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Clin Infect Dis. 2011 Nov 17. [Epub ahead of print]
Magnitude of Potential Biases in a Simulated Case-Control Study of the Effectiveness of Influenza Vaccination.
Ferdinands JM, Shay DK.
Source
Influenza Division, Centers for Disease Control and Prevention.
Abstract
Background. Many influenza vaccine effectiveness estimates have been made using case-control methods. Although several forms of bias may distort estimates of vaccine effectiveness derived from case-control studies, there have been few attempts to quantify the magnitude of these biases.Methods. We estimated the magnitude of potential biases in influenza vaccine effectiveness values derived from case-control studies from several factors, including bias from differential use of diagnostic testing based on influenza vaccine status, imperfect diagnostic test characteristics, and confounding. A decision tree model was used to simulate an influenza vaccine effectiveness case-control study in children. Using probability distributions, we varied the value of factors that influence vaccine effectiveness estimates, including diagnostic test characteristics, vaccine coverage, likelihood of receiving a diagnostic test for influenza, likelihood that a child hospitalized with acute respiratory infection had influenza, and others. Bias was measured as the difference between the effectiveness observed in the simulated case-control study and a true underlying effectiveness value.Results and Conclusions. We found an average difference between observed and true vaccine effectiveness of -11.9%. Observed vaccine effectiveness underestimated the true effectiveness in 88% of model iterations. Diagnostic test specificity exhibited the strongest association with observed vaccine effectiveness, followed by the likelihood of receiving a diagnostic test based on vaccination status and the likelihood that a child hospitalized with acute respiratory infection had influenza. Our findings suggest that the potential biases in case-control studies that we examined tend to result in underestimates of true influenza vaccine effects.
PMID:
22095567
[PubMed - as supplied by publisher]
Magnitude of Potential Biases in a Simulated Case-Control Study of the Effectiveness of Influenza Vaccination.
Ferdinands JM, Shay DK.
Source
Influenza Division, Centers for Disease Control and Prevention.
Abstract
Background. Many influenza vaccine effectiveness estimates have been made using case-control methods. Although several forms of bias may distort estimates of vaccine effectiveness derived from case-control studies, there have been few attempts to quantify the magnitude of these biases.Methods. We estimated the magnitude of potential biases in influenza vaccine effectiveness values derived from case-control studies from several factors, including bias from differential use of diagnostic testing based on influenza vaccine status, imperfect diagnostic test characteristics, and confounding. A decision tree model was used to simulate an influenza vaccine effectiveness case-control study in children. Using probability distributions, we varied the value of factors that influence vaccine effectiveness estimates, including diagnostic test characteristics, vaccine coverage, likelihood of receiving a diagnostic test for influenza, likelihood that a child hospitalized with acute respiratory infection had influenza, and others. Bias was measured as the difference between the effectiveness observed in the simulated case-control study and a true underlying effectiveness value.Results and Conclusions. We found an average difference between observed and true vaccine effectiveness of -11.9%. Observed vaccine effectiveness underestimated the true effectiveness in 88% of model iterations. Diagnostic test specificity exhibited the strongest association with observed vaccine effectiveness, followed by the likelihood of receiving a diagnostic test based on vaccination status and the likelihood that a child hospitalized with acute respiratory infection had influenza. Our findings suggest that the potential biases in case-control studies that we examined tend to result in underestimates of true influenza vaccine effects.
PMID:
22095567
[PubMed - as supplied by publisher]
