitutions include G129D, G133R, K136E, and V180R for HA protein. Importantly, the susceptibility to oseltamivir of influenza B isolates, but not A/H1N1 and A/H3N2 isolates, were reduced as assessed by the phenotypic assay. This study demonstrates the importance of monitoring genetic variation in influenza viruses regarding how acquired mutations could be associated with an improved adaptability for efficient transmission.

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Do longitudinal orthodontic trials use appropriate statistical analyses? A meta-epidemiological study

European Journal of Orthodontics ◽

10.1093/ejo/cjab069 ◽

2021 ◽

Author(s):

Samer Mheissen ◽

Haris Khan ◽

Mohammed Almuzian ◽

Emad Eddin Alzoubi ◽

Nikolaos Pandis

Keyword(s):

Statistical Analysis ◽

Epidemiological Study ◽

Data Extraction ◽

Statistical Significance ◽

Repeated Measure ◽

Exact Test ◽

Optimal Analysis ◽

Study Characteristics ◽

Measure Analysis ◽

Repeated Measure Analysis

Summary Background In orthodontic trials, longitudinal designs with multiple outcome measurements over time are common. The aim of this epidemiological study was to examine whether optimal statistical analysis approaches have been used in longitudinal orthodontic trials. Methods Pubmed was searched in August 2021 for longitudinal orthodontic trials with at least three time points of outcome assessment published in the 2017–20 period. Study selection and data extraction were done independently and in duplicate. The analysis approaches undertaken were tabulated and associations between study characteristics and the use of optimal analysis or not were assessed using Fisher’s exact test and logistic regression. Results One hundred forty-seven out of 563 unique records were deemed eligible for inclusion. Only 26.50% of these trials used an optimal statistical analysis for longitudinal data where the data structure is accounted for. None of the study characteristics except the statistical significance of the results were associated with the appropriateness of the statistical analysis. The odds of significant results in studies with suboptimal analyses were higher than that in studies with optimal longitudinal analyses (odds ratio: 3.48, 95% confidence interval: 1.62, 7.46, P = 0.001). For the studies with optimal analysis, the most frequent test was repeated-measure analysis of variance (RM-ANOVA). The reporting of the statistical analysis section was suboptimal in the majority of the trials. Conclusion Most longitudinal orthodontic trials are not analysed using optimal statistical approaches. Inferences and interpretation of their results are likely to be compromised.

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