The test-negative design for estimating influenza vaccine effectiveness
► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ► The TN design reduces confounding by differences in health care-seeking. ► TN studies of influenza vaccine must adjust for calendar time. ► TN studies of...
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Published in | Vaccine Vol. 31; no. 17; pp. 2165 - 2168 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier Ltd
19.04.2013
Elsevier Elsevier Limited |
Subjects | |
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Abstract | ► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ► The TN design reduces confounding by differences in health care-seeking. ► TN studies of influenza vaccine must adjust for calendar time. ► TN studies of influenza vaccine must restrict to times when influenza circulates.
The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.
In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.
With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.
The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. |
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AbstractList | ► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ► The TN design reduces confounding by differences in health care-seeking. ► TN studies of influenza vaccine must adjust for calendar time. ► TN studies of influenza vaccine must restrict to times when influenza circulates.
The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.
In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.
With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.
The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. Highlights * We identified the underlying assumptions of the test-negative (TN) design. * The TN design reduces bias due to misclassification of infection. * The TN design reduces confounding by differences in health care-seeking. * TN studies of influenza vaccine must adjust for calendar time. * TN studies of influenza vaccine must restrict to times when influenza circulates. The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed. In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative. With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time. The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. Objective: The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed. Methods: In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative. Results: With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time. Conclusions: The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. Highlights ► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ► The TN design reduces confounding by differences in health care-seeking. ► TN studies of influenza vaccine must adjust for calendar time. ► TN studies of influenza vaccine must restrict to times when influenza circulates. The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.OBJECTIVEThe test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.METHODSIn this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.RESULTSWith the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata.CONCLUSIONSThe test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. |
Author | Jackson, Michael L. Nelson, Jennifer C. |
Author_xml | – sequence: 1 givenname: Michael L. surname: Jackson fullname: Jackson, Michael L. email: jackson.ml@ghc.org organization: Group Health Research Institute. 1730 Minor Ave, Suite 1600, Seattle, WA, 98101-1448, United States – sequence: 2 givenname: Jennifer C. surname: Nelson fullname: Nelson, Jennifer C. organization: Group Health Research Institute. 1730 Minor Ave, Suite 1600, Seattle, WA, 98101-1448, United States |
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Snippet | ► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ► The TN... Highlights ► We identified the underlying assumptions of the test-negative (TN) design. ► The TN design reduces bias due to misclassification of infection. ►... OBJECTIVE: The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational... The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies.... Highlights * We identified the underlying assumptions of the test-negative (TN) design. * The TN design reduces bias due to misclassification of infection. *... Objective: The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational... |
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SubjectTerms | Adolescent Adult Allergy and Immunology Applied microbiology Bias Biological and medical sciences Case–control studies Cohort studies Design Fundamental and applied biological sciences. Psychology Humans Immunization Incidence Infection Influenza Influenza vaccine Influenza Vaccines - immunology Influenza, Human - immunology Influenza, Human - prevention & control Methodology Microbiology observational studies odds ratio Patient Acceptance of Health Care people Research Design Time Factors Treatment Outcome Vaccination Vaccine effectiveness Vaccines Vaccines, antisera, therapeutical immunoglobulins and monoclonal antibodies (general aspects) |
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Title | The test-negative design for estimating influenza vaccine effectiveness |
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