Eisen and colleagues have provided a good example of the use of smoothing splines in a thorough analysis of exposure-response data, for a study of lung cancer in relation to silica exposure.¹ Exposure-response data are increasingly important for two reasons.

First, as noted by Bradford Hill, a positive exposure-response provides support for a causal interpretation of an association. In the case of silica and lung cancer, evidence of a positive-exposure response in several studies has provided important support for the original 1997 IARC judgement that silica is a class I (definitive) carcinogen. That judgement has remained controversial because in some studies the exposed population has not had a higher lung cancer rate than the non-exposed comparison group. Some have argued that this may be because the surface properties of silica change in different settings and may have different toxicities, so that in some cases silica may not increase lung cancer risk. However, the explanation may simply be that in some cohorts there were not enough highly exposed subjects. Our own exposure-response analysis of 10 silica exposed cohorts (60 000 workers) indicated that indeed there is a positive exposure-response for silica but that the increase in risk is seen primarily at higher exposures, and the overall slope of the exposure-response curve is relatively low compared to classic lung carcinogens such as nickel and asbestos.⁵ This relatively low slope may be the reason why it has been it has been difficult to show that silica does indeed cause lung cancer.

Second, exposure-response data provide necessary data for regulators …