Epidemiology, cancer genetics and microarrays: making correct inferences, using appropriate designs

Different disciplines approach cancer with different study designs, techniques and established bodies of knowledge. This article identifies some established epidemiological data and methods, which are useful for cross-disciplinary molecular and genetic studies of cancer but which are ignored by some researchers. First, the international variation in cancer risk is accounted for extensively by variation in environmental exposures; it is unlikely that even minute characterization of individual genomes will provide the best assessment of cancer risk in the absence of comparably detailed information on the environment. Second, epidemiological study-design methods are sometimes the most appropriate to answer molecular questions, particularly when using techniques such as expression microarrays or proteomics to establish differences among cancer subtypes or biomarkers in the setting of a non-experimental study. In such studies, it is essential to avoid bias, control confounding and undertake accurate replication. Established epidemiological data and methods will contribute to the best use of the new molecular technology.