Quantification of length-bias in screening trials with covariate-dependent test sensitivity.

Abstract

Length-biased sampling exists in screening programs where longer duration disease is detected during the preclinical stage because a longer sojourn time (preclinical duration) has a higher probability of being screen detected. By modeling the course of disease, we quantify the effect of length-biased sampling on clinical duration when cases are subject to periodic screening with variable test sensitivity. We use the highly flexible bivariate lognormal density to jointly model preclinical and clinical durations, and we model screening test sensitivity as a function of the sojourn time and number of previous false negative screens. We show that the mean clinical duration among screen-detected cases can be up to 40% higher, with shrinking standard deviation, than those among nonscreen-detected cases, due to biased sampling alone, irrespective of any possible benefit (increased survival time arising from earlier detection or reduction in mortality). These findings will aid in the design and interpretation of screening trials.