In epidemiologic studies of two binary exposure factors, much attention has been given to the concept of synergism of the factors.
The leading dictionary of epidemiology offers two definitions of synergism, one of which this author labels statistical and the other biologic.
The epidemiologic literature has been largely concerned with statistical synergism, which is typically measured using additive or multiplicative interaction.
This paper focuses on biologic synergism, on the related concept of biologic parallelism, and on the question of how much information can be gleaned about population amounts of biologic synergism and parallelism-information which is of vital interest to epidemiologists.
A fundamental identity equates the difference between the amounts of biologic synergism and parallelism to the additive interaction.
Two biologic models, the multistage model and the no-hit or immunity model, enhance the interpretation of multiplicative interaction as a measure of statistical synergism, but it is pointed out here that, unfortunately, both models incorporate the strong assumption that there is no parallelism.
A third model, the single-hit or vulnerability model, makes the even stronger assumption that there is no biologic synergism and consequently that the additive interaction is equal to minus the amount of parallelism. (...)
Mots-clés Pascal : Synergie, Parallélisme, Biologie, Epidémiologie, Méthodologie, Modèle mathématique, Analyse statistique
Mots-clés Pascal anglais : Synergism, Parallelism, Biology, Epidemiology, Methodology, Mathematical model, Statistical analysis
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 97-0288203
Code Inist : 002B30A01A1. Création : 15/07/1997.