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American Journal of Epidemiology Vol. 136, No. 9: 1174
Copyright © 1992 by The Johns Hopkins University School of Hygiene and Public Health


correction

ERRATUM

Lars Järup and Göran Pershagen

Department of Occupational Medicine, Karolinska Hospital S-104 01 Stockholm, Sweden
Department of Epidemiology Institute of Environmental Medicine, Karolinska Institute S-104 01 Stockholm, Sweden

ABSTRACT

We have discovered an error in our article on arsenic exposure, smoking, and lung cancer in smelter workers (1). Because of a computational error, table 4 on page 549 of our article is not valid. When we excluded smoking-related causes of death among the controls, the remaining number of matched sets was too small to permit further analysis. Therefore, we dissolved the matching and applied unmatched analysis. In the change from matched analysis (conditional logistic regression) to unmatched analysis (logistic regression), a key variable remained unchanged by mistake, leading the computer to believe that the number of controls within each stratum was much larger than it actually was. Thus, the regression mistakenly converged, giving rise to the erroneous data in table 4.

We used the EGRET computer program in our analysis (2). The manufacturer of the EGRET package (Statistics and Epidemiology Research Corporation, Seattle, Washington) is aware of this potential problem and has modified the program to avoid mistakes of this type in the future.

We have now merged the upper two exposure categories to achieve convergence. The results of this reanalysis are shown in table 1.

Compared with those in the original table, the reanalyzed odds ratios are less stable, with wider 95 percent confidence intervals. In the article, we stated that there was a stronger dose-response relation between arsenic exposure and lung cancer among light and medium smokers than among heavy smokers, a phenomenon that has also been seen in other studies of lung carcinogens (3). Despite the wider confidence intervals, this still seems to be true, but the statistical uncertainty is too large to permit any firm conclusions.


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