Original ArticleNew strategies are needed to improve the accuracy of influenza vaccine effectiveness estimates among seniors
Introduction
In the United States, inactivated trivalent influenza vaccine is recommended for all persons aged 65 years and older to reduce influenza-related hospitalizations and deaths [1]. Accurately estimating the public health benefit of this strategy is important for pandemic planning and to judge the need for alternate prevention approaches during nonpandemic periods, such as universal childhood immunization to produce herd immunity in seniors [2], [3], [4], [5]. The need for alternative strategies depends on the magnitude of the benefit of the current strategy, which has been recently debated [6], [7], [8], [9], [10].
One problem is that there have been few randomized trials of the efficacy of influenza immunization in older adults, and the available trial evidence is based primarily on healthy, younger seniors. For example, although the largest trial of influenza vaccine efficacy in the elderly, which was restricted to healthy persons, observed a reduction in risk of serologically confirmed uncomplicated influenza infection in participants 60–69 years of age, the study lacked power to draw firm conclusions about the magnitude of vaccine effectiveness among those 70 years and older [11]. Furthermore, the efficacy findings in younger, healthy seniors may not apply to older and frail seniors because advanced age and the presence of serious medical conditions are associated with important changes in the function of the immune system, including a diminished immune response to influenza vaccine [12], [13], [14], [15], [16], [17], [18].
Without data from randomized controlled trials, existing estimates of influenza vaccine effectiveness in seniors derive from observational studies, which may be biased. Numerous observational studies have compared the risk of pneumonia hospitalization and all-cause mortality in vaccinated and unvaccinated seniors during influenza season and have consistently reported substantial reductions in risk for vaccinated seniors, including reductions on the order of 50% for all-cause mortality [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36]. These results have been interpreted by some as evidence that influenza vaccination substantially reduces the risk of death and hospitalization in the elderly [1], [37], [38], [39], [40], [41], [42] and have been incorporated into economic analyses reporting that the senior vaccination program is both cost-saving [20], [21], [43], [44] and among the most effective of all clinical preventive services [45].
However some studies, including a recent review of the literature [6], suggest that bias due to differences between vaccinated and unvaccinated seniors may account for some or all of previously observed risk differences. In the present article, we briefly review the evidence for bias in published observational studies of influenza vaccine effectiveness and then provide a methodological examination of the potential sources of this bias. We draw parallels to bias documented in observational studies of therapies in other areas of medical research, including pharmacoepidemiologic database studies of elderly persons, and we discuss reasons why existing adjustment methods may inadequately control for the bias. Last, we propose and evaluate study design and analytic strategies that may yield more accurate estimation of the public health benefit of influenza vaccine in future studies.
Section snippets
Evidence of bias in existing studies
Existing observational studies of influenza vaccine effectiveness typically use data from research databases, such as the General Practitioners Research database, or health care utilization data systems, such as those maintained by some health maintenance organizations in the United States. Schneeweiss and Avorn [46] have discussed general methodological issues that arise when using such databases in health research including data inaccuracies and residual confounding, but the methodological
Possible sources of bias
A credible explanation recently posed [6], [9] for the source of the healthy vaccinee bias in existing observational studies is selective underuse by frail seniors. Although universally recommended for seniors, receipt of influenza vaccine is voluntary and thus may be preferentially sought by motivated and healthier individuals. This healthy adherer effect has been well documented in evaluations of persons randomized to placebo in randomized trials [51], [52], [53], [54], [55]. For example, in
Problems with existing confounder adjustment methods
Healthy vaccinee bias can be overcome if relevant confounders are measurable and measured well. Most previous observational studies relied solely on information available in research and health care utilization databases to attempt to characterize confounders, often adjusting for the number of outpatient visits and for chronic illness variables defined by groupings of International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnostic codes assigned to patient
Strategies to reduce bias
Given the evidence for bias in existing observational estimates and the inability of previous adjustment methods to control for it, we recommend that new strategies be considered to reduce bias in future studies. First, a wider array of potential predictors of vaccination should be studied to more accurately characterize confounders, particularly given the potency of confounders, such as functional status that are not reliably classified by the information available in research and health care
Conclusion
Assessing the public health benefit of influenza vaccination among elderly individuals is an important problem and one fraught with considerable methodological challenges. There is strong evidence for the presence of bias in existing observational estimates of influenza vaccine effectiveness in the elderly and that current adjustment methods do not adequately control for it. Promising approaches for reducing this bias include obtaining more accurate information on confounders, such as
Acknowledgment
Internal funds supported this publication.
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