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Corraini P, Olsen M, Pedersen L, et al. Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators. Clin Epidemiol. 2017;9:331-338doi: 10.2147/CLEP.S129728.
Corraini, P., Olsen, M., Pedersen, L., Dekkers, O. M., & Vandenbroucke, J. P. (2017). Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators. Clinical epidemiology, 9331-338. https://doi.org/10.2147/CLEP.S129728
Corraini, Priscila, et al. "Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators." Clinical epidemiology vol. 9 (2017): 331-338. doi: https://doi.org/10.2147/CLEP.S129728
Corraini P, Olsen M, Pedersen L, Dekkers OM, Vandenbroucke JP. Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators. Clin Epidemiol. 2017 Jun 08;9:331-338. doi: 10.2147/CLEP.S129728. eCollection 2017. PMID: 28652815; PMCID: PMC5476432.
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Clin Epidemiol. 2017 Jun 08;9:331-338. doi: 10.2147/CLEP.S129728. eCollection 2017.

Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators.

Clinical epidemiology

Priscila Corraini, Morten Olsen, Lars Pedersen, Olaf M Dekkers, Jan P Vandenbroucke

Affiliations

  1. Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark.
  2. Leiden University Medical Center, Leiden, the Netherlands.
  3. Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

PMID: 28652815 PMCID: PMC5476432 DOI: 10.2147/CLEP.S129728

Abstract

We revisited the three interrelated epidemiological concepts of effect modification, interaction and mediation for clinical investigators and examined their applicability when using research databases. The standard methods that are available to assess interaction, effect modification and mediation are explained and exemplified. For each concept, we first give a simple "best-case" example from a randomized controlled trial, followed by a structurally similar example from an observational study using research databases. Our explanation of the examples is based on recent theoretical developments and insights in the context of large health care databases. Terminology is sometimes ambiguous for what constitutes effect modification and interaction. The strong assumptions underlying the assessment of interaction, and particularly mediation, require clinicians and epidemiologists to take extra care when conducting observational studies in the context of health care databases. These strong assumptions may limit the applicability of interaction and mediation assessments, at least until the biases and limitations of these assessments when using large research databases are clarified.

Keywords: effect modifiers; epidemiology; health care administrative claims; methods; stratified analyses

Conflict of interest statement

Disclosure The authors report no conflicts of interest in this work.

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