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Applying the E Value to Assess the Robustness of Epidemiologic Fields of Inquiry to Unmeasured Confounding.
Trinquart, Ludovic; Erlinger, Adrienne L; Petersen, Julie M; Fox, Matthew; Galea, Sandro.
Afiliação
  • Trinquart L; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.
  • Erlinger AL; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.
  • Petersen JM; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.
  • Fox M; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.
  • Galea S; Department of Global Health, Boston University School of Public Health, Boston, Massachusetts.
Am J Epidemiol ; 188(6): 1174-1180, 2019 06 01.
Article em En | MEDLINE | ID: mdl-30874728
We explored the use of the E value to gauge the robustness of fields of epidemiologic inquiry to unmeasured confounding. We surveyed nutritional and air pollution studies that found statistically significant associations between exposures and incident outcomes. For 100 studies in each field, we extracted adjusted relative effect estimates and associated confidence intervals. We inverted estimates where necessary so that all effects were greater than 1. We calculated E values for both the effect estimate and the lower limit of the 95% confidence interval. Nutritional studies were smaller than air pollution studies (median participants per study, 40,652 vs. 72,460). More than 90% of nutritional studies categorized the exposure, whereas 89% of air pollution studies analyzed the exposure as a continuous variable. The median relative effect was 1.33 in nutrition and 1.16 in air pollution. The corresponding median E values for the estimates were 2.00 and 1.59, respectively. E values for the 95% confidence intervals had median values of 1.39 and 1.26, respectively. Little to moderate unmeasured confounding could explain away most observed associations. The E value is necessarily larger for smaller studies that reach statistical significance, making cross-field comparison difficult. The E value for the 95% confidence interval might be a more useful measure in reports of epidemiologic observational studies.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudos Epidemiológicos / Métodos Epidemiológicos / Fatores de Confusão Epidemiológicos / Interpretação Estatística de Dados Tipo de estudo: Observational_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudos Epidemiológicos / Métodos Epidemiológicos / Fatores de Confusão Epidemiológicos / Interpretação Estatística de Dados Tipo de estudo: Observational_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article