Correcting for Healthy-Worker Survivor Bias of the Radon-lung Cancer Dose-response in a Cohort of Uranium Miners using Structural Nested Accelerated Failure Time Models

Abstract

Radon is estimated to cause over 20,000 lung cancer deaths per year in the United States. Occupational studies have been used to estimate population risks. These studies may be subject to healthy worker survivor bias, though this potential bias has not been thoroughly explored. Healthy worker survivor bias can be conceptualized as time-varying confounding by employment status. This confounding is problematic for regression models when radon exposure influences employment status. We estimate the time ratio (the relative decrease in median survival per 100 working level months, a unit of occupational radon exposure) using data from the Colorado Plateau uranium miners cohort. We estimated the association between radon and lung cancer, with and without control for the healthy-worker survivor bias using G-estimation of a structural nested accelerated failure time model. In a structural nested model not adjusted for healthy worker survivor bias, we estimate a time ratio (95% confidence intervals) per 100 working level months of 1.055 (1.055, 1.055). When we control this bias, the estimate is 1.168 (1.152, 1.174). We found that cumulative radon exposure was associated with leaving work, consistent with employment status being a confounder and intermediate variable, such that standard regression methods are biased. These findings suggest that healthy worker survivor bias leads to an underestimate of the effects of radon. Further, standard analyses of the radon-lung cancer dose-response cannot adequately control this bias, warranting re-examination of the current estimates of radon's carcinogenic effects.