Statistical tests of carcinogenicity are shown to have varying degrees of robustness to the effects of mortality. Mortality induced by two different mechanisms is studied--mortality due to the tumor of interest, and mortality due to treatment independent of the tumor. The two most commonly used tests, the life-table test and the Cochran-Armitage linear trend test, are seen to be highly sensitive to increases in treatment lethality using small-sample simulations. Increases in tumor lethality are seen to affect the performance of commonly used prevalence tests such as logistic regression. A simple survival-adjusted quantal response test appears to be the most robust of all the procedures considered.