Occupational radon exposure and lung cancer mortality: estimating intervention effects using the parametric g-formula.

The association between radon gas exposure and lung cancer has been well-documented in cohorts of underground uranium miners.1-7 However, traditional regression analysis techniques used in these studies focus on quantifying cumulative exposure-response functions that do not directly address the types of questions that concern regulators. The public health impacts of different policy options regarding radon concentrations in the workplace may be more useful to regulators than the estimated change in the excess relative rate of lung cancer per unit increase in cumulative exposure to radon. We apply the extended parametric g-formula8,9 to estimate the risk of lung cancer death had several historical radon exposure standards been in place throughout follow-up in an important cohort study of underground miners. The policy interventions that we consider are specified in terms of caps on monthly occupational radon exposure rather than limits on cumulative exposure (i.e., “limit radon exposure to X working level months per month while at work, and set monthly radon exposure to 0 working level months when not at work”). The interventions we consider are “threshold interventions”10 in which the intervention on radon exposure for a given month depends on the observed exposure for that month. The extended parametric g-formula has been used to estimate cumulative risk under threshold interventions in diverse substantive areas 11-15 . This approach was described by Robins9 to extend the standard parametric g-formula estimator to allow interventions to depend on the natural value of exposure. A formal discussion of the identifying conditions under which the extended parametric g-formula estimator can have a causal interpretation can be found in recent work by Richardson and Robins 16 and Young.17 Our implementation of the parametric g-formula also accommodates competing risks, as outlined by Taubman 11 and Cole.15 Here, we use the g-formula to estimate cumulative incidence of lung cancer mortality under various intervention scenarios and compute risk difference and risk ratio measures, which are often the most relevant estimates to present to the lay public and policy makers. These effect measures have intuitive interpretations as the estimated difference (or ratio) in cumulative incidence that would have been seen had the same population of miners been exposed to different dynamic exposure regimes corresponding to hypothetical industry guidelines. Estimates of attributable risk due to lung cancer derived in previous reports, such as the Biological Effects of Ionizing Radiation (BEIR) IV and BEIR VI reports, and life table calculations also aim to facilitate communication of the public health impact of radon exposure. However, the BEIR reports estimate the attributable fraction of radon-related excess lung cancer deaths, which conforms to change in risk given complete elimination of radon, while we focus on public health impacts of plausible policy interventions (i.e., reduction in radon exposure to specific limits, rather than elimination of radon exposure). In this work, we use the extended parametric g-formula to compare observed lung cancer mortality in the Colorado Plateau Uranium Miners cohort to estimated lung cancer mortality if radon exposure had been limited to three historical radon exposure standards in the U.S.