Comparison between mathematical models of intermittent androgen suppression for prostate cancer

Mathematical modelling is essential for personalizing intermittent androgen suppression, which was proposed to delay the relapse of prostate cancer by stopping and resuming the hormone therapy repeatedly than adopting the conventional continuous androgen suppression, or normal hormonal therapy. Although there are several mathematical models for intermittent androgen suppression, the performances of these mathematical models have not been compared sufficiently. In this paper, we compare the Hirata-Bruchovsky-Aihara model with the Portz-Kuang-Nagy model, two recently proposed models for intermittent androgen suppression. We fitted these mathematical models to the actual data of 17 patients and examined the dynamical behavior and prediction accuracy of these models. Although we found no significant difference between these models in terms of prediction accuracy, the Portz-Kuang-Nagy model could not reproduce the relapse under the simulation condition assuming the continuous androgen suppression. Thus, the results suggest that the Hirata-Bruchovsky-Aihara model is more useful than the Portz-Kuang-Nagy model when we attempt to compare the therapeutic efficiencies of intermittent suppression and continuous androgen suppression.