Can We Interpret Analyses of Etiologic Heterogeneity When Molecular Markers Are Used to Classify Tumors?

Analyses of etiologic heterogeneity use molecular markers to subtype cancers (e.g., breast cancer) and test whether an exposure is more strongly associated with one tumor subtype as opposed to other subtypes. However, these molecular markers (e.g., a mutated oncogene) may best be conceptualized as mediators of exposure-disease relationships.

Seven model causal scenarios, based on data from the literature on postmenopausal breast cancer, were created with varying relationships between an exposure, a mediating or non-mediating molecular marker, and a disease status, with molecular marker used to subtype the disease. Using numerical examples, we assessed how well the analyses of etiologic heterogeneity identify the distinct etiologic pathways in these seven scenarios.

Etiologic heterogeneity analyses of the data from the four causal mediation models produced similar results despite the mediating role of molecular marker differing across scenarios, with heterogeneity effect sizes ranging from 1.47 to 1.60. Analyses of data from the two scenarios, in which molecular marker did not affect the risk of disease, also produced evidence of etiologic heterogeneity, with heterogeneity effect sizes of 1.53 and 2.66. The smallest heterogeneity effect size (1.33) was observed in the scenario in which molecular marker was a sufficient cause of disease.

This methodologic research indicates that analyses of etiologic heterogeneity cannot distinguish between the modeled causal scenarios when a mediating or non-mediating molecular marker is used to subtype tumors.

We discuss these results in the context of the literature on obesity and etiologic heterogeneity in breast tumors subtyped by sex hormone receptor status.