Confounding after risk-set sampling in the beryllium study of Sanderson et al

Abstract

Purpose: Beryllium is classified as carcinogenic on the basis largely of limited human data showing a modest increase in lung cancer from occupational exposure. With occupational exposure now curtailed, earlier results merit more scrutiny. We simulated data to understand the design implications of a landmark case-control study.

Methods: We generated datasets from the original occupational cohort by randomly assigning lung cancer events to workers independently of their exposure. We analyzed the simulated data on the basis of different modes of risk-set sampling, with risk sets defined by calendar time, age, or both, to assess how much bias existed using several exposure metrics. We controlled for several time related variables to assess confounding. Finally, we re-analyzed the data from the original study, controlling for time-related covariates.

Results: No bias occurred using any type of risk-set sampling with unlagged exposures. When exposure was lagged 10 or 20 years, however, there was considerable confounding by year of birth and year of hire, which remained uncontrolled in the original study.

Conclusions: Simulations and reanalysis show that much of the reported association with lagged exposure is attributable to confounding by year of birth and year of hire. Lagging changes the exposure variable and can thus lead to changes in the amount of confounding.