Maggie Au
Many cancer treatment trials are conducted in unscreened populations. As cancer screening becomes more prevalent the questionable validity of these trial results in the presence of screening is increasingly pertinent. We evaluate the impact of screening on treatment efficacy estimates. We develop expressions for cause-specific cumulative incidence in the presence of screening and use these to simulate results under different settings of lead time, overdiagnosis, treatment efficacy, and other-cause survival. Under screening, we see a reduction in the difference in cumulative incidence of prostate cancer death between the two treatment arms, a corresponding reduction in the power of a study to detect a treatment effect, and an increase in the NNT (number needed to treat). These results clearly indicate that it is important to recognize that, under screening, treatments may not attain the benefits and may cost more than would have been expected based on clinical trials of their effect in the absence of screening. Conversely, treatments shown to be ineffective in trials done in a screened population could turn out to be worthwhile in populations where screening is not performed at the population level. Addressing and taking into account these differences that result from screening is an important next step in developing appropriate clinical practice for a population based on trial results.
