A stochastic model for tumor control probability that accounts for repair from sublethal damage

The tumor control probability (TCP) is the probability that a treatment regimen of radiation therapy (RT) eradicates all tumor cells in a given tissue. To decrease the toxic effects on healthy cells, RT is usually delivered over a period of weeks in a series of fractions. This allows tumor cells to repair from sublethal damage (RSD) caused by radiation. In this paper, we introduce a stochastic model for tumor response to radiotherapy which accounts for the effects of repair from sublethal damage. The tumor is subdivided into two cell types: affected cells which have been damaged by RT and unaffected cells which have not. The model is formulated as a birth-death process for which we can derive an explicit formula for the TCP. We apply our model to prostate cancer, and find that the radiosensitivity parameters and the probability of sublethal damage during radiation are the parameters to which the TCP predictions are most sensitive. We compare our TCP predictions to those given by Zaider and Minerbo’s one-class model (Zaider and Minerbo, 2000) and Dawson and Hillen’s two-class model (Dawson and Hillen, 2006) and find that for low doses of radiation, our model predicts a lower TCP. Finally, we find that when the probability of sublethal damage during radiation is large, the mean field assumption overestimates the TC