Using Evidence Factors to Clarify Exposure Biomarkers

Am J Epidemiol. 2020 Mar 2;189(3):243-249. doi: 10.1093/aje/kwz263.

Abstract

A study has 2 evidence factors if it permits 2 statistically independent inferences about 1 treatment effect such that each factor is immune to some bias that would invalidate the other factor. Because the 2 factors are statistically independent, the evidence they provide can be combined using methods associated with meta-analysis for independent studies, despite using the same data twice in different ways. We illustrate evidence factors, applying them in a new way in investigations that have both an exposure biomarker and a coarse external measure of exposure to a treatment. To illustrate, we consider the possible effects of cigarette smoking on homocysteine levels, with self-reported smoking and a cotinine biomarker. We examine joint sensitivity of 2 factors to bias from confounding, a central aspect of any observational study.

Keywords: biomarkers; evidence factors; reactive doses; sensitivity to confounding.

MeSH terms

  • Biomarkers*
  • Causality
  • Cigarette Smoking / blood
  • Cotinine / blood
  • Epidemiologic Factors*
  • Female
  • Homocysteine / blood
  • Humans
  • Male
  • Meta-Analysis as Topic*
  • Middle Aged

Substances

  • Biomarkers
  • Homocysteine
  • Cotinine