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Activity Number:
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461
- Design and Analytic Approaches to Address Unmeasured Confounding
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #312910
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Title:
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Sensitivity Analyses of Unmeasured and Partially Measured Confounders Using an Imputation Approach in Vaccine Safety Studies
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Author(s):
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Stan (Xuesheng) Xu* and Christina Clarke and Sophia Newcomer and Matthew Daley and Jason Glanz
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Companies:
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Institute for Health Research, Kaiser Colorado and Institute for Health Research, Kaiser Colorado and University of Montana, School of Public and Community Health Sciences and Institute for Health Research, Kaiser Colorado and Institute for Health Research, Kaiser Colorado
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Keywords:
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sensitivity analyses;
unmeasured confounder;
partially measured confounder;
imputation;
quantitative bias analysis;
observational studies
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Abstract:
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Despite the existence of quantitative bias analysis in pharmacoepidemiologic studies, simultaneously adjusting for unmeasured and partially measured confounders is challenging. We derived conditional probabilities for an unmeasured confounder and used them to impute the unmeasured confounder. We simultaneously imputed a partially measured confounder using a prediction model. We considered unmeasured breastfeeding and partially measured family history of Type 1 diabetes (T1DM) in a study examining the association between exposure to rotavirus vaccination and T1DM. Before sensitivity analyses, the hazard ratios (HR) were 1.50 (95% CI, 0.81-2.77) for those partially exposed and 1.03 (95% CI, 0.62-1.72) for those fully exposed with unexposed children as the referent group. When breastfeeding and family history of T1DM were adjusted, the HR was 1.55 (95% CI, 0.84-2.87) for the partially exposed group; the HR was 0.98 (95% CI, 0.58-1.63) for the fully exposed group. We conclude that adjusting for unmeasured breastfeeding and partially measured family history of T1DM did not alter the conclusion that there was no evidence of association between rotavirus vaccination and developing T1DM.
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Authors who are presenting talks have a * after their name.
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