tetano
Editor, Senior Moderator
Vaccine. 2017 Nov 1;35(46):6269-6274. doi: 10.1016/j.vaccine.2017.09.084. Epub 2017 Oct 9.
[h=1]Estimating influenza vaccine effectiveness: Evolution of methods to better understand effects of confounding in older adults.[/h] McElhaney JE[SUP]1[/SUP], Andrew MK[SUP]2[/SUP], McNeil SA[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Older adults are at high risk for serious complications of influenza illness and loss of vaccine-mediated protection. It is increasingly recognized that in addition to age, multiple chronic conditions and associated frailty contribute to the decline in vaccine effectiveness in this population. However, observational studies have been fraught with issues of confounding related to the degree of frailty and functional decline, measures of which are not included in standard administrative health care databases that are used to calculate vaccine effectiveness. This issue has led to the identification of confounding by indication or from "healthy vaccinee" bias, which respectively lead to underestimates or overestimates of influenza vaccine effectiveness. In addition, the sensitivity and specificity of the criteria used to define influenza-like illness declines with increasing age due to atypical presentations of illness and the inability to distinguish between influenza and other respiratory viruses. The test-negative case:control design has emerged as a method to estimate influenza vaccine effectiveness by comparing vaccination rates in those with laboratory-confirmed influenza to those with other acute viral respiratory illnesses. This review provides a perspective on how test-negative case:control study designs and new insights into mechanisms of protection have considerably strengthened influenza vaccination policy decisions for older adults that have historically been undermined by the conclusions of observational studies.
Copyright ? 2017 Elsevier Ltd. All rights reserved.
[h=4]KEYWORDS:[/h] Hospitalization; Influenza vaccine effectiveness; Older adults; Test-negative case:control design
PMID: 29032898 DOI: 10.1016/j.vaccine.2017.09.084
[h=1]Estimating influenza vaccine effectiveness: Evolution of methods to better understand effects of confounding in older adults.[/h] McElhaney JE[SUP]1[/SUP], Andrew MK[SUP]2[/SUP], McNeil SA[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Older adults are at high risk for serious complications of influenza illness and loss of vaccine-mediated protection. It is increasingly recognized that in addition to age, multiple chronic conditions and associated frailty contribute to the decline in vaccine effectiveness in this population. However, observational studies have been fraught with issues of confounding related to the degree of frailty and functional decline, measures of which are not included in standard administrative health care databases that are used to calculate vaccine effectiveness. This issue has led to the identification of confounding by indication or from "healthy vaccinee" bias, which respectively lead to underestimates or overestimates of influenza vaccine effectiveness. In addition, the sensitivity and specificity of the criteria used to define influenza-like illness declines with increasing age due to atypical presentations of illness and the inability to distinguish between influenza and other respiratory viruses. The test-negative case:control design has emerged as a method to estimate influenza vaccine effectiveness by comparing vaccination rates in those with laboratory-confirmed influenza to those with other acute viral respiratory illnesses. This review provides a perspective on how test-negative case:control study designs and new insights into mechanisms of protection have considerably strengthened influenza vaccination policy decisions for older adults that have historically been undermined by the conclusions of observational studies.
Copyright ? 2017 Elsevier Ltd. All rights reserved.
[h=4]KEYWORDS:[/h] Hospitalization; Influenza vaccine effectiveness; Older adults; Test-negative case:control design
PMID: 29032898 DOI: 10.1016/j.vaccine.2017.09.084