Do quantitative exposure assessments improve risk estimates in occupational studies of cancer?

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Abstract
Quantitative assessment of exposure intensity is a difficult process, particularly for jobs held long ago. Despite difficulties, the use of this approach is growing in occupational epidemiology because it is hoped that the estimates will more closely approximate delivered dose than more traditional measures such as duration of exposure. If this assumption is correct, development and use of quantitative exposure estimates should reduce nondifferential exposure misclassification, sharpen exposure‐response gradients, and enhance interpretation of study results. In this report, we used two methods to assess the value of quantitative exposure assessments in cancer epidemiology. In one, we surveyed the literature for investigations on occupational cancer that included assessments of both duration and intensity of exposure. The results of this survey indicated that exposure measures based on some measure of intensity of exposure yielded monotonically increasing exposure‐response gradients and larger relative risks more often than those based on duration of exposure. Duration of exposure, however, occasionally provided the larger relative risks. In another approach, we found that different measures of exposure to formaldehyde classified subjects quite differently. For example, duration of exposure was unrelated to average exposure and was only weakly associated with exposure intensity or peak exposure. Because different measures of exposure may classify subjects quite differently and because quantitative estimates usually, but not always, yield larger relative risks and sharper exposure‐response gradients than other measures of exposure, we believe that the prudent approach in epidemiologic investigations would be to develop quantitative estimates of exposure and to conduct analyses using several different measures of exposure, or combinations such as duration by intensity. Multiple comparisons would, however, increase chance findings. The value of such an approach is twofold. When a true association exists, use of several different measures decreases the chances of an unfortunate selection of an exposure measure that is poorly related to delivered dose, which would tend to produce negative results, and increases the chances of uncovering sharper exposure‐response gradients. Use of several exposure measures in investigations that fail to exhibit an association between exposure and disease would be of value because such an approach would provide greater confidence that negative findings were not simply due to exposure misclassification.

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