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Radiat Res. 1995 Dec;144(3):329-41.

Errors in exposure assessment, statistical power and the interpretation of residential radon studies.

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  • 1Epidemiology and Biostatistics Program, National Cancer Institute, Bethesda, Maryland 20892-7368, USA.


To date, epidemiological studies of risk from residential radon have not convincingly demonstrated an association with lung cancer. These case-control studies, however, have inherent limitations due to errors in estimates of exposure to indoor radon. These errors take on special significance because the level of residential risk predicted from studies of underground miners is relatively low and possibly at the limit detectable by current epidemiological methods. To illustrate the problem caused by errors in exposure assessment, a series of case-control studies were simulated and resulting dose-response relationships evaluated. For each of four assumed error distributions for exposure to radon progeny, 10 indoor radon studies of 700 cases and 700 controls were generated randomly from a population with a risk of radon-induced lung cancer based on extrapolations from studies of underground miners. When exposures were assumed as known without error, 6 of 10 studies failed to find a significant dose response, in accord with the theoretical power of the study of 0.47. For simulations in which exposures were measured with error, the situation was worse, as the power of the study was reduced further and it was even less likely that a single study would result in a significant finding. For each error scenario, combining data from the 10 simulated studies did result in a significant dose response. However, the pooled results are somewhat misleading, because the effects of mobility, missing radon measurements, residential occupancy and potential confounding variables such as cigarette smoking were not taken into account. Empirical estimates of power were computed using 1,000 simulated case-control studies. When mobility and missing radon measurements in prior homes were incorporated into the design, the power of the study decreased, reducing the chance of detecting a significant effect of exposure. Enlarging study size to 2,000 cases and 2,000 controls increased the power of the study to 0.90 when exposure error was absent and subjects lived in one home only, but power was below 0.40 under realistic conditions for exposure error and mobility. When studies were generated under an assumption that exposure does not increase risk, up to 15% of simulated studies with 700 cases and 700 controls resulted in an estimated dose-response parameter in excess of the dose response from studies of miners. With increasing mobility and exposure error, it became virtually impossible to distinguish between the distributions of risk estimates from simulated studies based on an underlying excess relative risk of 0.015/working level month from estimates based on no risk from exposure.(ABSTRACT TRUNCATED AT 400 WORDS)

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