THRESHOLD MODELS OF TUMOR RECURRENCE

The main advantage of threshold models of tumor recurrence is that the y closely parallel the real observation process in cancer post-treatme nt surveillance. Such models are typically based on the assumption tha t a recurrent tumor becomes detectable when its size attains some thre shold value which may be treated as a random variable. This paper disc usses various stochastic models that have been proposed for the analys is of data on tumor latency subject to censoring effects. A new model allowing for surviving clonogenic cells is presented.