After adjusting for bias in meta-analysis seasonal influenza vaccine remains effective in community-dwelling elderly. Darvishian, M., Gefenaite, G., Turner, R., M., Pechlivanoglou, P., Van Der Hoek, W., Van Den Heuvel, E., R., & Hak, E. Journal of Clinical Epidemiology, 67(7):734-744, Elsevier Inc, 2014. ![After adjusting for bias in meta-analysis seasonal influenza vaccine remains effective in community-dwelling elderly [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper abstract bibtex Objective To compare the performance of the bias-adjusted meta-analysis to the conventional meta-analysis assessing seasonal influenza vaccine effectiveness among community-dwelling elderly aged 60 years and older. Study Design and Setting Systematic literature search revealed 14 cohort studies that met inclusion and exclusion criteria. Laboratory-confirmed influenza, influenza-like illness, hospitalization from influenza and/or pneumonia, and all-cause mortality were study outcomes. Potential biases were identified using bias checklists. The magnitude and uncertainty of biases were assessed by expert opinion. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random effects model. Results After incorporating biases, overall effect estimates regressed slightly toward no effect, with the largest relative difference between conventional and bias-adjusted ORs for laboratory-confirmed influenza (OR, 0.18; 95% CI: 0.01, 3.00 vs. OR, 0.23; 95% CI: 0.03, 2.04). In most of the studies, CIs widened reflecting uncertainties about the biases. The between-study heterogeneity reduced considerably with the largest reduction for all-cause mortality (I2 = 4%, P = 0.39 vs. I2 = 91%, P < 0.01). Conclusion This case study showed that after addressing potential biases influenza vaccine was still estimated effective in preventing hospitalization from influenza and/or pneumonia and all-cause mortality. Increasing the number of assessors and incorporating empirical evidence might improve the new bias-adjustment method. © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
@article{
title = {After adjusting for bias in meta-analysis seasonal influenza vaccine remains effective in community-dwelling elderly},
type = {article},
year = {2014},
identifiers = {[object Object]},
keywords = {Vaccine effectiveness},
pages = {734-744},
volume = {67},
websites = {http://dx.doi.org/10.1016/j.jclinepi.2014.02.009},
publisher = {Elsevier Inc},
id = {381cef97-1124-3c22-a2cf-77e38a2efa04},
created = {2015-09-14T17:37:38.000Z},
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last_modified = {2015-09-14T21:03:56.000Z},
tags = {NEW1,Original,VDECVE},
read = {false},
starred = {false},
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citation_key = {Darvishian2014},
source_type = {article},
abstract = {Objective To compare the performance of the bias-adjusted meta-analysis to the conventional meta-analysis assessing seasonal influenza vaccine effectiveness among community-dwelling elderly aged 60 years and older. Study Design and Setting Systematic literature search revealed 14 cohort studies that met inclusion and exclusion criteria. Laboratory-confirmed influenza, influenza-like illness, hospitalization from influenza and/or pneumonia, and all-cause mortality were study outcomes. Potential biases were identified using bias checklists. The magnitude and uncertainty of biases were assessed by expert opinion. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random effects model. Results After incorporating biases, overall effect estimates regressed slightly toward no effect, with the largest relative difference between conventional and bias-adjusted ORs for laboratory-confirmed influenza (OR, 0.18; 95% CI: 0.01, 3.00 vs. OR, 0.23; 95% CI: 0.03, 2.04). In most of the studies, CIs widened reflecting uncertainties about the biases. The between-study heterogeneity reduced considerably with the largest reduction for all-cause mortality (I2 = 4%, P = 0.39 vs. I2 = 91%, P < 0.01). Conclusion This case study showed that after addressing potential biases influenza vaccine was still estimated effective in preventing hospitalization from influenza and/or pneumonia and all-cause mortality. Increasing the number of assessors and incorporating empirical evidence might improve the new bias-adjustment method. © 2014 The Authors. Published by Elsevier Inc. All rights reserved.},
bibtype = {article},
author = {Darvishian, Maryam and Gefenaite, Giedre and Turner, Rebecca M. and Pechlivanoglou, Petros and Van Der Hoek, Wim and Van Den Heuvel, Edwin R. and Hak, Eelko},
journal = {Journal of Clinical Epidemiology},
number = {7}
}
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Study Design and Setting Systematic literature search revealed 14 cohort studies that met inclusion and exclusion criteria. Laboratory-confirmed influenza, influenza-like illness, hospitalization from influenza and/or pneumonia, and all-cause mortality were study outcomes. Potential biases were identified using bias checklists. The magnitude and uncertainty of biases were assessed by expert opinion. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random effects model. Results After incorporating biases, overall effect estimates regressed slightly toward no effect, with the largest relative difference between conventional and bias-adjusted ORs for laboratory-confirmed influenza (OR, 0.18; 95% CI: 0.01, 3.00 vs. OR, 0.23; 95% CI: 0.03, 2.04). In most of the studies, CIs widened reflecting uncertainties about the biases. The between-study heterogeneity reduced considerably with the largest reduction for all-cause mortality (I2 = 4%, P = 0.39 vs. I2 = 91%, P < 0.01). Conclusion This case study showed that after addressing potential biases influenza vaccine was still estimated effective in preventing hospitalization from influenza and/or pneumonia and all-cause mortality. Increasing the number of assessors and incorporating empirical evidence might improve the new bias-adjustment method. © 2014 The Authors. Published by Elsevier Inc. All rights reserved.","bibtype":"article","author":"Darvishian, Maryam and Gefenaite, Giedre and Turner, Rebecca M. and Pechlivanoglou, Petros and Van Der Hoek, Wim and Van Den Heuvel, Edwin R. and Hak, Eelko","journal":"Journal of Clinical Epidemiology","number":"7","bibtex":"@article{\n title = {After adjusting for bias in meta-analysis seasonal influenza vaccine remains effective in community-dwelling elderly},\n type = {article},\n year = {2014},\n identifiers = {[object Object]},\n keywords = {Vaccine effectiveness},\n pages = {734-744},\n volume = {67},\n websites = {http://dx.doi.org/10.1016/j.jclinepi.2014.02.009},\n publisher = {Elsevier Inc},\n id = {381cef97-1124-3c22-a2cf-77e38a2efa04},\n created = {2015-09-14T17:37:38.000Z},\n file_attached = {true},\n profile_id = {7a0fec24-6ec6-312f-956e-f210abd2cdb7},\n group_id = {943817ab-6073-3383-a1c5-963a6e7efbea},\n last_modified = {2015-09-14T21:03:56.000Z},\n tags = {NEW1,Original,VDECVE},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Darvishian2014},\n source_type = {article},\n abstract = {Objective To compare the performance of the bias-adjusted meta-analysis to the conventional meta-analysis assessing seasonal influenza vaccine effectiveness among community-dwelling elderly aged 60 years and older. 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The between-study heterogeneity reduced considerably with the largest reduction for all-cause mortality (I2 = 4%, P = 0.39 vs. I2 = 91%, P < 0.01). Conclusion This case study showed that after addressing potential biases influenza vaccine was still estimated effective in preventing hospitalization from influenza and/or pneumonia and all-cause mortality. Increasing the number of assessors and incorporating empirical evidence might improve the new bias-adjustment method. © 2014 The Authors. Published by Elsevier Inc. 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