Methodological Challenges in the Statistical Analysis of Epidemiology Studies: use of Average Exposure Metrics in Historical Cohort Designs

Abstract

An important methodological challenge in the analysis of historical occupational cohort data is choosing the most appropriate metric for the average exposure of the workers under study. We describe and illustrate the many issues associated with this challenge using a recent re-analysis by Kopylev [1] of lung cancer mortality in the National Cancer Institute (NCI) acrylonitrile cohort study. Kopylev proposed the routine use of both Average Exposure and Average Intensity when analyzing epidemiological cohort data. However, due to the methodological issues that arise with these metrics, we have concerns about the validity of his finding of a significant positive association between workers’ acrylonitrile exposure and increased lung cancer mortality in a subset of the NCI cohort. These include 1) the opportunity for substantial selection bias to have impacted the results; 2) the failure to account properly for latency; 3) the absence of a convincing biological rationale or other a priori justification for Kopylev’s preferred exposure metrics; 4) the absence of meaningful differences in Average Exposure- and Average Intensity- based risk estimates; 5) the lack of a logical basis for using either of these exposure metrics and 6) the conclusion that smoking was not a significant positive confounder, which is at odds with all other such findings for this cohort.