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 inVaccine Vol. 31; no. 17; pp. 2165 - 2168
Main Authors Jackson, Michael L., Nelson, Jennifer C.
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 19.04.2013
Elsevier
Elsevier Limited
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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.
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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Keywords Case–control studies
Methodology
Influenza vaccine
Cohort studies
Vaccine effectiveness
Infection
Viral disease
Cohort study
Influenza
Case-control studies
Vaccine
Case control study
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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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