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Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias
It is widely believed that influenza (flu) vaccination of the elderly reduces all-cause mortality, yet randomized trials for assessing vaccine effectiveness are not feasible and the observational research has been controversial. Efforts to differentiate vaccine effectiveness from selection bias have...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2728831/ https://www.ncbi.nlm.nih.gov/pubmed/19625341 http://dx.doi.org/10.1093/aje/kwp173 |
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author | Fireman, Bruce Lee, Janelle Lewis, Ned Bembom, Oliver van der Laan, Mark Baxter, Roger |
author_facet | Fireman, Bruce Lee, Janelle Lewis, Ned Bembom, Oliver van der Laan, Mark Baxter, Roger |
author_sort | Fireman, Bruce |
collection | PubMed |
description | It is widely believed that influenza (flu) vaccination of the elderly reduces all-cause mortality, yet randomized trials for assessing vaccine effectiveness are not feasible and the observational research has been controversial. Efforts to differentiate vaccine effectiveness from selection bias have been problematic. The authors examined mortality before, during, and after 9 flu seasons in relation to time-varying vaccination status in an elderly California population in which 115,823 deaths occurred from 1996 to 2005, including 20,484 deaths during laboratory-defined flu seasons. Vaccine coverage averaged 63%; excess mortality when the flu virus was circulating averaged 7.8%. In analyses that omitted weeks when flu circulated, the odds ratio measuring the vaccination-mortality association increased monotonically from 0.34 early in November to 0.56 in January, 0.67 in April, and 0.76 in August. This reflects the trajectory of selection effects in the absence of flu. In analyses that included weeks with flu and adjustment for selection effects, flu season multiplied the odds ratio by 0.954. The corresponding vaccine effectiveness estimate was 4.6% (95% confidence interval: 0.7, 8.3). To differentiate vaccine effects from selection bias, the authors used logistic regression with a novel case-centered specification that may be useful in other population-based studies when the exposure-outcome association varies markedly over time. |
format | Text |
id | pubmed-2728831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27288312009-08-20 Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias Fireman, Bruce Lee, Janelle Lewis, Ned Bembom, Oliver van der Laan, Mark Baxter, Roger Am J Epidemiol Practice of Epidemiology It is widely believed that influenza (flu) vaccination of the elderly reduces all-cause mortality, yet randomized trials for assessing vaccine effectiveness are not feasible and the observational research has been controversial. Efforts to differentiate vaccine effectiveness from selection bias have been problematic. The authors examined mortality before, during, and after 9 flu seasons in relation to time-varying vaccination status in an elderly California population in which 115,823 deaths occurred from 1996 to 2005, including 20,484 deaths during laboratory-defined flu seasons. Vaccine coverage averaged 63%; excess mortality when the flu virus was circulating averaged 7.8%. In analyses that omitted weeks when flu circulated, the odds ratio measuring the vaccination-mortality association increased monotonically from 0.34 early in November to 0.56 in January, 0.67 in April, and 0.76 in August. This reflects the trajectory of selection effects in the absence of flu. In analyses that included weeks with flu and adjustment for selection effects, flu season multiplied the odds ratio by 0.954. The corresponding vaccine effectiveness estimate was 4.6% (95% confidence interval: 0.7, 8.3). To differentiate vaccine effects from selection bias, the authors used logistic regression with a novel case-centered specification that may be useful in other population-based studies when the exposure-outcome association varies markedly over time. Oxford University Press 2009-09-01 2009-07-22 /pmc/articles/PMC2728831/ /pubmed/19625341 http://dx.doi.org/10.1093/aje/kwp173 Text en American Journal of Epidemiology © 2009 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Practice of Epidemiology Fireman, Bruce Lee, Janelle Lewis, Ned Bembom, Oliver van der Laan, Mark Baxter, Roger Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title | Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title_full | Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title_fullStr | Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title_full_unstemmed | Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title_short | Influenza Vaccination and Mortality: Differentiating Vaccine Effects From Bias |
title_sort | influenza vaccination and mortality: differentiating vaccine effects from bias |
topic | Practice of Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2728831/ https://www.ncbi.nlm.nih.gov/pubmed/19625341 http://dx.doi.org/10.1093/aje/kwp173 |
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