Maryam Darvishian1, Giedre Gefenaite1, Rebecca M Turner2, Petros Pechlivanoglou3, Wim Van der Hoek4, Edwin R Van den Heuvel5, Eelko Hak6. 1. Unit of PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus 30 001, 9700 RB Groningen, the Netherlands. 2. Medical Research Council Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge. UK. CB2 0SR. 3. Unit of PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV, Groningen, The Netherlands; Toronto Health Economics and Technology Assessment collaborative, University of Toronto, 144 College st. Rm:685, Toronto ON M5S3M2, Canada. 4. Department of Respiratory Infections of the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands. 5. Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus 30 001, 9700 RB Groningen, the Netherlands. 6. Unit of PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus 30 001, 9700 RB Groningen, the Netherlands. Electronic address: e.hak@rug.nl.
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 (I(2) = 4%, P = 0.39 vs. I(2) = 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.
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 (I(2) = 4%, P = 0.39 vs. I(2) = 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.
Authors: Jung Yeon Heo; Joon Young Song; Ji Yun Noh; Min Joo Choi; Jin Gu Yoon; Saem Na Lee; Hee Jin Cheong; Woo Joo Kim Journal: Hum Vaccin Immunother Date: 2017-12-19 Impact factor: 3.452
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